timps-swarm

Server Quality Checklist

Profile completionA complete profile improves this server's visibility in search results.

Latest release: v2.2.1
Disambiguation1/5
Many tools have identical or nearly identical purposes, such as timps_log_detective and timps_log_pattern_analyzer with the exact same description, timps_flaky_test_detective and timps_flaky_test_hunter, and timps_research_scout, timps_research_agent, and timps_deep_research_agent. With 161 tools, an agent would frequently face ambiguous choices.
Naming Consistency4/5
All tools share the 'timps_' prefix and use snake_case. Most follow a noun-based naming (e.g., timps_system_optimizer) or verb+noun (e.g., timps_list_agents). Though some names are vague (timps_dispatch, timps_run_task), the pattern is fairly consistent.
Tool Count1/5
Having 161 tools is far beyond any reasonable scope. It overwhelms the agent and creates a maintenance nightmare. Even a very broad server should not exceed 50 tools; this is extreme and impractical.
Completeness3/5
The tool set covers an enormous range of domains, but many are redundant and some basic lifecycle operations (e.g., update/delete for most agents) are missing. The breadth gives coverage, but the lack of consolidation and repetitive agents indicates an incomplete and poorly structured surface.
Average 3.5/5 across 154 of 161 tools scored. Lowest: 1.8/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 19 commits in the last 12 weeks
- Last stable release on June 11, 2026
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is failing
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
Add related servers to improve discoverability.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided for this tool serious behavioral gaps. The description is a passive statement of purpose and does not disclose whether it performs mutations, requires authentication, makes external calls to GrowthBook, or what type of output (configuration snippet, plan, report) it produces. With zero annotation coverage and no behavioral details, this is severely lacking.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very short – a single sentence – which is inherently concise employment of words. However, it is under-specified to the point of being nearly a title. It lacks structure, such as listing capabilities or important details. While it has no fluff, it is overly minimal and fails to be informative enough to warrant a high score.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no annotations and no output schema, the description should compensate by explaining expected inputs (e.g., what 'request' should contain), what the tool actually produces (Welch's t-test power analysis results, a GrowthBook config snippet), and any dependencies or constraints. The description is a single sentence, not enough to guide an agent on how to interact effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema describes two parameters: 'request' (plain-English task) and 'language' (programming language). The description does not add more detail than the schema's own descriptions. Given 100% schema coverage, the baseline of 3 is appropriate, but the description adds no extra meaning beyond reinforcing the A/B testing context.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states 'Design A/B tests with Welch's t-test power analysis and GrowthBook configuration', which names a specific activity (designing A/B tests) and includes technical details (Welch's t-test, GrowthBook). However, it does not convey what the tool actually does beyond the name 'timps_ab_testing_agent' - it essentially restates the name with a phrase. It lacks clarity on whether this tool analyzes, configures, or generates something, and how it differs from sibling tools like timps_analytics_agent or timps_feature_flag.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives. It does not mention when this tool is appropriate, when not to use it, or any prerequisites. The description merely states the task in general terms without context or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full behavioral transparency burden. It mentions reading pytest failure cache and scanning for specific flake sources, but doesn't disclose whether the tool only analyzes the pytest cache or also runs tests, what side effects (if any) exist, or what the output format looks like. For a diagnostic tool, the agent would benefit from knowing whether this is read-only or might execute tests.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise at two sentences, front-loading the purpose with the verb 'identify.' The first sentence is actionable, and the second provides context about the data source. No wasted words, but it's minimal.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
There is no output schema and no annotation, and the only parameter is unexplained. The description tells the agent what it does but not how to invoke it, what inputs are expected, what outputs are produced, or what side effects might occur. For a tool that presumably needs a repo path going into a pytest cache, this is insufficient for reliable invocation. It also doesn't differentiate from timps_flaky_test_hunter or other similar tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has one parameter (repo_path) with no description, and schema coverage is 0%. The description never mentions repo_path or what it should contain (e.g., a path to the project root). The description assumes a context but provides zero parameter guidance. With only 0% schema coverage)Skip, the description must compensate, but it doesn't address the parameter at all.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: identifying flaky tests by scanning for timing dependencies, random data, and external HTTP calls. The verb 'Identify' plus the specific resource ('flaky tests') and the three detection heuristics make the tool's function clear. It's distinct from siblings like timps_test_intelligence or timps_log_pattern_analyzer, though not explicitly differentiated.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description mentions it reads the pytest failure cache but provides no guidance on when to use this tool over alternatives like timps_flaky_test_hunter or timps_test_intelligence. There's no mention of prerequisites (e.g., needing a configured repo_path), limitations, or exclusions. A specialized tool like this would benefit from clear advice on when to choose it over the similarly-named timps_flaky_test_hunter.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations, so the description must carry the burden of explaining behavior. It does not state whether the agent produces a plan, performs setup steps, computes pricing, generates invoices, or takes actions such as installing dependencies or creating files. The observable behavior remains largely opaque.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, compact phrase with no filler words. It front-loads the central purpose and lists concrete focus areas efficiently. It is terse but not wordy; the main weakness is under-specification, not lack of conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, no output schema, and only generic free-text parameters, the description does not sufficiently clarify expected deliverables, tool boundaries, or behavior. While an agent could infer a GTM planning scope, it gets no indication of what the agent will actually return or how it should behave.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema fully describes both parameters (`request` and `language`), so the description does not need to repeat them. However, the description also adds no extra semantic nuance beyond the schema, such as expected formats for the request or how the language parameter influences outputs.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description identifies a clear domain—India GTM planning—with specific elements like INR pricing, Razorpay, and GST invoicing. However, it lacks an explicit verb or action (e.g., 'creates', 'generates', 'advises'), so it reads more like a topic tag than a precise tool purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided about when to choose this tool over alternatives, such as timps_gst_compliance, timps_upi_agent, or timps_monetization_agent. The intended use case is implied by the name and description, but there are no explicit usage conditions or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry full transparency burden. It only states it scans and returns a plan, without disclosing read-only nature, permission requirements, or potential side effects. This is a significant gap for a potential analysis tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with two short sentences, efficiently stating the core action and output. No unnecessary words or repetitions.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has no output schema, the description should clarify what the 'prioritised debt repayment plan' includes or how it is formatted. It also doesn't mention prerequisites (e.g., a valid repo path) or any limitations, leaving the tool under-specified for its complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has one parameter (repo_path) with no description, and schema description coverage is 0%. The tool description does not mention the parameter at all, leaving its purpose and constraints completely unexplained.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states it scans for TODO/FIXME density, cyclomatic complexity hotspots, and deprecated patterns, and returns a prioritised repayment plan. However, it does not differentiate from sibling tools like timps_technical_debt, which likely overlaps, so it stops short of a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool compared to alternatives like timps_technical_debt or timps_full_checkup. The description only states what it does, not when it should be selected.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It only states the action (generate) and outputs, but does not disclose side effects, file modifications, permissions needed, or any limitations. No behavioral context is given.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence listing all outputs, which is concise and without fluff. However, it is a long list that could benefit from structured formatting or front-loading, but it remains efficient and readable.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (generating multiple artifacts) and lack of annotations/output schema, the description is incomplete. It does not explain the workflow, required inputs, or what the generated outputs look like, making it insufficient for the agent to use effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not mention any parameters. It does not explain how framework, design_system, accessibility_level, or description are used, leaving the agent to infer from enums alone. The description adds no semantic value over the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool generates a UI component spec, implementation code, Storybook story, design tokens, and WCAG accessibility audit. It uses a specific verb (Generate) and lists concrete resources, distinguishing it from siblings due to its comprehensive scope, even though timps_storybook_story_generator overlaps partially.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like timps_storybook_story_generator or timps_accessibility_tester. It does not mention contexts, prerequisites, or when to avoid it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It does not state whether the tool is read-only, what side effects might occur (e.g., AWS CLI calls), what permissions are needed, or what the output format is. The description implies an audit but doesn't clarify if it mutates anything or only reports.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, relatively concise sentence covering both main actions. It's front-loaded with the purpose. However, the sentence is dense and jumps between two concepts (Terraform scanning and AWS CLI checking) without clear structural separation.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no annotations, no output schema, and a single optional parameter, the description must carry significant context. It mentions what it scans but omits what the results look like, how to interpret findings, whether it writes any files, and what environments it supports. This is incomplete for a tool that combines IaC scanning with live CLI checks.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has one parameter (repo_path, optional) with 0% description coverage. The description never mentions repo_path or what it represents (e.g., GitHub repo path, local filesystem path). Since the schema provides no defaults or descriptions, the description should have explained this parameter, and it doesn't.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the primary action: scanning Terraform configs for waste and checking AWS CLI for idle resources. This gives a specific verb (scan/check) and resources (Terraform configs, AWS CLI). However, it doesn't explicitly differentiate from similar sibling tools like timps_cost_optimizer or timps_finops_agent, which could overlap in purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is used to audit Terraform configs and AWS CLI resources, but it provides no explicit guidance on when to use this tool versus alternatives like timps_terraform_plan_reviewer or timps_cost_optimizer. No when-not-to-use or prerequisite conditions are stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of disclosing behavioral traits, but it only lists outputs and gives no indication of side effects (e.g., whether it makes network calls, requires authentication, or has side effects). It doesn't disclose return format, potential side effects, or any operational behavior beyond 'generate'. This is a significant gap for a tool that could be expected to interact with external monitoring systems.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence that efficiently enumerates the tool's outputs. It has no redundant words and immediately conveys the core function. Every part is necessary.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (4 parameters, multiple output types) and the absence of annotations and output schema, the description is under-specified. It doesn't clarify how the tool decides which artifacts to generate, what the expected behavior with no 'slos' is, or how language/alerting_platform affect the output. The description is too terse to be considered complete for this generation tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds zero parameter-related information. With schema coverage at only 25% (only one of four parameters has a description in the schema), the description's complete silence on parameters such as 'slos', 'language', and 'alerting_platform' leaves the agent without adequate context to use the tool correctly. The description fails to compensate for the sparse schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a strong imperative verb 'Generate' and lists specific artifacts (Prometheus metric definitions, Grafana dashboard JSON, alerting rules, instrumentation code snippets), making the tool's core purpose clear and distinct from many unrelated siblings. However, it does not explicitly differentiate itself from closely related tools like timps_observability_cost_optimizer or timps_model_perf_monitor, so it falls slightly short of a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It merely states what it generates, without any context on use cases, prerequisites, or scenarios where another tool might be more appropriate. No exclusions or alternative tool references are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations, and the description provides no information about side effects, permissions, rate limits, or whether operations are read-only or mutate state. The description carries the full burden but fails to disclose any behavioral traits beyond the basic function.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise, consisting of two short sentences with no redundant information or fluff. It is well-structured and to the point.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description lacks critical context for a complex web3 tool. It does not explain what 'audit' entails, what 'Slither/Mythril patterns' refer to, or what the output format might be. There is no mention of return values or how the generated code is delivered, making the description incomplete for agent usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already provides descriptions for both parameters (request and language), covering their meanings. The tool description does not add any additional value or context beyond what the schema states, so it meets the baseline for parameter semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's two main functions: auditing smart contracts with Slither/Mythril patterns and generating Solidity code with gas optimisation. It is specific enough to distinguish it from the many sibling timps_* tools, though 'with Slither/Mythril patterns' could be clearer.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not specify when to use this tool versus alternatives, nor does it provide any context about prerequisites or conditions under which it should be invoked. It only describes what it does without guiding usage decisions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description does not disclose any side effects, permissions, or limitations. It is a simple statement without behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, concise and to the point.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description lacks information on input/output format, usage examples, and edge cases, making it incomplete for practical use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool description does not explain the parameters 'request' and 'language' nor how they influence the audit. The schema descriptions are generic and insufficient.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool audits LLM applications against OWASP LLM Top 10 with mitigations, providing a specific action and scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not provide any guidance on when to use this tool versus other security tools, nor does it mention alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description fully carries the behavioral burden. It describes the transformation (workflow → code) but doesn't mention outputs, side effects, limits, or require that `request` be in plain English despite being explicitly described as 'plain-English'. The description mentions it produces 'code, diagram, and tests' but doesn't say what happens to existing files or whether it modifies anything.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single clear sentence, well front-loaded with the core purpose. Could benefit from example input/output or sample usage.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and only 2 simple params, the description covers the essentials: input type, target frameworks, and outputs (code, diagram, tests). The missing piece is output format details, but for a no-output-schema tool this is acceptable.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 2 parameters at 100% coverage — 'request' is described as 'Plain-English task or context' and 'language' has a default. The description adds 'multi-step workflow' specificity but the parameter names carry most of the meaning. Baseline 3 is appropriate since schema covers everything.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description specifies generating executable code for three named frameworks plus a Mermaid diagram and tests from a plain-English workflow. It clearly distinguishes itself from sibling workflow/automation tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description doesn't explain when to use this tool or when alternatives are better. No mention of input characteristics, complexity limits, or when a simpler tool might suffice.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations are absent, so the description bears full responsibility for behavioral disclosure. It states outcomes (risk score, backup script) but doesn't clarify whether the script is executed, written to a file, or returned as text. It doesn't mention permissions, potential side effects (e.g., creating backup scripts), or safety implications. The ambiguity around what 'backup script' means is a transparency gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
One sentence, front-loaded with the action verb and audit scope. It's efficient and readable. No fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description doesn't explain the output format or how the backup script is delivered (file? console?), and with no output schema the agent lacks that context. Given it's a multi-part audit producing both results and a script, this is a moderate gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters, so baseline is 3. The description adds no parameter-specific guidance, which is acceptable given there are no parameters to document.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description starts with a clear action verb (
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. With dozens of sibling tools (e.g., timps_full_checkup, timps_disk_space_prophet), the agent has no basis to choose this over others. No prerequisites, exclusions, or context for when this is the right tool are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose any behavioral aspects such as permissions, side effects, rate limits, or whether it sends emails or just generates content. The mention of 'spam-safe' is a feature, not a transparency disclosure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence that efficiently conveys all key features without unnecessary fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the main purpose and output elements but lacks information about the output format (since there's no output schema) and any prerequisites or context needed to use the tool effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema descriptions are minimal. The tool description does not add clarity to the 'request' parameter (e.g., what details like persona and offer should be included) or the 'language' parameter, which is confusingly described as a programming language despite being used for email sequences.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: writing a 5-7 step cold-outreach email sequence. It specifies key elements like persona, offer, subject variants, social proof, objection handling, CTA, and spam-safe, making it distinct from other technical tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not provide explicit guidance on when to use this tool versus alternatives. It only describes what it does, without mentioning conditions, scenarios, or comparisons to other tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. It mentions the tool will 'audit' and produce a 'remediation roadmap' but does not explain what happens during the audit (e.g., whether it modifies any settings, requires input files, or performs read-only analysis). The description lacks depth about potential side effects or dependencies.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, efficient and front-loaded with the main purpose. It packs key compliance areas into a list without verbosity. However, it omits necessary details about parameters or audit scope, but the structure is clean and concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (legal compliance audit) and the minimal schema (2 params, no output schema, no annotations), the description is incomplete. It fails to specify what inputs are required (e.g., system documentation, data flow diagrams), what the output looks like beyond 'roadmap', or any limitations. The lack of output schema makes the description more critical, yet it leaves major gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema covers both parameters with descriptions, but the description adds no extra meaning. 'request' is vaguely defined as 'Plain-English task or context' and 'language' as a programming language, yet the tool's core function is a compliance audit — it's unclear why a 'language' parameter is needed or what 'request' should specifically include. The description fails to elaborate how these params drive the audit.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool audits systems or data flows against India's DPDP Act 2023, specifying the key compliance areas (consent, notice, rights, breach, penalties) and outputs a remediation roadmap. This distinguishes it from generic compliance or security auditors in the sibling list, though it doesn't explicitly contrast with them.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is for DPDP Act compliance audits but does not explicitly state when to use it versus alternatives like timps_compliance_auditor or timps_security_guard. It lacks guidance on exclusions or specific use cases beyond the general 'audit a system or data flow' context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description bears the full burden of behavioral disclosure; however, it only names the outputs (recommendations, budget alerts) without revealing any side effects, prerequisites, or operational details. It doesn't mention that running Infracost likely requires network calls, API keys, or external tooling, nor whether any action is taken or just recommended. The description is purely functional and leaves the agent unaware of the tool's full operational footprint.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, scannable sentence that front-loads the key verb and object, making it efficient and easy to parse. The only deduction is that it borders on under-specification, conflating brevity with conciseness by omitting essential details about how to use the tool effectively.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with a generic 'request' parameter and zero required arguments, the description does too little work. It provides no examples of valid 'requests', no clarification of the output format (text, JSON, tags), and no mention of common constraints (e.g., cloud provider, cost data sources, refresh frequency). The tool—potentially a powerful FinOps agent—feels underspecified in its current form, leaving too much to be inferred if Infracost is unavailable or configured differently than expected.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3 per the rubric, and the schema does provide short descriptions for both 'request' and 'language'. However, the description itself adds no semantic clarity—especially for the unexpected 'language' parameter (why would a FinOps agent need a primary programming language?), which is surprising given the schema includes it. The description misses the opportunity to explain whether 'language' refers to IaC type, cost data format, or something else entirely.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the verb ('analyse'), resource ('cloud costs'), specific tooling ('Infracost'), and concrete outputs ('rightsizing recommendations and budget alerts'). The main deduction is that it doesn't distinguish itself from obviously overlapping siblings like timps_cloud_cost_auditor, timps_cost_optimizer, and timps_observability_cost_optimizer—close cost-focused tools where differentiation would be valuable.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided for when to use this tool versus the many adjacent siblings—particularly timps_cloud_cost_auditor, timps_cost_optimizer, and timps_observability_cost_optimizer, which cover similar ground. There is no mention of the use case (e.g., 'use this for Infracost-generated reports' or 'when you need budget alerts'), so an agent would struggle to select the right tool from the large set of cost-related options.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description clearly states the tool extracts strings, generates JSON files, and flags issues, which is transparent about its primary actions. However, it does not disclose any potential side effects such as file overwriting, network calls, or limitations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence listing the three main actions. It is concise and well-structured without unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description gives an overview of functionality but omits details on input expectations, output format, or return values. Since there is no output schema, the agent may not know what results to expect, making it incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool description does not elaborate on the meaning or role of any of the four parameters. It only mentions 'multiple locales' without connecting to target_locales, and the schema descriptions are equally minimal, so the description adds no additional parameter context.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description precisely states the tool's purpose: extracting translatable strings, generating translation JSON files for multiple locales, and flagging RTL/cultural issues. This is specific and easily distinguishes it from generic agents.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not provide any guidance on when to use this tool compared to other agents. It simply states the tool's functions without context on appropriate scenarios or alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It suggests read-only analysis ('analyse', 'distil') but doesn't disclose side effects—does it write improvements back to disk, require history/state, or have side effects on other agents' configs? For a tool that improves 'all agents', the absence of side-effect and access information is a notable gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
A single, concise 11-word sentence that is front-loaded with the primary action ('Analyse past successful runs'). Every word earns its place; no filler or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no output schema and an ambiguous optional 'request' parameter, the description should clarify expected outputs, side effects, or typical invocation context. Given the enormous sibling list with many similar-sounding agents, the description should do more to disambiguate when this is the right agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3 per the rubric. The description adds no parameter detail, but the schema documents 'request' and 'language' adequately. The description could have explained why 'language' matters for a learning agent, but the schema does the heavy lifting here.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses specific verbs and resources: 'Analyse past successful runs' and 'distil prompt improvements', clearly scoped to 'all agents'. It differentiates from siblings like timps_run_task and timps_self_critic_agent by focusing on learning/optimizing from past runs. However, it's slightly generic and could be mistaken for a meta-tool without more operational context.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given on when to use this tool versus the many overlapping siblings (timps_pattern_detector, timps_self_critic_agent, timps_run_task, timps_agent_composer). The learning intent is implied but there's no explicit when/when-not, no exclusions, and no mention of alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden of behavioral disclosure. It fails to disclose side effects (e.g., persistence behavior of 'store', scope of 'manage', whether recall has side effects), permission requirements, or reversibility. The exotic term 'contextual memory' is left undefined. The description merely restates the basic function without behavioral depth.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single 12-word sentence with no wasted words or redundancy. The most informative content ('Store, recall, and manage') is front-loaded. However, like the 'update_drive' calibration example, it is an efficient single sentence—concise but not over-condensed to the point of tautology.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no annotations, no output schema, and a vague term like 'contextual memory,' the description leaves much to be desired. The natural-language 'request' parameter is the primary interface, yet the description doesn't clarify what kinds of requests are appropriate, what 'run history' includes, or what the agent returns. For a tool with such broad delegation capability, this is a significant gap in a simple context with minimal other documentation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%: 'request' is documented as 'Plain-English task or context for the agent' and 'language' as 'Primary programming language (default: python).' At the high-coverage baseline, the description doesn't need to add parameter details, but it also fails to add anything beyond the schema. The baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses specific verbs ('Store, recall, and manage') with a clear resource ('TIMPS run history and contextual memory'). This clearly states the tool's function but does not differentiate it from potentially overlapping siblings like timps_context_switcher or timps_context_briefing, so it earns a 4 rather than a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus the 160+ siblings, no exclusion criteria, and no mention of when it would NOT be appropriate. The usage is only barely implied by the purpose statement, which is not enough given the vast tool landscape. There are no alternatives mentioned, so it fails to guide tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It implies configuration actions (which are likely mutating and potentially destructive), but it doesn't disclose any side effects, required permissions, or whether it makes live changes versus dry-runs. The agent lacks critical safety information.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that lists the key capabilities. It is front-loaded with the main verb ('Configure') and covers the essentials without fluff. It could be slightly more detailed but stays efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool that configures payment infrastructure, the description is too sparse. It lacks any mention of the request parameter's complexity, potential outcomes, or error handling. With no output schema and no annotations, the agent has limited understanding of what to expect or how to proceed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so both parameters are documented in the schema. The description itself adds no parameter-level detail beyond what the schema provides, but it does clarify the overall task scope. With full schema coverage, baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: configuring Stripe/LemonSqueezy products, checkout flows, webhooks, and dunning emails. It's specific about the resources and actions, and while it doesn't explicitly distinguish from siblings, its domain (payment monetization) is unique among the many siblings, making it easy to identify.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, typical scenarios, or exclusions. The agent would have to infer usage from the domain alone, which is insufficient for a complex configuration task.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must convey behavioral traits. It only says 'detect', implying a read-only analysis, but does not disclose whether it modifies files, what output it produces, how it accesses the codebase, or any limitations. This is insufficient for a tool with zero annotation support.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that immediately states the tool's purpose. It is concise, front-loaded, and contains no redundant wording. Every word adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is relatively complex (detects multiple pattern types) yet has no output schema, no annotations, and a minimal description. It does not explain what happens with the 'request' parameter, how the codebase is located, what the return format is, or any constraints. This is inadequate for a tool that needs to guide an agent on invocation and interpretation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so both parameters are already documented. The description adds nothing about the parameters beyond the schema; it does not explain how 'request' should be phrased or which languages are supported beyond the default. Baseline 3 is appropriate given full schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool detects specific code anti-patterns (duplicate code, god classes, magic numbers) and general anti-patterns, so the purpose is well-defined. However, it does not explicitly distinguish this from sibling tools like timps_tech_debt_quantifier or timps_refactoring_agent, though the focus on detection of these specific patterns is fairly unique.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. There is no mention of required context, prerequisites, or scenarios where this tool is preferred. The description is purely a statement of function without any usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden but fails to disclose behavioral details. It does not say whether 'write' means generating text, creating files/directories (e.g., runbooks), mutating a repo, or merely returning content. The extent of agent autonomy and side effects is undefined.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single front-loaded sentence that packs a clear verb, object, and specific deliverable list with zero filler. Every clause earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For an agent with no annotations and no output schema, the description is too thin. It omits key context: what the agent does with its outputs, whether it operates on the repo/workspace, how it gets incident facts, what the interaction model is, and how it differs from timps_incident_responder or timps_disaster_recovery. The vague 'request' param plus the odd 'python' default further obscure actual usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already provides 100% parameter descriptions, establishing baseline 3. The tool description adds minimal value on top of the schema, and the language parameter's relevance to a postmortem is not explained beyond 'Primary programming language (default: python)'.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Write') plus a distinct resource ('postmortems') and enumerates concrete deliverables ('5 Whys, root causes, P0-P2 action items, runbooks'). While it does not name sibling tools, the intent is unmistakable and meaningfully scoped among agent tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. Sibling tools such as timps_incident_responder, timps_incident_response_coordinator, and timps_disaster_recovery clearly overlap with a postmortem workflow, yet the description gives no 'when-to-use' / 'when-not-to-use' direction or mention that a postmortem typically follows an incident.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations, so the description carries the full burden of behavioral disclosure. It says 'Build' but does not explain whether it writes files, runs commands, returns code, requires permissions, or has side effects, leaving important operational behavior undisclosed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, dense sentence with no filler or repetition. It is front-loaded and easily scannable, though slightly too sparse to carry the full selection/warning burden.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has no annotations and no output schema, yet this is a broad, agentic capability. The description names the real-time protocols but omits expected return value, boundary conditions, authentication needs, file-safety behavior, or constraints, making it incomplete for safe invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already covers both parameters with clear descriptions and 100% coverage. The tool description adds no parameter-level insight, but the baseline of 3 is appropriate because the schema does the explanatory work.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies a specific capability: building WebSocket/SSE/Redis Pub-Sub/Kafka server+client real-time systems. It names concrete technologies and a clear action, though it does not differentiate itself from sibling tools beyond that domain.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No usage guidance is provided: it does not say when to prefer this tool over alternatives, what prerequisites exist, or what kind of requests are out of scope. The intended use is only implied by the domain-specific phrase 'real-time systems'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure, but it only lists actions without explaining consequences such as whether files are modified, external services are invoked, or output is returned. The reader cannot tell if this tool audits and reports or actively edits code/sitemaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single compact sentence that immediately conveys the scope. Every phrase adds value and there is no filler or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description leaves out important context: whether all listed tasks run together, what outputs are produced, whether changes are destructive, and what credentials or environment assumptions exist. Given the tool has no annotations and no output schema, this is an incomplete description for reliable agent use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% since both 'request' and 'language' are described in the schema. The description adds no additional parameter nuance, but this is acceptable because the schema already documents the parameters accurately.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description names specific SEO activities ('Run Lighthouse CI, generate schema.org JSON-LD, fix Core Web Vitals, build sitemaps') with clear verbs and resources, making the tool's purpose evident. It is not a tautology, but it does not explicitly distinguish itself from other SEO-adjacent sibling tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no explicit guidance on when to use this tool versus alternatives, nor any mention of when not to use it. The intended use is only implied by the tool name and the task list, not clearly stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the full disclosure burden. It mentions the output ('debt roadmap') but does not state whether the tool is read-only, requires git history or a local repo, has side effects, or what exactly the roadmap contains.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
A single dense sentence with no filler, front-loading the main action and method. Every phrase contributes meaning, and it is easily scannable.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For an analysis tool with no output schema and no annotations, the description is sparse. It does not explain the format of the debt roadmap, prerequisites like git access, whether files are modified, or how to interpret results, leaving significant gaps for the agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% for both parameters, so the baseline is 3. The description does not add parameter-specific details beyond what the schema already provides, but the schema itself sufficiently documents `request` and `language`.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states 'Quantify technical debt via radon complexity + git churn + TODO density; output a debt roadmap,' giving a specific verb, resource, and method. However, it does not differentiate from the near-identical sibling `timps_tech_debt_quantifier`, so it lacks explicit sibling distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No when-to-use context or alternatives are provided. The description implies it is for technical debt analysis, but there is no guidance on selecting it over the similarly named `timps_tech_debt_quantifier`, nor any exclusions, prerequisites, or scenario-based recommendations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must disclose what the tool actually does. It lists output components but does not explain whether this creates files, returns config, modifies an existing project, or requires any particular environment. It also does not mention side effects, permissions, or what a successful invocation returns. Some behavior is conveyed by 'generate', but significant ambiguity remains.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that starts with the action verb and immediately specifies the tool's product. It lists the key facets without filler or redundancy. The density is appropriate and every phrase earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite describing the output scope well, the tool has no output schema, no annotations, and only a bare description of behavior. It does not explain the expected result of the 'request' parameter, what the agent should do if it detects an existing tracing setup, or how the output is delivered. This creates a meaningful gap for a tool that is most likely interactive with project code.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%: both 'request' and 'language' already have descriptions in the schema. The tool description does not add any parameter-specific meaning beyond that. The baseline of 3 for full schema coverage is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Generate') and names a concrete resource: an OpenTelemetry tracing bootstrap. It lists the included components (service name, resource attributes, auto-instrumentation, sampling, pipelines, exporter config), so a reader knows what the tool produces. It is less strong than a 5 because no sibling differentiator is explicitly addressed, though the specificity makes it identifiable.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies this tool should be used when generating an OpenTelemetry tracing bootstrap, but it provides no explicit when-to-use guidance, no exclusions, and no comparisons to alternatives such as monitoring_agent or observability_cost_optimizer. The usage context is only inferred from the tool's name and description, not stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations, so the description carries the full burden. It only mentions 'design' and 'integration code,' which implies a non-destructive, advisory role, but it does not disclose whether it modifies files, requires specific permissions, or has any side effects. The behavioral scope is unclear.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that conveys the core purpose without redundancy. It is appropriately sized for a simple tool, though it could include more detail without becoming verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, no output schema, and only two parameters fully covered by the schema, the description is minimal. It does not explain the scope of design (e.g., does it generate code files?), the expected output format, or any constraints on the request. This is insufficient for an agent to effectively use the tool for complex design tasks.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Both parameters are described in the schema with 100% coverage. The description does not add extra meaning beyond the schema, but the schema already explains 'request' and 'language'. The description implies the request is a design task, but that's already evident from the tool name and description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: designing vector database schemas and integration code for specific technologies (Qdrant, Pinecone, Weaviate, pgvector). It is specific and action-oriented, though it does not explicitly differentiate from sibling tools like timps_db_agent, which could also handle database tasks.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No usage guidance is provided. The description does not indicate when to use this tool versus alternatives (e.g., timps_db_agent for general databases) nor any prerequisites or context. It is left to the agent to infer.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full responsibility for behavioral disclosure. It mentions the tool generates a changelog and supports semver recommendations, but does not clarify whether the operation is read-only, whether it creates or modifies files, what the output format is, or any side effects. This lack of safety/effect information is a significant gap for an unannotated tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence that front-loads the core function and adds a secondary feature. Every word contributes, with no padding or repetition. This is a model of conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
While the tool is simple (two parameters, no output schema), the lack of annotations places a greater burden on the description. It defines what the tool does but omits operational details like return value, whether it modifies any state, or any limitations. This is minimal viable completeness but leaves clarity gaps for an autonomous agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% for both parameters ('request' and 'language'), so the schema already provides adequate meaning. The description adds no extra parameter-level detail, which is acceptable given the high coverage, but it does not elevate beyond the baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Generate a Conventional Commits changelog from commit history, PRs, and issues; supports semver bump recommendation.' It specifies the verb, resource, and sources, making the purpose highly understandable. However, it does not explicitly distinguish this from sibling tools like timps_release_manager, which could also involve changelogs, so it misses the highest bar.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no explicit when-to-use guidance or alternatives. It simply describes the tool's capability without indicating when to prefer it over other tools, whether any prerequisites exist, or when not to use it. This leaves the agent to infer usage context from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'analyse git history' but doesn't disclose that it makes read-only operations, that it may be slow or expensive, or what exactly it produces (e.g., does it write files? Does it require network access?). It doesn't state any side effects or prerequisites like having a git repository locally. This is a significant gap for a tool that runs analysis.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that efficiently communicates the core purpose and outputs. It's not overly verbose and gets to the point. However, it could be structured better with a clearer breakdown of the three outputs, but given the brevity, it's acceptable. It doesn't waste words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
This is a tool that performs complex analysis (AST graph, risk map, tribal knowledge) with no output schema and no annotations. The description provides only a high-level summary without detailing the exact behavior, limitations, or expected output format. With two parameters but no guidance on how to use them, the description is incomplete for an agent to use it effectively. It doesn't mention whether it returns a report, a structured file, or an in-memory result.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, meaning both parameters (request, language) are described in the schema. The description doesn't add any extra meaning beyond what the schema provides; it doesn't explain how 'request' should be phrased or what languages are supported. Baseline 3 is appropriate given high schema coverage, but it could have added examples of effective requests or clarified that language affects parsing.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (analyse git history) and the three outputs (AST import graph, risk map, tribal knowledge document). It distinguishes from siblings like timps_tech_debt_quantifier or timps_dependency_rebel by focusing on git history and producing a combined analysis, though it doesn't explicitly contrast with them. The resource is 'git history' which is specific enough.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies it should be used when you need a comprehensive understanding of codebase dependencies and risks from git history, but it doesn't explicitly state when to use it versus alternatives. For example, it doesn't say 'use this instead of timps_dependency_rebel for deeper context' or 'when you need tribal knowledge'. The request parameter allows plain-English task, but the description doesn't guide on what kind of requests are appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the responsibility for behavioral transparency. It does clearly reveal that the tool estimates costs and produces a prioritised savings list, which suggests a read-only planning behavior. However, it does not disclose output structure, pricing assumptions, potential limitations, or whether any provider APIs or credentials are required.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that front-loads the action ('Estimate...') and immediately states the deliverable ('prioritised list of savings optimisations'). There is no filler or redundant restatement, so it is concise and structurally effective.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, no output schema, and four conceptual parameters, the description is too thin to be fully self-sufficient. It does not specify how the architecture should be expressed, what the returned list contains, whether monthly/annual is a toggle, or how `monthly_requests` influences the estimate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not explain any of the four parameters: `architecture`, `provider`, `regions`, or `monthly_requests`. The word 'architecture' appears only as a generic rhetorical object, with no indication of expected format, optionality, or how it interacts with the other params.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly says the tool 'Estimate[s] monthly/annual cloud cost for an architecture' and 'generate[s] a prioritised list of savings optimisations.' This is a specific verb-resource-outcome combination that clearly distinguishes it from nearby siblings like `timps_cloud_cost_auditor` or `timps_observability_cost_optimizer`.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no explicit guidance on when to use this tool versus alternatives such as `timps_cloud_cost_auditor`, `timps_finops_agent`, or `timps_observability_cost_optimizer`. The intended use case is only implied by the purpose sentence, and there are no exclusions, prerequisites, or alternative references.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries the full behavioral disclosure burden. It does state that the tool runs audit tools and produces four outputs, but it fails to mention whether it modifies the manifest, requires network access, or has any other side effects. For a tool that executes external commands, this is a significant transparency gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The first two sentences are informative and front-loaded, but the third sentence 'Security-conscious devs' favourite agent' is marketing fluff that adds no functional guidance. Overall it is brief, but not every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description lists the produced artifacts inline, which partially compensates for the missing output schema. However, with no annotations and several dependency-related siblings, it would be more complete if it mentioned prerequisites, side effects, or boundary conditions versus timps_dependency_sentinel and timps_dependency_rebel.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is a 3. The description adds no additional parameter-level value beyond implicitly naming python/node/rust ecosystems; it also omits Go despite the schema supporting go.mod. All meaningful parameter detail is already in the input schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly identifies the tool as a dependency vulnerability auditor that runs pip-audit/npm audit/cargo audit and lists four concrete outputs. This is a specific verb+resource pairing, but it doesn't explicitly differentiate from sibling agents like dependency_sentinel or dependency_rebel, so it stops short of a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'after code generation' gives a clear timing context for when to invoke this tool. However, there is no guidance on when not to use it, no alternatives named, and no exclusions for other dependency-related agents in the sibling list.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden of behavioral disclosure. The description does not reveal any behavioral traits such as whether it creates files in the current directory, whether it overwrites existing files, or whether it requires specific project structure. It is a 'create' tool, implying side effects, but no details on side effects, permissions, or state changes are disclosed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that efficiently enumerates the tool's capabilities without fluff. It is front-loaded with the verb and immediately lists the artifacts, making it easy for an agent to scan and understand the core purpose. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has only two parameters, both well-documented in the schema, and no output schema, so the description doesn't need to explain return values. The tool's complexity is moderate (embedded firmware generation), and the description covers the key output types. However, given the lack of guidance on usage context (e.g., when to use this versus other code-generation agents), and the minimal behavioral context, a perfect completeness score is not warranted.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 100% schema description coverage, the schema already explains both parameters adequately (request as plain-English task, language with default python). The description lists the output types (firmware, HAL headers, etc.) which adds some context to what the request parameter should contain, but it does not add substantial meaning beyond what the schema provided. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool creates firmware, HAL headers, CMakeLists, and OTA update scripts for Arduino/ESP32/RPi. The verb 'Create' is specific and the resource types are enumerated. While it doesn't explicitly distinguish from siblings, the specificity of the output artifacts (firmware, HAL headers, etc.) makes it clear this is an embedded development tool, distinct from the many other timps_* agents.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no explicit guidance on when to use this tool versus alternatives. With over 100 sibling tools, many specialized agents (e.g., timps_agent_composer, timps_mcp_server_generator) could overlap, but the description does not mention any conditions, exclusions, or alternative tools. The usage context is only implicit in the tool's specialty.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral aspects, but it only states 'Generate...' without revealing side effects (e.g., file creation, API calls), output format, or required credentials. The tool likely performs mutations, but nothing is disclosed, making it risky for an agent to invoke.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, compact sentence with no redundant text. Every word adds value, listing specific outputs and geographic scope. It is front-loaded and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with two well-described parameters and no output schema, the description covers the basic functionality. However, as a compliance tool it lacks context about expected input format, typical use cases, or any caveats (e.g., data requirements). It is minimally complete but not robust.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Both parameters are already described in the schema (request: Plain-English task/context; language: default python). The description adds no additional meaning beyond that, so the schema carries the burden. Baseline of 3 applies due to 100% schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: generating GST-specific outputs (GSTR-1/3B filings, e-invoice XML, ITC reconciliation reports) and scopes it to India GST. This distinguishes it from sibling compliance agents (e.g., timps_fssai_compliance_agent, timps_dpdp_act_auditor).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description only lists what it generates, without specifying typical scenarios or exclusions. There is no mention of prerequisites or when it would be inappropriate, leaving the agent to infer usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided retical. The description mentions 'suggest a fix' but does not clarify side effects (e.g., is it read-only? does it modify logs?), required access permissions, or output format. For a tool that analyses logs)Skip, the lack of explicit non-destructive disclosure is a notable gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: two short sentences that clearly communicate capabilities. Front-loaded with the primary function, and the second sentence enumerates supported log formats. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no output schema and no annotations, the description leaves out expected return format and any side effects (e.g., whether it writes or only analyzes). It mentions input types (stack traces, JSON logs, syslog, journald) but not how the request parameter is interpreted. Given the simplicity of the tool (2 params) and no output schema, a moderately informative description is acceptable, but some behavioral details (e.g., whether it requires prior setup) are missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% (both 'request' and 'language' are described). The description adds minimal semantic detail beyond the schema—it implies the tool processes logs based on the request, but does not explain how the 'language' parameter influences analysis. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (cluster log errors, identify root cause, suggest fix) and the input scope (production log errors). It doesn't explicitly distinguish from sibling tools like timps_log_interpreter or timps_log_detective, but the purpose is specific and actionable.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus the many sibling log-related tools (e.g., timps_log_detective, timps_log_interpreter). The description does not mention prerequisites, typical scenarios, or trade-offs, leaving the agent to guess when this tool is preferred.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must fully disclose behavioral traits. It states the tool scans and generates code and hooks, but it does not clarify whether it modifies existing files, what side effects it has (e.g., creating files, requiring network access), or what the tool returns. The term 'generate' suggests output but lacks detail on scope or side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that efficiently lists three capabilities. It is front-loaded with the primary action ('Scan for hardcoded secrets') and maintains clarity without excessive wording. Slightly packed, but still readable and concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool that generates migration code and pre-commit hooks, the description lacks critical context: what input the 'request' parameter should contain, what the output format is (no output schema), how it integrates with existing codebases, and any limitations. It does not explain the meaning of 'migration code' in this context or how the tool handles multiple languages. This leaves significant gaps for an agent to invoke it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already provides descriptions for both parameters ('request' and 'language'), with 100% coverage. The tool description adds no additional meaning to these parameters, so the baseline of 3 applies. It does not elaborate on how the request should be phrased or what language values are supported beyond the default.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description specifies three concrete actions: scanning for hardcoded secrets, generating Vault/AWS Secrets Manager migration code, and creating pre-commit hooks. The verb 'scan' and the resource 'hardcoded secrets' are specific, and the generated outputs are clearly stated, making it distinct from other security tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like timps_security_guard or timps_security_remediation. The description implies a use case (migrating secrets to Vault/AWS) but does not mention any exclusions, prerequisites, or decision criteria for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavioral traits. It mentions that it returns direction, confidence, and a hedge recommendation, but omits any side effects, limitations, required inputs, or unusual behavior like the 'language' parameter being a programming language, which seems irrelevant to forecasting. The lack of detail leaves significant ambiguity.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, dense sentence that front-loads the core purpose and outputs. It has zero fluff and every word contributes to understanding the tool's function.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no output schema and vague parameters, the description should provide more detail on how to invoke it effectively. It lists factors and outputs but does not explain what 'request' should contain, how the language parameter affects results, or what format the outputs take. The open-ended request requires more guidance for correct agent usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% for the two parameters, but the descriptions are generic ('Plain-English task' and 'programming language') and do not explain how they relate to this specific tool. The description adds no extra meaning beyond what the schema already states, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it forecasts Indian agri-commodity prices, listing specific inputs (mandi arrivals, MSP, weather, festival demand) and output (direction, confidence, hedge recommendation). This specifics verb+resource and distinguishes it from the generic timps_demand_forecaster sibling.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives context (target users) but provides no explicit guidance on when to use this tool vs alternatives like timps_demand_forecaster. It lacks any when-not-to-use conditions or references to sibling tools, leaving the agent to infer usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. 'Set up' implies mutating actions, but the description says nothing about whether it modifies code, requires API credentials, creates external resources, or is reversible. This is a significant transparency gap for a setup tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no filler or redundant phrasing. Every word contributes to stating the tool's purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool is an agent with no annotations, no output schema, zero required parameters, and a generic 'request' input, the description is too thin. It does not explain behavior, expected outputs, prerequisites, or limitations, leaving the agent without enough context for correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, and the two parameters ('request' and 'language') are already described in the schema. The description's mention of PostHog/Mixpanel/Amplitude and dashboards gives some context for what 'request' might contain, but it adds no parameter-specific semantics beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Set up') and names concrete resources (PostHog/Mixpanel/Amplitude event tracking, funnels, and dashboards), making the tool's purpose clear. It clearly differentiates from the long list of generic sibling agents by being analytics-specific.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not state when to use this tool versus alternatives, nor does it mention any exclusions or prerequisites. Usage is only implied by the domain-specific wording; there is no explicit guidance for an agent deciding between this and a sibling tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden for behavioral disclosure. 'Generate' implies the creation of new files or code, but the description does not mention side effects such as file system modifications, dependency installation, permission requirements, or whether the operation is reversible. This is a significant gap for a tool that likely modifies the environment.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, effectively conveying the core purpose in minimal words. Every word earns its place, and it is front-loaded with the main verb and object. It is an exemplar of concise, structured description.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having no output schema and no annotations, the description does not explain return values, output artifacts (e.g., generated files, command structure), or any expected behavior after generation. Given the potential complexity of generating CLI tools with multiple frameworks, the description lacks the detail needed for the agent to anticipate outcomes or handle edge cases.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Parameter schema coverage is 100%, so basic descriptions for 'request' and 'language' are provided in the schema. The description adds no extra information about parameters, leaving the schema to carry the load. This aligns with a baseline score of 3 when schema coverage is high and description doesn't override it.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Generate') and names specific resource types (Click/Cobra/Commander CLI tools) plus additional features (shell completions, release workflows). It clearly distinguishes the tool's purpose and is unambiguous even without sibling comparison, as no sibling tool seems to cover CLI generation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives no guidance on when to use this tool versus other timps_* agents. It only states what it does, without any contextual triggers, prerequisites, or explicit alternative recommendations. The absence of any 'when to use' or 'when not to use' information leaves the agent without decision support.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure, and it only states what is designed (plans, runbooks, scripts) without clarifying key behavioral traits: whether it only generates documents, whether it can execute or modify runbooks, what cloud providers are supported, or whether tool use is read-only. The readOnly/destructive safety profile is entirely undisclosed, which is a significant gap for a tool whose purpose implies potential operational impact.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
A single, tightly-written 16-word sentence that front-loads the essential purpose with zero filler. Every phrase ('RTO/RPO-aware', 'failover runbooks', 'DR test scripts', 'for cloud systems') earns its place by adding specificity. The structure is ideal for agent comprehension.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool whose purpose is generative design/planning in a disaster-recovery domain, the description lacks critical context: it does not mention the output format, the expected turnaround for runbooks or test scripts, whether the 'language' parameter affects script output (Python vs. other languages), or any guardrails for RTO/RPO specification. Despite its simple 2-parameter schema, the domain warrants richer context than 'design plans' to be considered a complete contract for the agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the description is not obligated to explain each parameter in depth. The description's mention of 'RTO/RPO-aware' provides context for what the 'request' parameter should contain, but it doesn't add meaningfully beyond the schema's 'Plain-English task or context for the agent.' This is a proper use of the baseline 3 for full coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Design') paired with a well-scoped resource: 'RTO/RPO-aware DR plans, failover runbooks, and DR test scripts for cloud systems.' It names three distinct deliverable types, which strongly differentiates it from close siblings like timps_backup_sentinel (backup monitoring) and timps_incident_response_coordinator (incident handling). The scope qualifier 'for cloud systems' further tightens the purpose definition.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description offers no explicit 'use when' guidance, no exclusions, and no alternative tool references. While the purpose is apparent from the name and description, the agent is given no help distinguishing when to prefer this over the many seemingly related tools (e.g., timps_incident_responder, timps_backup_sentinel) for overlapping scenarios. There is no statement of exclusions or alternatives as the rubric requires.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It mentions the tool returns exact terminal commands to fix issues, which is useful, but it doesn't disclose whether it modifies anything, what permissions it might need, or what happens if it can't find an issue. It is not contradictory but lacks depth.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, efficient and front-loaded with the purpose. No fluff, every sentence adds value. A 5 is reserved for perfectly distilled, and this is very close but could have added a usage hint without much length.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (one optional parameter, no output schema), the description provides adequate overview but lacks details about the return format (list of issues vs. single fix), whether it runs diagnostics or just static checks, and edge cases. It's sufficient for basic use but not rich.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% (only one parameter with detailed description), so the baseline is 3. The description doesn't add any extra meaning beyond what the schema provides; it merely mentions the categories checked, but the focus parameter is already fully documented in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool diagnoses broken development environments and lists the specific components it checks (Python, Node.js, Docker, Git, PATH, shell config). It is distinguished from siblings like timps_full_checkup (which may be broader) but doesn't explicitly differentiate, so it's not a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use (when dev environment is broken) and names alternatives indirectly through sibling list, but it doesn't explicitly state when not to use or how it compares to timps_full_checkup or timps_system_optimizer. No explicit exclusions are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose side effects but only says 'generate' without detailing whether files are overwritten, if a git repo is required, or what other impacts occur (e.g., installing dependencies, modifying configuration). This lack of transparency is a gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that front-loads the action (generate) and lists the key outputs. It is efficient and not overly verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description lacks information about required context (e.g., existing repository), potential side effects (e.g., overwriting files), dependencies, or expected output. With no annotations and no output schema, this is a meaningful gap for a tool that generates configuration files.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already provides 100% coverage with descriptions for 'request' and 'language' (default python). The tool description does not add any extra meaning to these parameters, but since the schema is adequate, this is acceptable; however, no added insight is provided.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb (generate) and the specific components (pre-commit hooks, commitlint, lefthook, release-please config, PR template, CODEOWNERS), making the tool's purpose unambiguous and distinct from other automation tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives, nor any prerequisites or exclusions. The description only states what it does, not when it should be invoked among the many sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the behavioral burden. It only states the creation action, but does not disclose side effects, output format, file creation, permissions, or scope.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, direct sentence with concrete nouns and no filler. Every word contributes to identifying the tool's purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema and no annotations, the tool should explain expected return values or artifacts, but it does not. The description is too thin for an agent to know what will happen after invoking it.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Both parameters are fully described in the input schema, so the description adds no meaningful parameter semantics beyond what schema already provides. The baseline of 3 applies because schema coverage is 100%.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description names specific deliverables: evaluation harnesses, adversarial test inputs, and RAGAS config for LLM models. This clearly distinguishes it from sibling tools like timps_rag_evaluator or timps_model_perf_monitor.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives no guidance on when to use this tool versus alternatives, and it names no exclusions or sibling fallbacks. The intended context is only implied by the action verb.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full responsibility for disclosing behavioral traits. It does not mention whether the tool modifies anything, requires permissions, or has side effects. It only says it 'recommends', leaving transparency lacking.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence that gets straight to the point. It includes all essential information without any fluff or unnecessary details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's specific purpose and simple schema, the description is quite complete. It mentions the input (observability bill) and the output (recommendations with projected savings), covering the main aspects adequately.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% for both parameters, and the descriptions in the schema are generic. The tool description adds no additional context or constraints beyond the schema, so a baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: analysing observability bills and recommending cost-saving actions with projected savings. It distinguishes itself from sibling tools by focusing on observability cost optimization.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It does not mention any specific scenarios or exclusions, leaving the usage context ambiguous.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the behavioral disclosure burden. It does not explain whether the tool executes code, accesses external resources, or modifies files. The phrase 'generate Qiskit circuits' could imply code creation, but side effects and requirements are unspecified.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that clearly lists three deliverables. It is concise and front-loaded, with no unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Considering the complexity of the domain (quantum computing, NIST PQC migration) and the lack of annotations and output schema, the description leaves significant gaps. It does not specify the expected input format for the request, the nature of the output, or any limitations. The tool appears to be complex, yet the description provides minimal operational context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema fully describes both parameters (request and language) with clear descriptions. The tool description adds no additional meaning about how these parameters influence behavior, so the baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states three specific actions (identify, generate, produce) with concrete resources (quantum-vulnerable algorithms, Qiskit circuits, NIST PQC migration plans), making it unmistakable what the tool does. It is specific and distinct from generic security tools in the sibling list.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool versus alternatives. The description does not mention any prerequisites, exclusions, or contexts. Given the many sibling tools, it does not help the agent decide when to invoke this over timps_security_guard or timps_threat_intel_analyst.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Since no annotations are present, the description carries the full burden of behavioral disclosure. It does not mention whether the tool outputs code, writes files, requires network access or API keys, or any side effects. It only hints at the content of generated scrapers but not the tool's own behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that starts with the verb 'Generate' and contains no unnecessary words. It is maximally concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (code generation) and lack of output schema and annotations, the description is incomplete. It doesn't explain the expected output format, how the request should be structured, or any error handling/limitations. An agent would struggle to use it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions for both request and language. The description adds no additional parameter semantics beyond what the schema already provides, so the baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool generates scrapers using specific libraries (Playwright/Scrapy/httpx) with anti-bot config and data extraction logic. This is a specific verb+resource combination that distinguishes it from sibling tools like timps_browser_automation or timps_web_search.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives, no mention of prerequisites, exclusions, or context. It's a bare declarative statement with no usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must disclose behavioral traits. It mentions producing a Markdown file but does not clarify whether the file is saved, returned as text, or if any side effects occur. There is no mention of permissions, input/output handling details, or potential destructive actions, leaving the behavior ambiguous.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, succinct sentence that directly states the tool's purpose and key features. It avoids unnecessary details and is well-structured for immediate understanding.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the core function (turning a decision into an ADR) and its main components, but it lacks details about the output mechanism (e.g., does it save a file or return text?) and any potential edge cases. This leaves some ambiguity for a user assessing the tool's full behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already provides descriptions for both parameters ('request' and 'language') with 100% coverage. The tool description does not add any extra meaning to these parameters beyond what is in the schema, so it meets the baseline but provides no additional clarity.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: converting a technical decision into a Michael Nygard-style Architecture Decision Record, listing the included sections (context, options matrix, decision, consequences) and the output format (rendered Markdown file). This is specific and distinguishes it from sibling tools that likely have different purposes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not provide any guidance on when to use this tool versus alternatives. There is no mention of use cases, prerequisites, or comparisons to related tools. Users are left to infer when an ADR is needed, but no explicit instruction is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It adds some useful context by listing tracked marketplaces, but it does not disclose whether the tool performs live web fetches, relies on cached knowledge, mutates anything, requires authentication, or what kind of output it produces. This is a significant transparency gap for an unannotated tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences and front-loads the core purpose. The second sentence adds concrete scope by enumerating tracked marketplaces, earning its place. There is no filler, redundancy, or unnecessary detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with two optional parameters, the description covers the domain and sources adequately. However, with no output schema and no annotations, it should explain what the agent can expect as a result (e.g., a curated list, comparisons, or ranked recommendations) and clarify when it should be preferred over sibling research tools. These gaps prevent a higher score.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3 even though the description itself adds no parameter-level meaning. The 'request' and 'language' fields are self-explanatory from the schema, but the description does not clarify how 'language' relates to marketplace curation or how detailed the 'request' should be.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a specific verb ('Curate') and a clear resource ('AI agent / MCP / LLM-tool marketplaces'), then clarifies the intended outcome ('recommend picks by use-case'). Naming tracked sources like pulse.mcp.run and glama.ai makes the tool's scope concrete and distinguishes it from generic research or agent-listing siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not say when to use this tool versus alternatives such as timps_web_search, timps_research_agent, or timps_list_agents. It provides no exclusions, prerequisites, or explicit 'use this when' guidance, leaving the agent to infer applicability solely from the tool name and purpose.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full responsibility for transparency. It mentions outputs (scores, forecast, segments, recommendations) but does not disclose how inputs are used, data requirements, side effects, or return format. There's no mention of whether the tool is read-only or what processing occurs.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, compact sentence that lists the main actions clearly. It is front-loaded with the primary task and avoids fluff. However, it could be split into bullet points for readability, but it remains sufficiently concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has no output schema, so the description must explain what is returned. It lists four outputs (scores, survival-curve, segments, save plays) but does not specify format, how results are delivered (report, JSON, etc.), or what data inputs are expected. Given the complexity and lack of annotations, this is inadequate for an agent to confidently invoke the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% as both parameters have descriptions, but they are generic ('Plain-English task or context' and 'Primary programming language'). The tool description does not add specific meaning to the 'request' parameter, such as expected structure or examples. Baseline is 3 for high coverage, and no added value beyond baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: score churn risk, build survival curves, segment at-risk cohorts, and recommend save plays. This is a specific verb+resource (accounts/users) that distinguishes it from sibling tools, which focus on other domains like testing, forecasting, or compliance.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for churn analysis (through the name and explicit actions) but provides no explicit when-to-use or when-not-to-use guidance, nor does it name alternatives. It relies on the agent's inference from the tool name and siblings, which is minimal guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It states the tool 'monitors' and 'returns a brief,' implying read-only behavior. However, it doesn't disclose whether this makes network calls, has rate limits, requires API keys or authentication, or if it performs live tracking versus static analysis. The output is described as a 'brief' but not its format or size. Some behavior is disclosed but not enough for a monitoring tool that likely performs external fetching.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loads the main action ('monitor competitors for...'), and uses a single output statement. It's concise and well-structured. It could add a tiny bit more detail without bloat.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has a moderate complexity (array input, optional enum), and the description covers the what and the return. But absence of annotations and no mention of data sources, timeframes, or specific deliverables beyond 'brief' leaves gaps. For a tool that gathers external competitor data, important context (live fetch vs. stored data, scope, refresh) is missing. Given zero annotation coverage, the description should compensate more.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% (both parameters described). The description adds domain context by listing 'pricing changes, new features, job postings, and public sentiment' which correspond to the focus_areas enum values (pricing, features, job postings?, sentiment?), bridging schema to intent. However, it doesn't explain the competitors parameter beyond 'names' — basic semantics are captured in schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool monitors competitors across four specific dimensions (pricing, features, job postings, sentiment) and returns a competitive intelligence brief. The verb 'monitor' plus the resource 'competitors' is specific, and the output is described. However, it doesn't explicitly distinguish itself from other intelligence-gathering siblings like timps_deep_research_agent or timps_trend_monitor, though its narrower focus is implied.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no explicit guidance on when to use this tool versus alternatives. It doesn't say 'use this when you need competitor intelligence' or mention scenarios where it's not appropriate. Among a large set of sibling tools, this lacks any differentiation cues.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of disclosing behavior. It mentions that the tool 'designs' and references targeting rules and rollout plans, but it does not explain side effects, whether files are modified, what outputs are produced, or any prerequisites. This is a significant gap for a tool with no structured annotation safety profile.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single front-loaded sentence with no filler. Every phrase adds meaningful specificity: the action, the platforms, and the expected deliverables.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has no annotations and no output schema, so the description must carry more weight. It conveys the core domain and expected output artifacts, but it lacks any example request, explanation of what a completed design looks like, or process details. This is adequate for a free-form agent tool but not comprehensive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% for the two parameters ('request' and 'language'), so the baseline is 3. The description does not add parameter-level detail, but it does provide domain context that clarifies what kind of free-form 'request' would be appropriate, which is marginal value above the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states a specific action ('Design feature flags') with distinct platforms (LaunchDarkly/Flagsmith/GrowthBook) and deliverables (targeting rules and rollout plans). This is specific enough to distinguish it from the many sibling agent tools, none of which are named for feature-flag design.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given for when to use this tool versus alternatives or which situations it is best suited for. The description implies the usage context through its purpose statement, but it never explicitly states when to invoke it or when not to.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It only says 'Write,' implying creation, but does not mention side effects, required permissions, output format, or the agent's interactive nature. This is a significant gap for an agent that likely performs complex, multi-step operations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, action-oriented sentence that front-loads the core purpose. It is concise and avoids fluff, though it could be slightly more structured to list deliverables. Overall, it efficiently conveys the main function.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (agent handling multiple GraphQL components), the description is incomplete. It lacks guidance on what constitutes a good 'request,' expected interactions, or output behavior. With no output schema or annotations, the description alone is insufficient for an agent to use this tool effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% since both 'request' and 'language' have descriptions in the schema. The tool description does not add any additional meaning beyond what the schema provides, so a baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Write' and specifies the resource as 'GraphQL SDL schemas, resolvers, DataLoader, subscriptions, and federation config.' This is specific and directly distinguishes it from sibling tools like generic web search or SQL optimizer, making its purpose unmistakable.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
While the description implies usage for GraphQL development tasks, it does not explicitly state when to use this tool versus alternatives, nor does it provide exclusions or alternative recommendations. Given the many sibling tools, more guidance would be helpful, but the purpose alone implies the context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full transparency burden. It suggests the tool generates a 'play-by-play response' but does not disclose whether that response is a plan, or whether the tool actually executes actions like sending communications or initiating containment. This ambiguity leaves side effects and required permissions undefined.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence with front-loaded purpose and specific deliverables. Every clause adds meaning: incident types, the planning action, and the components of the response.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
At a high level, the description captures the tool's scope and outputs, but it lacks material detail about the generated playbook structure, prerequisites, limits, or any behavior beyond producing the plan. The two free-form parameters and lack of output schema mean more behavioral specifics are needed for an agent to confidently use and trust the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, so baseline 3 applies. The description does not add additional meaning to the 'request' or 'language' parameters beyond what the schema already states—particularly, it does not explain how the plain-English request is interpreted or why a programming language is relevant to incident coordination.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: converting an active incident (SIEM alert, customer report, CVE) into a structured response with comms, containment, and a postmortem stub. It uses a specific verb and describes the resource/deliverables, though it doesn't explicitly distinguish itself from sibling tools like timps_incident_responder.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear trigger context ('active incident' with specific examples), implying when this tool should be used. However, it does not mention alternatives or explicitly state when not to use it, which is important given the many similar security/incident-related sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits. It only states that it 'generates' artifacts, but does not mention any side effects, prerequisites, or environmental changes (e.g., file creation, external tool dependencies, network access). The agent has no insight into what happens when invoking the tool beyond the abstract output.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no redundant content. It conveys the core functionality and key deliverables efficiently, earning a high score for conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is complex (supports multiple load testing frameworks and creates dashboards), but the description is minimal. It does not explain output format, file structure, or how the agent should interpret results. Given the presence of a request param for context, the description might be minimally viable, but it lacks details that could be expected for such a specialized tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, with both parameters having descriptions ('Plain-English task or context' and 'Primary programming language'). The description adds no extra meaning about how these parameters influence the output. Baseline 3 is appropriate because the schema already carries the parameter semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states the tool generates load test scripts for specific tools (k6/Artillery/Locust) along with ramp-up plans and Grafana dashboards. This uses a specific verb (generate) and identifies the resource and deliverables, clearly distinguishing it from sibling tools like timps_api_perf_profiler or timps_test_intelligence.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool versus alternatives. Given the large sibling list with many performance/testing tools, the absence of context or exclusionary criteria leaves the agent without decision support. The description simply states what it does, not when it's appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description is the only source. It indicates the tool analyzes overlap but does not specify output format, side effects, or whether it modifies the repo. Behavioral traits are only partially disclosed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that is well-structured and front-loaded with the core purpose. No unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description omits critical details such as input requirements, output format, or any limitations. Without an output schema, it is incomplete for a tool of this complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has no descriptions (0% coverage), and the description does not elaborate on the parameters beyond the obvious names (branch_a, branch_b, repo_path). It fails to clarify their roles or constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: predicting merge conflicts between two branches before merging, with file-level and line-level analysis. It is specific and distinguishes from the many sibling tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'before merging' gives a context for when to use it, but it does not explicitly mention alternatives or when not to use this tool. No comparison to other tools is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full responsibility for behavioral disclosure. It mentions scaffolding and included features, but does not detail side effects, permissions, or the exact nature of the operation. The agent cannot infer whether this mutates the filesystem, requires network access, or what the end state will be.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with no wasted words. It front-loads the action and target. However, it lacks any structured breakdown, but for the brevity, it is appropriately concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the absence of annotations, output schema, and detailed parameter context, the description is too sparse. It fails to explain how the request parameter should be used, what the output or deliverable will be, or any prerequisites. For a tool with 2 parameters and no other structured information, this is insufficient for an agent to effectively use it.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%: both parameters have descriptions in the schema. The tool description adds no additional parameter context beyond what is already provided. Per the rubric, with high coverage, baseline is 3, and the description does not compensate further.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states a specific action (scaffold) and resource (React Native/Flutter/Expo apps) with notable features (push notifications, deep links). This distinctly identifies the tool's purpose among the large set of siblings, which are mostly unrelated (web scraping, data pipelines, etc.).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use for scaffolding mobile apps but does not provide explicit when-to-use or when-not-to-use guidance. It doesn't contrast with any alternative tools or mention scenarios where this would be inappropriate. The context is clear but not exclusive or instructive.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavior disclosure. It does not state whether emails are actually sent, whether target lists are required, how payloads are tracked, or what safety mechanisms exist beyond the ethical note. This is especially concerning for a security-sensitive tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence plus an ethical clause, front-loading the core purpose and key deliverables. It avoids fluff, though a slightly more structured breakdown could improve readability.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is security-sensitive and has no output schema, so the description should explain return values, required contextual inputs, and safety boundaries in more depth. It lists deliverables but omits whether anything is sent, how results are presented, and what happens after generation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% for both 'request' and 'language', so the schema already documents the parameters clearly. The tool description adds no additional parameter-level meaning, so the baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'Generate' and clearly identifies the resource as an 'organisation-tailored phishing simulation' with concrete deliverables (emails, landing pages, payload tracking, click-through metrics). It is distinct from sibling security tools like timps_red_team_agent but does not explicitly name alternatives, so it misses the top score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'Strictly for authorised training use' provides an explicit boundary for when the tool should not be used. The opening 'Generate a realistic phishing simulation' implies the primary use case. However, it does not mention alternative tools or further when-to-use guidance, keeping it from a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses that the tool reads a failing CI/CD run and produces a diff, implying it both reads configuration and outputs changes ret. However, it does not specify whether it modifies files directly, requires credentials, or has side effects. Since no annotations exist to supply this information, the description carries the burden and only partially meets it.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, front-loaded with the core action ('Read a failing CI/CD run') and then lists specific fix categories. It is concise but slightly run-on, with a colon-led list that could be clearer. No unnecessary filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and no annotations, the description must convey expected returns, side effects, and usage constraints. It mentions producing a diff and lists fix categories but omits how the diff is delivered, whether it's applied automatically or just proposed, and any requirements (e.g., repo access). With 0 required parameters and two freeform fields, the description is incomplete for safe agent use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Both parameters are fully described in the schema (request: plain-English task; language: primary programming language), so the baseline is 3. The description does not add semantics beyond the schema; it only hints that the tool operates on CI/CD, which is already implied. There is no additional guidance on parameter values or interactions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('Read'), resource ('CI/CD run'), and outcome ('produce a minimal diff to make it green'). It also lists concrete categories of fixes (cache bumps, image bumps, secret injection, retries), which distinguishes it from sibling tools like timps_full_checkup or timps_incident_responder that likely have broader or different scopes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage on a failing CI/CD pipeline but provides no explicit guidance on when to choose this tool over alternatives, nor does it mention any exclusions or requirements. Sibling tools like timps_full_checkup and timps_incident_responder suggest overlapping contexts, yet no differentiation is offered.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It only lists generated artifacts and does not reveal whether files are written, how the generation is performed, whether external systems are accessed, or any side effects or limitations. This is a significant gap for an agent that likely performs complex generation tasks.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence, front-loaded with the primary verb and listing specific outputs. Every word adds value and there is no filler or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool covers multiple complex artifacts (ROS2 nodes, URDF, motion planning config, safety analysis) but has no output schema and no annotations. The description minimally lists expected outputs but omits how the request should be structured, what the result format will be, or any execution constraints, leaving notable gaps for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with both parameters ('request' and 'language') already described. The description adds no additional parameter meaning, so the baseline score of 3 is appropriate; it neither enriches nor contradicts the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb ('Generate') with concrete resources ('ROS2 nodes, URDF descriptions, motion planning config, and ISO 10218-1 safety analysis'), making the tool's function unmistakable. It also clearly distinguishes itself from sibling tools, as none of the listed siblings target robotics.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool, what prerequisites exist, or how it compares to alternatives. The description simply lists outputs with no contextual usage direction, leaving the agent to infer applicability from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description does not disclose side effects, such as whether it creates GitHub issues or modifies existing data. Without annotations, there is no indication of permissions or state changes, leaving behavioral expectations unclear.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is brief and front-loaded, immediately stating the core action. It avoids unnecessary words and is well-structured for quick comprehension.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with only two simple parameters, the description provides adequate context for its main purpose. However, it omits details about return values, potential side effects, or examples, which would enhance completeness for a user deciding to invoke it.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema covers both parameters ('request' and 'language') with descriptions, achieving 100% coverage. The tool description does not add extra semantic detail beyond the schema, so the baseline score of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's primary function: decomposing epics into sprint tickets with estimates and GitHub Issues payload. It uses a specific verb ('decompose') and identifies the resource and output, making it distinct from sibling tools like sprint_reporter.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not provide any guidance on when to use this tool versus alternatives, nor does it mention prerequisites or conditions for use. It lacks explicit context such as 'use when you have epics to break down' or comparisons to related agents.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full responsibility for disclosing behavioral traits. Although it says 'Refresh' and 'write', which suggest file modification, it does not state whether existing files get overwritten, where outputs are written, whether it only generates text in memory, or that it requires any authentication/scope. This leaves significant behavioral uncertainty for a doc-generation and possible file-mutation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, compact sentence that enumerates all major deliverables without editorializing or redundancy. Every word carries meaning ('refresh', 'write', 'generate', 'from the codebase') and the structure is front-loaded with the primary action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's broad scope and lack of output schema, the description lists the expected outputs but misses some context an agent would need: no mention of where outputs land, whether the action is irreversible, what aspects of the codebase are explored, or how the 'request' parameter shapes content. It is adequate as an overview, but incomplete for fully autonomous invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and both parameters ('request' and 'language') have descriptive text, so the schema already provides the core meanings. The tool description does not add any extra parameter semantics, such as example requests, the effect of language, or relation between request and the list of outputs, but because the schema is complete, a baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function with specific actions and outputs: refresh a README, write ADRs, generate a Getting Started guide, FAQ, and reference page from the codebase. It is much more specific than a tautology, but it does not explicitly distinguish itself from closely related sibling tools like timps_adr_writer or timps_changelog_generator, which could cause selection ambiguity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies this is a broad technical-writing assistant for producing multiple documentation artifacts from a codebase. However, there is no explicit guidance on when to use this tool versus a more targeted sibling like timps_adr_writer or timps_docstring_generator, and it does not mention any exclusions or alternative workflows.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must explain behavior, but it only lists actions without detailing side effects, authorization needs, or return values. The phrase 'Implement' suggests code or workflow generation, but no specifics on execution, data access, or outcomes are disclosed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, focused sentence that front-loads the core responsibilities. Every word contributes to conveying the tool's domain and actions, making it highly concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite the domain's complexity (ABDM, FHIR, consent workflows), the description provides no detail on expected inputs beyond 'request', no output schema, and no behavior specifications. An agent could not fully understand the tool's capabilities, limitations, or integration requirements from this description alone.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already provides clear descriptions for both parameters (request as plain-English task, language with default). The tool description adds no additional semantic meaning beyond what the schema covers, earning the baseline score for 100% schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: implementing ABHA enrollment, HIP/HIU flows, FHIR R4 bundles, and consent workflows within India's ABDM framework. The verb 'Implement' and specific domain terms make it distinguishable from broader or unrelated sibling agents.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for ABDM-related health data tasks but provides no explicit 'when to use' or 'when not to use' guidance. It does not mention alternatives or exclusions, leaving the agent to infer relevance from the domain name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of disclosing behavior. It implies creating a file but does not state side effects (e.g., file location, overwrite behavior), required permissions, or what the result/response looks like. This is a significant gap for a generation/mutation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that communicates the core purpose with no wasted words. It is appropriately sized for a tool whose parameters are already well-documented in the schema.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
This is a code/file-generation tool with no output schema and no annotations. The description does not explain return values, file output behavior, error conditions, or when it should be chosen over related generation tools. For a tool with potential side effects, this is incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% for both parameters ('request' and 'language'), so the schema already explains them. The description adds minimal semantic value by linking 'natural-language description' to the request parameter and 'Python' to the default language, but does not need to compensate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Generate') and names the resource ('new fully-functional Python agent file') and source ('natural-language description'). It clearly differentiates from sibling tools which list, dispatch, or run agents, not create new agent files.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The intended use is implied by the description ('generate a new agent file'), but there are no explicit when-to-use instructions, exclusions, or comparisons to alternatives such as timps_mcp_server_generator or timps_list_agents. It is intuitive but not explicitly guided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. The description lists analysis outputs but does not disclose side effects (e.g., whether it only reads logs or mutates anything), required permissions, performance impact of running the profiler, or limitations (e.g., truncation, sampling). As a profiling tool, it likely performs read-only analysis, but nothing confirms this, leaving a substantial gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence front-loading the core action ('Profile an API') and then listing expected outputs. It is efficient and avoids fluff, but could be slightly better structured by separating the core purpose from the output list for greater readability.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has moderate complexity (2 simple parameters, no output schema, no annotations). The description covers the main purpose but lacks details on return format, data sources specifics, or how to phrase requests. Given the schema is simple and no output schema exists, the description is minimally adequate but misses guidance on what 'access logs / traces' means or what 'concrete optimisations' entails.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, with two simple parameters: 'request' (plain-language task) and 'language' (primary programming language, default python). The description adds context on the overall task (profiling) but does not detail how 'request' should be phrased or how 'language' affects profiling (e.g., impacts parsing of logs). With full schema coverage, baseline is 3; description does not add meaning beyond the schema, so 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific action ('Profile an API') with a clear resource ('access logs / traces') and enumerates expected outputs (p50/p95/p99 by endpoint, slow query, N+1 detection, optimisations). This is specific and distinct from siblings like timps_sql_optimizer or timps_tech_debt_quantifier, which target different concerns.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for performance profiling of APIs using logs or traces, which suggests a suitable context. However, it does not explicitly state when to use this tool versus alternatives like timps_sql_optimizer or timps_log_interpreter, nor does it give exclusions or prerequisites (e.g., need for access logs). The implied usage is clear enough for a basic scenario, but lacks explicit guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided. The description does not mention side effects, permissions, or limitations. It does hint at the output structure (storyboard, B-roll, on-screen copy), which provides some transparency, but there is no mention of error handling or constraints.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is one concise sentence that lists the key outputs. It is well-structured, directly to the point, and avoids unnecessary verbosity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description gives a good overview of what the tool produces, but it does not specify the format of the output (e.g., plain text, structured JSON) or how the language parameter fits in. The mismatch with the language parameter leaves a gap in understanding, making the overall context incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema descriptions for 'request' and 'language' are present. However, the 'language' parameter is described as 'Primary programming language (default: python)', which seems irrelevant for a demo video script writer and is not mentioned in the tool description. This creates confusion. The 'request' parameter is adequately described, but the overall parameter semantics are undermined by the mismatched 'language' field.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: writing a 60-90s product demo video script with specific components (hook, problem, demo beats, payoff, CTA) and additional outputs (storyboard, B-roll, on-screen copy). It is specific and distinguishable from sibling tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not provide any guidance on when to use this tool versus alternatives. It lacks context such as target user, scenarios, or prerequisites. No conditions or exclusions are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It only says 'Implement...flows' without disclosing behavior such as whether it makes network calls, stores credentials, returns code, or handles OAuth tokens. Given the sensitive nature of eKYC and Aadhaar OTP, this is a significant transparency gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
A single sentence that wastes no words. It front-loads the action verb and enumerates the flows concisely. Perfectly scoped for an agent description.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For the complexity of OAuth and eKYC integration, the description is too terse. It doesn't mention prerequisites, success/error behavior, or whether the implementation is code generation or direct API invocation. The lack of output schema and annotations heightens the need for a richer description, which is absent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so both parameters (request and language) are already documented. The description adds domain context that helps interpret the 'request' parameter (e.g., tasks related to DigiLocker/eKYC) but no extra parameter-level details are necessary. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool's function: 'Implement DigiLocker OAuth, document pull, Aadhaar OTP, PAN verify, and eKYC flows (India).' It uses specific verbs and lists specific resources, which distinguishes it from sibling tools focused on other domains (e.g., GST, UPI). The scope is unmistakable.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage is implied by the name and description—this is the tool for DigiLocker-related implementation tasks. However, no explicit guidance is given on when to choose this over similar India-specific agents (e.g., timps_gst_compliance, timps_upi_agent) or when not to use it. A clear when-to/when-not-to would elevate this.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations and no output schema, the description has the full burden of explaining what happens when this tool runs. It only states that it 'composes' a docker-compose file, but does not say whether the tool writes files, returns YAML content, modifies an existing project, or whether there are side effects or permissions/context requirements.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
One sentence contains the core action, the target artifact, the quality attribute ('production-grade'), the scope ('multi-service', 'project'), and a useful list of covered compose aspects. There is no filler, repetition, or unnecessary wording.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For what could be a file-producing or file recommending tool, there is no mention of return format, delivery mechanism, project context assumptions, or whether an existing project is required. There are no annotations and no output schema, so the description alone is not enough to fully inform an agent about expected behavior and scope of results.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description doesn't add detail about the two parameters, but the input schema already provides clear descriptions: request for plain-English task/context and language for the primary programming language. Since schema coverage is 100%, the schema carries the load, and the baseline score of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly specifies a concrete action ('Compose a production-grade multi-service docker-compose') and resource ('docker-compose (or compose.yaml)'), with an enumerated scope that includes the relevant concerns: env, healthchecks, volumes, networks, profiles. This is differentiated from sibling tools by explicitly targeting docker-compose rather than Kubernetes, Terraform, or container scanning.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies that the tool should be used when a project needs a production-grade multi-service compose file, and it gives a short list of what the generated file should contain. However, it does not explicitly describe when not to use it, or compare it against alternatives such as kubernetes_navigator or container_image_scanner. The usage intent is clear but only implied.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the full burden of behavioral disclosure. It only says 'Generate' without stating whether the tool returns code, writes files, executes training, or merely produces scripts. Side effects, authorization needs, and environment interactions are not disclosed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no filler. Every phrase contributes useful detail: the frameworks, the completeness of the pipeline, and the push-to-hub deliverable.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a complex code-generation agent with no output schema and no annotations, this one-line description is incomplete. It lacks details about return values, whether files are created, what a 'complete pipeline' includes, and what inputs or prerequisites are needed beyond a plain-English request.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% for the two parameters, and the `request` and `language` descriptions are already self-explanatory. The tool description adds no parameter-specific meaning, so the baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with the action verb 'Generate' and names a concrete output: complete LoRA/MLX/Axolotl/Unsloth fine-tuning pipelines plus push-to-hub scripts. This clearly distinguishes it from sibling tools like dataset_agent or model_evaluator. The scope is specific and unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage is implied by the description: it is presumably the right tool when a user wants fine-tuning pipelines in those frameworks. However, there is no explicit when/when-not guidance, no mention of alternatives, and no prerequisites or exclusions, leaving an agent to infer the invocation context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of disclosing side effects and behavior. It states the tool 'finds' and 'returns' results, which suggests read-only analysis, but it never explicitly says whether it writes to the repo, makes external calls, or only parses the supplied CI history. This lack of explicit safety/behavioral disclosure is a meaningful gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is one sentence, concise, front-loaded with the main action, and has no redundant filler. It efficiently communicates the purpose and the nature of the returned result.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the low complexity of the tool, the description adequately covers what the agent needs to know: the purpose, input domain, and output shape. It lacks explicit behavioral/safety details, but those are already accounted for in behavioral transparency; for a simple analyze-and-return tool, the description is complete enough.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema fully describes both parameters with 100% described coverage, so the baseline is 3. The description reinforces that CI history is the core input, but it adds no new parameter-level semantics beyond what the schema already states. More guidance on acceptable `ci_history` format or how `repo_path` would be used would improve this dimension.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific action ('Find non-deterministic tests') and identifies the source data ('CI run history') and output ('ranked list of flaky tests, suspected causes, and fix suggestions'). It is clear, but it does not distinguish itself from the closely named sibling timps_flaky_test_detective.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use the tool: when the agent has CI run history and wants flaky-test analysis. However, it provides no explicit guidance about alternatives or when not to use it, which matters because the sibling list includes `timps_flaky_test_detective`, `timps_test_intelligence`, and similar analysis tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It describes the scan and return of a score/action list but does not disclose whether any system modifications occur, whether it's read-only, potential side effects, or the exact nature of the 'prioritised action list' (e.g., are actions executed or just suggested?). This lack of detail on behavior beyond the surface is a notable gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence that front-loads the action and clearly states the return value. No unnecessary words; every part contributes to understanding the tool's purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (orchestrating 6 agents), the description is brief. It lists the agents involved and the output (health score and action list), but does not explain what each agent assesses, how the score is computed, or the format/type of actions. With no output schema and no annotations, the description should provide more detail about the return value and potential side effects, but it remains high-level and underspecified.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% (the single optional 'focus' parameter is described). The tool description adds no additional meaning beyond the schema; it merely repeats the hint to customise the checkup. Baseline is 3 due to full coverage, and the description adds no extra nuance.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool runs a comprehensive computer health scan across a specific list of 6 agents and returns a combined health score and prioritized action list. It uses a specific verb ('Run') and resource ('computer health scan'), and it distinctly differentiates itself from the sibling individual agent tools by indicating it's an aggregation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for a full health overview but does not explicitly state when to use this tool versus individual agents (e.g., 'use when you need a complete health assessment, use specific agents for targeted checks'). No explicit exclusions or alternatives are mentioned, though the comprehensive nature is implied.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry full behavioral disclosure. It mentions 'alerting thresholds' and 're-training trigger plan' but does not state whether the tool performs actions (e.g., alerts, triggers retraining) or only reports recommendations. It also omits potential side effects, permissions required, or whether it modifies the model. This lack of detail leaves the agent uncertain about the tool's side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence: it opens with the core action ('Monitor an ML model in production'), then enumerates specific metrics and features using a colon and em-dash. It is concise, free of filler, and front-loaded with the most important information, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Since there is no output schema, the description should clarify what the tool returns or accomplishes (e.g., a report, alerts, or actions). It mentions 'alerting thresholds' and 're-training trigger plan' but does not specify the output format, whether it returns data, or how the results are delivered. This leaves critical context missing for an agent to invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema provides complete descriptions for both parameters (request and language), achieving 100% coverage. The tool description adds no additional semantic context for these parameters; it does not explain how 'request' should be formulated or how 'language' affects behavior. Thus, it meets the baseline but adds no value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Monitor an ML model in production' with specific metrics (drift, accuracy decay, latency, cost) and additional features (alerting thresholds, re-training trigger plan). This distinctly identifies it as a monitoring tool for ML models, distinguishing it from siblings like model evaluation or other agents.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for monitoring ML model performance in production but does not explicitly state when to use it versus alternatives or mention conditions for not using it. It lacks explicit comparisons to sibling tools (e.g., timps_model_evaluator) and does not provide use-case boundaries, though the specificity of 'production monitoring' offers some guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full responsibility for disclosing side effects or read-only behavior. It does not state whether the tool modifies anything, requires permissions, or has rate limits, leaving behavior ambiguous.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that efficiently lists the guide's components without unnecessary verbiage or structural complexity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description lists what the guide includes but omits details about output format, expected use case, or parameter specifics. With no output schema or annotations, this leaves significant gaps in understanding the tool's full behavior and context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema includes a single parameter (repo_path) with no description or required flag. The tool description does not mention or explain this parameter, forcing the agent to infer its meaning solely from the name, which is insufficient given the lack of schema detail.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: generating a customised onboarding guide with specific components (most-touched files, architecture overview, key modules, recent PR walkthroughs). This is a specific action on a resource (repo_path) and distinguishes it from the many sibling tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage (when an onboarding guide is needed) but does not explicitly state when to use this tool over alternatives. Given the large number of sibling tools, explicit guidance on suitable scenarios would improve clarity.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations, so the description carries the burden. It states the tool rewrites prompts, which implies a non-destructive operation (though rewrite could be destructive to the original if not careful). It doesn't disclose side effects, output format, or whether it modifies the input or creates a new version. Sufficient for a text-processing tool but lacks depth.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concatenated sentence that is concise (14 words) and front-loaded with the verb 'Rewrite'. It conveys the purpose and methods efficiently without padding.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is relatively simple (2 optional params, no output schema, no annotations). The description covers the core function but lacks guidance on expected output, reversibility, or quality guarantees. It doesn't say what the rewritten prompt looks like or how to assess the improvement. Given the simplicity, it's adequate but could mention typical use cases or limitations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema already documents both parameters. The description adds context about what the tool does but doesn't add meaning about the 'request' or 'language' parameters beyond their schema descriptions. 'language' default is python, but the description doesn't explain why language matters for prompt rewriting, or if it affects the rewrite style.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool rewrites prompts to improve LLM output using specific techniques (Chain-of-Thought, XML tags, few-shot examples). It has a specific verb (rewrite) and resource (prompts), and the mention of techniques distinguishes it from generic prompt-related tools, though no sibling tool specifically does the same.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when you have a prompt that needs improvement, but it doesn't explicitly state when to use this tool versus alternatives like timps_self_critic_agent or timps_prompt_injection_scanner. No exclusions are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It only states that the tool 'designs' pipelines, but does not specify what the output or action will be (e.g., does it generate code, produce a plan, return a sequence of steps?). It lacks details on side effects, required inputs, or whether it modifies any files. This is a significant gap for a tool with no annotation support.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, tightly crafted sentence that front-loads the core purpose. It avoids redundancy and conveys the essential information without fluff. Every word contributes to the meaning, making it an excellent model of conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of RAG pipeline design, the description is too sparse. It does not clarify what the 'design' entails—whether it returns a step-by-step plan, code snippets, a configuration, or something else. The absence of an output schema increases the need for the description to set expectations, which it fails to do. Sibling tools like timps_rag_evaluator have more specific roles, but this one leaves users guessing about its deliverable.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already provides descriptive semantics for both parameters: 'request' (plain-English task) and 'language' (programming language). With 100% schema coverage, the description does not need to add parameter details. The description adds no extra meaning beyond the schema, so the baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: designing RAG pipelines with specific components (chunking, embedding, retrieval, reranking) and target frameworks (LlamaIndex or LangChain). It uses a specific verb ('design') and resource ('RAG pipelines'), distinguishing it from siblings like timps_rag_evaluator or timps_local_rag_builder which focus on evaluation or building.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is for the design phase of RAG pipelines, but does not explicitly state when to use it versus alternatives. It does not provide exclusions or mention related tools (e.g., 'use timps_rag_evaluator for evaluation'). The 'design' verb suggests it is not for implementation, but this is implicit rather than explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It mentions 'execute' and 'runnable exploit harness' but does not clarify whether actual execution occurs, whether authorization is required, or any safety guardrails. This is a security-sensitive tool where such ambiguity is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single concise sentence, front-loaded with the main verb, and enumerates key elements without fluff. Every word adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a red-team engagement tool, the description covers the main output areas (threat model, test cases, payloads, exploit harness, remediation). It does not specify return format or execution safety, but the deliverable list is reasonably complete for the stated purpose.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3 even though the description adds no parameter-specific details. The description's mention of 'context' and 'language' maps to the schema but does not enrich it.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb+resource: 'Plan and execute an OWASP-style red-team engagement' and lists concrete deliverables (threat model, test cases, payloads, runnable exploit harness, remediation checklist). This clearly distinguishes it from sibling tools focused on, e.g., 'security_guard' or 'security_remediation'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage via 'Plan and execute an OWASP-style red-team engagement' but provides no explicit when-to-use vs alternatives, no exclusions, and no guidance on when NOT to use this tool. Given many security-related siblings (threat_intel_analyst, prompt_injection_scanner, etc.), explicit differentiation would help.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not mention side effects, permissions, whether it performs mutations, or any other behavioral traits. The tool's operational impact is opaque.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence that efficiently lists all major deliverables of the release plan without any redundancy or extraneous information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
While the description enumerates the components of the release plan, it omits details about how parameters affect the output, what the final response format is, or any usage context. It is adequate for basic understanding but lacks depth.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description does not reference the 'request' or 'language' parameters, adding no meaning beyond the schema definitions. It relies entirely on the schema descriptions for parameter understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: to produce a release plan with specific components (SemVer bump, release notes, rollout strategy, etc.), which distinguishes it from other specialized sibling tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for release planning but does not explicitly specify when to use this tool over alternatives, such as a changelog generator or sprint planning agent. The purpose is clear, but guidance on when to invoke it is implicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It does disclose the output structure and depth options, which is useful. However, it omits behaviors like whether the tool performs live web searches, uses internal knowledge, has rate limits, or can fail on obscure topics. This is a moderate level of transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the core purpose, and every sentence adds value. It lists the output sections and depth options without any fluff or redundant phrasing.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a relatively simple tool with two parameters and no output schema, the description covers both input (topic, depth) and the expected return format. It is complete enough for invocation, though it lacks details on how depth levels differ semantically and does not address edge cases. The sibling context is not leveraged for differentiation, but the core invocation needs are met.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with both parameters described in the schema. The description's mention of depth options ('quick, medium (default), deep') largely repeats the schema's default and description, adding minimal new meaning. The topic parameter is self-explanatory, so the description does not need to compensate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool performs deep-dive research on any topic and specifies the structured brief it returns (key findings, consensus view, controversies, recommended actions, sources). This is a specific verb+resource pairing. However, it does not distinguish itself from sibling research tools like timps_research_agent or timps_deep_research_agent, so it lacks sibling differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no explicit guidance on when to use this tool versus alternatives such as timps_web_search, timps_research_agent, or timps_deep_research_agent. It merely states 'any topic' without context, prerequisites, or exclusions, leaving the agent to guess the appropriate selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It discloses that the tool can run terraform plan if plan_text is omitted, and that it requires approval for high-risk plans. However, it doesn't detail what happens after review (e.g., does it block apply? does it return a risk assessment?), or any side effects like running terraform plan in the repo.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the core purpose, and adds the key behavioral note about approval. It's efficient with no fluff, though it could be slightly more structured with explicit parameter guidance.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (reviewing terraform plans, potentially running plan, gating apply), the description is adequate but not complete. It doesn't explain the output format (e.g., risk assessment, approval mechanism), nor does it clarify what 'high-risk' means or how the approval flow works. With no output schema and no annotations, more detail would be expected.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 50%: plan_text has a description, but repo_path has none. The description adds context that plan_text is optional and will run terraform plan if omitted, which is helpful. However, repo_path is left unexplained—the agent must infer it's the path to the terraform repo, which is a gap given the low coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool reviews terraform plan output for destructive changes, which is a specific verb+resource combination. It distinguishes itself from siblings like timps_iac_drift_detector and timps_pr_reviewer by focusing on destructive change review and approval gating.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when reviewing terraform plans for destructive changes, and mentions 'requires explicit approval before allowing apply on high-risk plans,' which gives some context. However, it doesn't explicitly state when not to use it or name alternative tools for non-destructive plan reviews.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions analysis, finding, suggesting, and proposing, implying a read-only or advisory role, but it does not explicitly state that the tool makes no changes, nor does it mention any access requirements (e.g., git history permissions) or limitations. The absence of any side-effect disclosure makes it insufficiently transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence of about 17 words, front-loading the main action and listing all key outputs. There is no fluff or redundancy, making it highly concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has moderate complexity (involves test suite analysis and git history) and no output schema. The description lists actions but does not explain what the tool returns (e.g., a report, a list of suggested tests, a config file) or any prerequisites. It lacks completeness for an agent to know what to expect after invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Both parameters are fully described in the schema (100% coverage). The description does not add extra semantics beyond what the schema provides (e.g., it doesn't elaborate on how 'request' or 'language' affect the analysis). Since schema coverage is complete, the baseline is 3, and the description adds no meaningful additional parameter information.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: analyzing test suites and git bug history to find untested code paths, suggest property-based tests, and propose mutation-testing configs. It uses specific verbs and resources, and it distinguishes from siblings like timps_unit_test_writer (which writes tests) and timps_flaky_test_detective (which detects flaky tests).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the scenario (when you want to analyze test coverage and get suggestions), but it does not explicitly state when to use this tool versus alternatives. There is no mention of exclusions or when not to use it. Given the large sibling list, explicit guidance would be helpful, but the purpose is clear enough for basic inference.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It states the tool returns a complete test file ready to run, which is useful. However, it doesn't disclose potential side effects (e.g., whether it modifies files, requires network access, or has execution limits). For a code analysis tool, this is adequate but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that efficiently conveys the core purpose and output. It's front-loaded with the action ('Analyse source code') and includes key coverage areas. No wasted words, though it could be slightly more structured with a second sentence for usage context.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (3 params, no output schema), the description covers the main purpose and output. However, it lacks details on return format specifics (e.g., file path vs. string), how the framework auto-detection works, and any constraints on source code size or language support. It's adequate but leaves gaps for an agent to infer.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all three parameters. The description adds no additional parameter-level detail beyond what the schema provides (e.g., it doesn't explain what 'auto' framework detection means or how language affects output). Baseline 3 is appropriate since the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool analyzes source code and generates a comprehensive test suite covering happy paths, edge cases, and error conditions, and returns a complete test file. It distinguishes itself from siblings like timps_test_intelligence and timps_flaky_test_detective by focusing on generation rather than analysis or detection, though it doesn't explicitly name alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage: provide source code to get tests. It doesn't explicitly state when to use this vs alternatives like timps_test_intelligence or timps_test_data_agent, nor does it mention limitations (e.g., only for functions/classes, not full projects). The context is clear but lacks explicit guidance on when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of disclosing behavioral traits. It does not mention whether the tool is read-only, has side effects, or requires specific permissions. This lack of transparency could mislead an agent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, dense sentence that packs all essential information without fluff. It is well-structured and immediately comprehensible.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the tool's purpose but does not specify output format, return value, or any additional context. Given the lack of an output schema, this leaves some ambiguity about what the agent can expect from the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Parameter descriptions are minimal: 'request' is described as 'Plain-English task or context' and 'language' as 'Primary programming language'. They add little beyond the schema and do not explain how they affect the tool's behavior or output.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: analyzing won/lost deals, surfacing reasons (pricing, champion, timing, competitor, fit), and recommending sales-coaching and product fixes. It is specific and distinct from typical analytics tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for win/loss analysis but does not explicitly mention when to use this tool versus alternatives or any exclusions. It lacks guidance on selecting this over similar analytical tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral details, but it only states that the tool generates tests. It does not mention whether files are written to disk, whether tests are executed, what side effects occur, or what the agent receives in response.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, focused sentence with no filler. Every phrase ('page objects,' 'fixtures,' 'CI config') adds concrete value about scope and deliverable.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool that generates a full Playwright test suite, the description feels under-specified: it lacks behavioral expectations and return-value guidance, and there is no output schema to compensate. It is adequate for basic selection but deficient for understanding execution impact.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents the 'request' and 'language' parameters. The description does not add parameter-level context, but since the schema covers both parameters, the baseline of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a strong verb ('Generate') with a specific resource ('Playwright E2E tests') and concrete artifacts ('page objects, fixtures, CI config'). This clearly differentiates it from sibling test-related tools and other automation agents.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The intended use is implied by 'Playwright E2E tests,' so an agent can infer when this tool is relevant. However, there is no explicit when-to-use or when-not-to-use guidance, and no alternatives are named despite many similar sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. The description implies side effects ('configure', 'preview what would change') but doesn't explicitly state that it modifies files, may require permissions, or could overwrite existing configs. It mentions --dry-run for preview, so it's clear it writes files by default. This is reasonable but not highly detailed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
A single, information-dense sentence that states the action, scope, and a key usage tip (--dry-run). No redundancy, no filler. Front-loaded with the verb and target.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Simple tool with 2 optional params and clear purpose. The description covers it adequately but doesn't detail side effects, idempotency, or what happens if tool_id is omitted. Given the configuration-writing nature, more context would be helpful but is not critical for basic use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% (both parameters documented). The description adds value by explaining the purpose of dry_run (preview changes) and implies tool_id scoping ('every AI coding tool', 'all detected' default in schema). No additional syntax or nuance beyond the schema, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the action ('auto-configure'), the resource ('TIMPS Swarm as an MCP server'), and the scope ('every AI coding tool installed'). It distinguishes from sibling tools like timps_list_agents or timps_run_task which are about listing/running agents, not installation/config. Minor deduction for not explicitly contrasting with other timps_* tools, but it's specific enough.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description mentions the --dry-run flag to preview changes, which is a usage hint. It doesn't explicitly state when to use this tool vs alternatives, but the purpose is fairly unique (configuring MCP in other tools). However, it lacks guidance on when NOT to use it (e.g., when a specific tool is unsupported).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the intended outcome ('Design... pipelines') but does not clarify whether the tool produce code, creates files, requires credentials, or returns a plan. The lack of side-effect or output details leaves significant behavioral ambiguity.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a concise single sentence that states the main purpose and scope without fluff. It is front-loaded with 'Design', immediately establishes what is tool does, and includes a focused list of technologies. Every word contributes value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a description of a 2-param, no-output-schema tool, the one-liner is usable but incomplete. It lacks context on what to expect in response, prerequisites, or how it differs from many related sibling tools. An agent can select it but may not know how to effectively use it without additional clarification.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema covers 100% of parameters with meaningful descriptions for 'request' and 'language', so the baseline is 3. The tool description itself adds no additional parameter context beyond what the schema already provides. This meets the minimum viable threshold.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'Design' with a clear resource: dbt/Airflow/Prefect/Dagster ETL/ELT pipelines, adding scope via 'with monitoring and lineage.' This distinguishes it from siblings like timps_pipeline_healer, which focuses on healing, and timps_data_wrangler, which handles data manipulation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is used when someone wants to design data pipelines in specific frameworks, but it provides no explicit when-to-use/when-not-to-use guidance. It does not mention alternatives or any conditions that would make this tool the right choice versus sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It states actions ('validate and clean') and outputs, but does not explain side effects, destructive potential, permissions, or what happens to the dataset (e.g., modified in place vs. copies). This matches the 'update_drive' calibration example where mutation is implied but safety/reversibility is missing.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that efficiently front-loads the core purpose and key outputs. Every phrase adds value, with no redundant or filler content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description adequately names the tool's purpose and outputs (data cards, quality reports), which helps for a free-form agent tool. However, it lacks detail on expected input format, return behavior, and side effects. Since there is no output schema and no annotations, more context would improve completeness, but it is not severely deficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents both parameters ('request' and 'language') clearly. The description adds no extra parameter detail, but the baseline score of 3 is appropriate since the schema handles the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Validate and clean') and resource ('ML training datasets'), and adds concrete outputs ('generate data cards and quality reports'). This clearly distinguishes it from sibling tools like timps_data_wrangler or timps_data_pipeline by focusing on ML-specific dataset quality artifacts.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for ML dataset validation and cleaning, but does not explicitly state when to use this tool over alternatives, nor does it provide exclusions or conditions. It is inferable from the description but not explicitly guided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden for behavioral transparency. It only states that it generates code; it does not disclose what the tool returns, whether it writes files, whether it requires network access, or what side effects or limitations exist.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with a front-loaded verb and no filler. Every word contributes meaningful context about the tool's purpose and capabilities.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple two-parameter schema and lack of output schema, the description provides a minimally viable purpose. However, it omits usage boundaries, return/output behavior, and any qualifiers about generated code, leaving the agent with some gaps for a tool of this nature.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the request and language parameters are already documented. The description adds platform/feature context but no additional parameter semantics beyond what the schema provides, matching the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Generate') and identifies exact target resources: Cloudflare Workers, Vercel Edge, and Fastly code. It also adds distinguishing scope with 'KV storage and geo-routing,' making it clearly distinct from generic code-generation siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The intended use is implied by the description: use when generating edge platform code with KV storage and geo-routing. However, it does not explicitly state when to choose this tool over alternatives or mention any exclusions, so the guidance remains implicit rather than explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose side effects. It says it outputs patches but does not state whether it modifies resources, requires cluster credentials, or is read-only. The phrase 'Diagnose... Outputs' implies it produces artifacts, but the write/side-effect nature is ambiguous, leaving behavioral transparency insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: two sentences, front-loaded with the action ('Diagnose Kubernetes workloads') and ends with the output type. Every word adds value and no redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description lists what can be diagnosed and the output format, but doesn't mention any prerequisites (e.g., cluster access), scope limits, or how the request parameter should be phrased to get best results. Given no output schema, it provides decent context but leaves gaps for a complex domain like Kubernetes.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already describes the 'request' parameter as a plain-English task, and the tool description reinforces this by saying 'Request: Plain-English task or context for the agent.' The description doesn't add additional meaning beyond the schema, which has 100% coverage. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool diagnoses Kubernetes workloads and lists specific resource types (pods, services, RBAC, resources, network policies) with a concrete output (fix YAML, Helm/Kustomize patches). This is specific verb+resource and distinguishes it from siblings like timps_network_analyzer.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
It implies usage for Kubernetes diagnosis but does not explicitly state when to choose this over alternatives or any exclusions. Given many sibling tools, there is no guidance on when not to use it or what prerequisites exist, but the context is clear enough for general use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions conditional integration of syft/trivy and risk flagging, but does not state whether the tool writes files, its side effects, network usage, or permissions required. For a generation tool, it should clarify if it is read-only or modifies the environment, which is absent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence that is front-loaded with the core action and output. It efficiently conveys multiple aspects (formats, source, integrations, risk flagging) without fluff or repetition. Every phrase earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool of moderate complexity, the description covers the main purpose but omits critical context such as the output format (file vs. text), prerequisites (e.g., availability of syft/trivy handling), and any limitations. Without annotations or an output schema, the description should specify what happens on success/failure and the nature of the generated SBOM (e.g., where it is stored). This is a gap, so a score of 3 is appropriate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema provides 100% coverage of both parameters ('request' as plain-English task, 'language' with default). The description does not add additional meaning beyond what the schema states; it only ties to the overall purpose. With high schema coverage, the baseline of 3 is appropriate since the description adds no extra parameter-specific details.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool generates a CycloneDX/SPDX SBOM from a project tree and manifests, with additional actions like integrating syft/trivy and flagging risks. It uses a specific verb ('Generate') and resource ('Software Bill of Materials'), distinguishing it from sibling tools like license compliance or dependency scanners.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context (supply-chain auditing) but does not explicitly state when to use this tool versus alternatives. There is no mention of when not to use it or reference to sibling tools like timps_license_compliance_scanner or timps_dependency_sentinel. It provides some context (from project tree + manifests) but lacks explicit exclusions or alternative guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears the full transparency burden. It does disclose the generated content areas (mTLS, traffic policies, retries, circuit-breakers, observability, multi-cluster, and migration plan), but it does not state whether the tool outputs YAML/Helm manifests, writes files, applies changes, or requires cluster access. This is a meaningful behavioral gap for a config-generation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, dense sentence that begins with the primary verb and packs the technology scope and feature list without filler. Every clause adds information, and it is easy to scan.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has only two simple parameters, but there is no output schema and no annotations. The description enumerates scope well but omits important context like the exact output format, how the migration plan is delivered, and whether the tool only generates configs or also applies them. It is minimally adequate but not fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, and both parameters ('request' and 'language') already have clear descriptions in the input schema. The tool description adds no additional parameter-specific meaning, but the schema carries the load, so the baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description starts with a specific verb ('Generate') and identifies the resource: production-grade service-mesh configuration. It further scopes the tool by listing supported meshes (Istio / Linkerd / Consul) and included features (mTLS, traffic policies, retries, circuit-breakers, observability, multi-cluster, migration plan), clearly distinguishing it from sibling tools focused on Kubernetes navigation or migration.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives no guidance on when to use this tool versus alternatives. Sibling tools like timps_kubernetes_navigator, timps_migration_pilot, and timps_terraform_plan_reviewer overlap in infrastructure contexts, but no exclusions or conditions are provided. The usage context is only implied by the tool's name and output scope.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It mentions generating realistic and edge-case-covering data, giving some insight into behavior, but does not detail outputs, side effects, or limitations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence with no redundant information. It effectively covers the core functionality without fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and lack of output schema, the description sufficiently indicates the generation of seed data, but does not specify return format or error handling. It is adequate but could be more complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already provides clear descriptions for all parameters (schema, count, format, locale). The tool description adds minimal new meaning, mostly repeating the schema's purpose, so the baseline holds.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool generates realistic, edge-case-covering seed/fixture data for multiple input types (JSON schema, SQL DDL, plain-text description), which is specific and actionable.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not explicitly state when to use this tool over alternatives or when not to use it. It implies usage for test data generation but lacks direct guidance or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full responsibility for behavioral disclosure. It only lists output artifacts (links, QR codes, webhook handlers) and omits critical behaviors such as whether it makes external API calls, requires credentials, or has side effects. For a tool handling webhook handlers, this lack of transparency could lead to misuse.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that front-loads the action and key deliverables. It is free of filler, flows naturally, and conveys the tool's scope efficiently.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The schema is simple, but the tool is an agent with a broad plain-English 'request' parameter. The description lists core capabilities yet omits execution context, output format, prerequisites, or limitations. This is adequate for a basic understanding but leaves clear gaps for an agent that may perform complex payment-related tasks.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% (both 'request' and 'language' are described), so the baseline is 3. The description does not add any parameter-level meaning beyond what the schema already provides, leaving parameter semantics entirely to the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'Generate' with concrete objects (UPI deep links, QR codes, webhook handlers) and scopes the domain to 'India UPI'. This clearly distinguishes it from sibling agents like timps_gst_compliance or timps_abdm_agent, making the tool's purpose obvious.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when UPI payment infrastructure is needed, but does not explicitly state when to use this tool over alternatives or provide exclusions. The sibling list contains no other payments agent, so the differentiation is implicit rather than explicit, leaving the agent to infer context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry the behavioral transparency burden. It clearly says the tool checks, warns, and generates certbot renewal commands, which signals a read/analysis behavior. But it does not explicitly say whether the generated commands are executed, whether files are modified, or how it selects the config files, so transparency is partial.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded: two sentences that cover the core purpose, the alert threshold, and the expected output. There is no filler or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description provides a reasonable high-level understanding of behavior and output, but lacks enough detail for confident parameterization. Since there is no output schema and no annotations, important context about parameter use and the exact nature of the generated commands is missing. It is usable for basic discovery but incomplete for full operational clarity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not explain the `hosts` or `repo_path` parameters. It refers to 'hosts found in config files,' but does not specify whether `hosts` is a filter, what `repo_path` defaults to, or how the parameters interact. The parameter names are guessable, but the description provides very little semantic value beyond the schema itself.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description uses a specific verb and resource: 'Check TLS certificate expiry for all hosts found in config files.' It also defines concrete behavior: warning at 30 days and generating certbot renewal commands. This clearly distinguishes it from the sibling tools, none of which focus on TLS certificate checking or renewal.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The intended usage is implied: use this when you need to audit TLS certificate expiry or prepare certificate renewals based on config-file-defined hosts. However, there is no explicit when-to-use vs. when-not-to-use guidance, no prerequisites, and no comparison to alternative tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavior. It mentions outputs (intervals, backtest MAPE/MASE, ordering recommendation) but does not mention side effects, data access, or safety profile. A forecasting tool is likely non-destructive, but this is not stated, leaving the agent uncertain.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the core purpose and then the key outputs. Every word earns its place—no fluff, no redundancy, perfectly concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
While the tool is complex (forecasting) and has no output schema, the description adequately covers return values (intervals, MAPE/MASE, ordering recommendation). However, it does not specify how the request parameter should be structured or what information is expected, leaving some ambiguity for a free-form input.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% for both parameters (request and language), so the baseline is 3. The description does not add any detail beyond the schema; it neither elaborates on how to phrase the request nor explains the language parameter, so it adds no value here.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: to produce a demand forecast at SKU/location level, including seasonality, promotions, and trend. It specifies the granularity and key features, distinguishing it from the many generic sibling tools like timps_dispatch or timps_run_task.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for demand forecasting but provides no explicit when-to-use guidance, prerequisites, or alternatives. Given the large list of sibling tools, it does not explicitly differentiate or state when this tool is preferred over others.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the transparency burden. It does convey a non-mutating 'Scan' behavior and describes the output ('severity-ranked report with upgrade commands'), but it does not disclose whether the scan requires network access, how CVE data is sourced, or whether any files are modified.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two concise sentences, front-loaded with the action and scope, followed by the output. Every phrase contributes: supported manifest types, CVE/outdated focus, and the report's severity ranking and upgrade commands.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple two-parameter schema and no output schema, the description adequately summarizes the return value as a 'severity-ranked report with upgrade commands.' It slightly under-specifies auto-detection behavior and output detail, but is complete enough for an agent to select and invoke the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema already documents both parameters. The description lists the supported manifest types in prose, but this largely repeats the manifest_type property description and adds no additional semantic guidance beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the verb and resource: 'Scan a dependency manifest... for CVEs and severely outdated packages' and states the return artifact. It is specific enough to distinguish from generic update or security tools, though it does not explicitly name or contrast sibling tools like timps_dependency_rebel.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The intended use is implied by the description: use this when you need to scan a supported dependency manifest for CVEs or severely outdated packages. However, there is no explicit when-to-use guidance, no mention of when not to use it, and no comparison with alternative sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden of behavioral disclosure. It only says 'Design' without indicating what the tool actually does (e.g., generates code, returns a plan, requires interaction), any side effects, or auth/permission needs. This is a significant gap for a tool with no annotation support.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence that front-loads the core purpose. Every word contributes to the meaning with no redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Without an output schema or annotations, the description is insufficiently complete. It does not explain what the tool returns (e.g., a design document, code snippets, a plan), what constitutes a valid request, or any prerequisites. This is a notable gap for a tool that presumably generates complex pipelines.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Both parameters are fully described in the schema with coverage at 100%. The description adds that the tool deals with FL pipelines, but it does not elaborate on the 'request' parameter (e.g., typical phrasings) or 'language' (e.g., languages supported beyond Python). Since the schema covers the basics, a 3 is the appropriate baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: to design federated learning pipelines using specific frameworks (Flower, FedAvg, PySyft) and with specific considerations (differential privacy, aggregation strategies). It distinguishes itself from sibling tools like timps_finetuning_agent and timps_model_evaluator by specifying the FL domain and frameworks.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly implies the tool's intended use for FL pipeline design, but it does not explicitly state situations where it should not be used or alternative tools for similar tasks. Given the sibling list, this is reasonably clear context without needing exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations are absent, so the description must carry the burden. It mentions '10-agent SDLC pipeline' and the sequential stages, implying a complex multi-step process, but does not describe potential side effects, resource intensity, or failure modes. It adds some value (listing stages, examples) but leaves many behavioral details undisclosed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact, two sentences, and front-loaded with the key action and pipeline stages. The use case examples are useful and not redundant. Minor redundancy: '10-agent' is repeated in the pipeline stages listing, but still concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description is adequate for a complex tool with full schema coverage and no output schema. It explains the pipeline stages and typical use cases, but given the tool's complexity (10 agents), it could benefit from more detail on expected behavior, iterations, or potential limitations. No output schema means description could clarify return format, but it doesn't.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already fully describes all three parameters (request, language, max_iterations) with clear descriptions and defaults (100% coverage). The tool description adds no additional parameter semantics beyond what the schema provides, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it runs a full 10-agent SDLC pipeline, specifying the stages (product manager → architect → ... → docs) and giving concrete examples of use cases (writing code, fixing bugs, building APIs). This distinguishes it from sibling tools like timps_dispatch or timps_agent_composer, though it doesn't explicitly name alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides a clear context: 'Use for software development tasks' with examples, which helps the agent decide when to invoke this tool. However, it does not explicitly state when NOT to use it or mention alternative tools for narrower tasks, but the general guidance is sufficient.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description must convey side effects and safety. It does not mention whether the tool modifies data, requires special permissions, or has any limitations. It only states what it returns, not potential impacts.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that clearly and efficiently conveys the tool's purpose and output. It is well-structured with the main action front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description explains the output (optimized rewrite, index recommendations, speedup) and lists supported databases, but does not cover error scenarios or limitations. Still, it provides a clear overview of what the tool does and returns.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already provides descriptions for all parameters, and the tool description adds little beyond repeating the supported databases. It does not clarify the expected format or additional context for the parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: analyzing a slow SQL query and returning optimization details such as rewrite, index recommendations, and speedup estimate. It also specifies supported databases, distinguishing it from other tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for SQL query optimization but does not explicitly contrast with alternative tools or provide conditions for use. It is clear but lacks explicit guidance on when to use vs. not use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of behavioral disclosure. It states the tool 'scans' and 'generates a dry-run cleanup script,' which implies no destructive actions, but it doesn't explicitly state that it makes no changes or that the cleanup script is only a suggestion. This is somewhat helpful but leaves ambiguity about whether the script is actually executed or just generated.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise (two sentences) and front-loaded with the primary purpose, then details what it scans and produces. No filler, though it could benefit from a brief mention of output format. Still, it's efficient and clear.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a system optimizer toolasi, the description covers key aspects: it diagnoses, scans specific areas, returns a report, and generates a dry-run script. It doesn't specify output format (e.g., JSON structure), but with no output schema or annotations, it provides sufficient context for an agent to understand the tool's function. The sibling context (e.g., timps_environment_doctor) might be related, but the description is adequate for basic selection.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The only parameter 'context' is optional and has a clear description ('Optional: extra context like laptop fan running loudly'). Since schema coverage is 100% and the description adds a concrete example, it adds value beyond the schema's basic 'Optional' label.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool diagnoses slow computers ('Diagnose why a computer is slow') and lists what it scans (CPU/RAM processes, startup items) and returns (report with processes to kill/disable, dry-run cleanup script). This is a specific verb+resource, but it doesn't explicitly distinguish from sibling 'timps_full_checkup' which likely covers similar ground.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for diagnosing slowness but doesn't explicitly say when to prefer this over 'timps_full_checkup' or other siblings. It mentions scanning specific system areas, giving a hint of scope, but lacks explicit exclusions or alternatives. The optional 'context' parameter is a weak guideline for providing extra details.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It does disclose a key behavioral trait: the inclusion of 'safety approval gates'. It also hints at a coupling with runtime tools. However, it omits details like error behavior, permission/authentication requirements, or whether the execution is idempotent, which would be valuable for a planning/mutation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, each earning its place. The first states the core action and output; the second situates the tool in the broader ecosystem. No fluff, no repetition of schema-visible information, and front-loaded verb leads.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 2 parameters, high schema coverage, and no annotations or output schema, the description covers the essentials—purpose, output medium, safety posture, and integration context. Still, for a safety-relevant agent that handles OS-level automation, a sentence on scope or expected usage flow would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so this is a baseline 3. The description does add slight value by clarifying the OS-specific output context (cliclick/xdotool/PowerShell), which implicitly relates to the 'language' parameter's potential targets, but it does not go beyond what a well-documented schema already communicates.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses specific verbs ('Plan', 'emit') and a clear resource ('GUI / computer-use task', 'OS-specific step scripts'), naming concrete technologies (cliclick / xdotool / PowerShell). It further distinguishes itself from the large sibling list by noting it 'Pairs with the runtime computer_use tools', which is a clear differentiation point.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use the tool: whenever a GUI/computer-use task must be planned and scripted. However, there is no explicit 'use when', 'not for', or named alternatives, which is notable given the enormous sibling list of specialized agents. The guidance is functional but relies on inference.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description carries the disclosure burden. It does reveal a key behavioral trait: it wraps installed tools and falls back to static Dockerfile analysis. However, it does not describe side effects, execution duration, environment requirements, or what the results look like—meaningful gaps for a tool with no annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two tightly written sentences. The first sentence states purpose and outputs, the second explains implementation and fallback behavior. Every word contributes value; no fluff or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool wraps multiple scanners and has no output schema, so the description should clarify what the agent should expect in return. It explains scanning scope and fallback, but leaves out how the 'request' parameter steers the scan, what result format is returned, and whether the scan targets a local image, registry image, or a Dockerfile path. These gaps make it adequate but not complete for a tool of this complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% for both parameters ('request' and 'language'), so the schema carries the parameter meaning. The description adds no additional parameter context or usage examples, which is expected at this baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific action ('Scan') with a specific resource ('container image / Dockerfile') and the exact value produced ('CVEs, misconfigurations, and supply-chain risk'). It also explains the implementation approach (wrapping trivy/grype/syft with a static analysis fallback), making the tool's role clear and distinct from generic security tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage context is implied by the scope: use when you need vulnerability or risk scanning for container images/Dockerfiles. However, there is no explicit guidance on when NOT to use it or which sibling tools (e.g., security_guard, sbom_generator, license_compliance_scanner) would be better alternatives for adjacent use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the transparency burden. It discloses the internal process (decompose, parallel search, cross-reference) and output (sourced report with citations and bottom-line answer), but it omits limitations, potential side effects (e.g., many network requests), authorization requirements, or failure handling. This is adequate but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, information-dense sentence that is front-loaded with the tool's role. Every clause adds value—what it does, how it works, and what it returns. There is no redundancy or fluff, though the '[N] citations' placeholder is slightly awkward.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a complex research agent with no output schema, the description provides a solid high-level overview of inputs and outputs, but lacks operational details like expected runtime, format of the report, or constraints. It is sufficient for basic selection and invocation but not fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already provides descriptions for both parameters, giving 100% coverage. The tool description does not add further meaning about how the parameters are used (e.g., the role of 'language' in the report), so the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it is a multi-hop, multi-source research planner that decomposes queries, runs parallel web searches, cross-references, and returns a sourced report with citations and a bottom-line answer. This specific verb+resource+scope distinguishes it from sibling tools like timps_web_search or timps_research_agent.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies its use for complex, multi-hop research tasks but does not explicitly state when to use it versus alternatives, nor does it mention exclusions or conditions. There is no comparison with sibling research tools, so guidance is limited to inferred context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the transparency burden. It does disclose key behavioral output ('Emits ingest, retrieve, generate, evaluate, Dockerfile, Makefile'), but it omits side effects, prerequisites (e.g., Ollama installed), whether files are overwritten, or whether network access is needed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single dense, front-loaded sentence with no wasted words. It communicates the core action, technical stack, input source, and output artifacts efficiently.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a scaffold-generation tool with only two simple parameters, the description covers the main purpose and outputs reasonably well. However, with no annotations or output schema, it lacks behavioral caveats and prerequisites, leaving some uncertainty about execution context and side effects.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% for both parameters, so the baseline is 3. The description adds minor context by suggesting 'request' should contain a corpus description, but it does not elaborate on the 'language' parameter beyond what the schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Build') with a clear resource ('fully-local RAG pipeline') and names concrete components (Ollama embeddings, Chroma/FAISS, reranker, chat) plus generated artifacts. This makes the tool's function unambiguous and differentiates it from sibling RAG-related tools like timps_rag_designer or timps_vector_db_agent.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'from a corpus description' implies the intended use case, and 'fully-local' hints at a specific scenario. However, there is no explicit guidance on when to prefer this tool over alternatives, no exclusions, and no mention of when it should not be used.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses the outputs (diff summary, complexity scores, improvement list) and implies a non-mutating 'produce a version' rather than directly modifying files, but it doesn't explicitly state whether the tool modifies files or requires any permissions. The return behavior is partially clarified but side effects are ambiguous.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, information-dense sentence that lists core actions and outputs with no filler. Every clause adds value, making it both concise and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 3 params and no output schema, it describes key outputs but lacks guidance on parameter combinations, language support specifics, or tool limitations. The core inputs and expected output artifacts are present, but it feels incomplete for an agent to decide whether this is the right refactoring tool and how to structure goals effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, with each parameter having a description (code, goals, language). The description itself adds no extra parameter detail but the example for goals ('reduce_complexity', 'extract_functions') is in the schema. This meets the baseline but provides no additional semantics beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's action (detect code smells and produce a refactored version) and its specific deliverables (diff summary, complexity scores, improvement list). It distinguishes itself from sibling tools like timps_pr_reviewer or timps_unit_test_writer by focusing on refactoring rather than review or test generation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use for code refactoring via 'detect code smells and produce a fully refactored version', but it doesn't explicitly state when to use this tool versus alternatives or provide exclusions. There is no guidance on when not to use it, such as for simple formatting or full-scale code review.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses the core behavior (scoring, identifying weaknesses, auto re-run) but omits potential side effects such as cost implications, risk of infinite loops if threshold never met, or state changes from re-running agents. It also does not mention defaults for threshold/max_retries, though these are in the schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with the primary purpose, and no redundant content. Every word contributes to describing the tool's function and its strategic context.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Describes the core loop but lacks details on output format, error handling, or what constitutes an 'improved prompt'. With no output schema and no annotations, it could be more explicit about termination conditions and edge cases, but it provides a minimally acceptable overview.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with clear field descriptions. The description references threshold and retries indirectly but does not add new semantics beyond the schema's own parameter docs. Baseline of 3 is appropriate as schema handles parameter meaning.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool scores outputs on a 1-10 scale, identifies weaknesses, and re-runs the originating agent with an improved prompt until a threshold is met. This verb+resource specificity distinguishes it from sibling tools like timps_dispatch or timps_run_task by focusing on the feedback loop.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Implies usage for quality assurance across the swarm ('closes the quality feedback loop'), but does not explicitly state when to use this over alternatives like timps_agent_composer or timps_prompt_engineer. No exclusions, prerequisites, or when-not-to-use guidance is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry the burden of behavioral disclosure. It states the output components (outline, prose, etc.), which clarifies what the tool returns. However, it does not mention any side effects, limitations, or prerequisites beyond the input parameters. It is transparent about the output but not about any internal behavior or constraints.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence that front-loads the main purpose and lists deliverables concisely. Every word contributes to the meaning, with no fluff or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description lists the output components clearly, which is helpful in the absence of an output schema. However, it does not explain how the parameters (request, language) are used, and the language parameter is confusingly described as 'programming language', which is irrelevant. The tool's complexity is moderate, but the parameter semantics are incomplete, leaving gaps in context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds no additional meaning beyond the schema, and the 'language' parameter with default 'python' is clearly misaligned for a story generator (not a programming task). The description does not explain or compensate for this mismatch, so it adds no value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: generating an original illustrated children's story with specific deliverables (outline, prose, page breaks, illustration prompts, PDF layout spec). This is a specific verb+resource and distinguishes it from all sibling tools, which are technical/dev-focused.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use the tool (for story generation) but provides no explicit guidance on when to use versus alternatives, nor any exclusions. Since all sibling tools are unrelated technical utilities, the use case is obvious, but there is no explicit context or when-not guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the safety/behavior transparency burden. It does convey a non-mutating-sounding 'diff and surface' behavior and hints at an explanatory output, but it does not explicitly say whether baselines or files are modified, whether external services are contacted, or what format the root-cause hints take.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that front-loads the action and scope, then states the expected outcome. There is no filler, repetition, or unnecessary qualifier.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a two-parameter tool with no output schema and no annotations, the description provides a solid overview but still leaves important context unstated: the exact shape/format of the report, what happens when a baseline is missing, and whether this is a read-only operation. It is adequate for basic selection but not fully self-contained.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already describes both parameters at 100% coverage, so the description does not need to document them. The description adds no extra semantics about how 'request' should be structured or how 'language' affects the diff, leaving it at the baseline score.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the resource ('design tokens / Storybook / screenshot baselines') and the specific action ('Diff ... and surface unintended visual changes with root-cause hints'). This distinguishes it from sibling detective/review tools like timps_flaky_test_detective or timps_storybook_story_generator.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The use case is implied: it should be used when you need visual regression checks or diff-based visual change detection. However, there is no explicit 'use when...' statement, no exclusions, and no direct comparison to sibling tools that might handle related visual or testing concerns.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations, so the description carries the behavioral burden. 'Audit' implies read-only analysis rather than mutation, and the listed check areas give useful behavioral scope. However, it does not state whether it modifies files, what input it requires (URL, file path, code snippet), or what kind of report it produces.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence with no filler. It front-loads the core purpose and then lists concrete audit categories, making it easy to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has no output schema and no annotations, so the description should explain what the audit returns and how to specify the target. It does neither. With zero required parameters, it is unclear what happens if 'request' is omitted, and the odd 'language' parameter adds confusion rather than guidance.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline 3 is appropriate. The tool description adds no parameter-specific meaning. In particular, the 'language' parameter (default: python) seems unrelated to auditing HTML/React/Vue frontends, and the description does not clarify how 'request' should be formulated.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description names a specific verb ('Audit'), a specific resource ('frontend (HTML / React / Vue)'), and specific standards/check areas ('WCAG 2.2 AA & AAA', 'colour contrast, ARIA, keyboard nav, focus order, screen reader hints'). This clearly distinguishes it from sibling tools like ui_ux_agent or full_checkup.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description makes the intended use clear: accessibility auditing of frontend code. It does not explicitly mention when not to use it or name alternatives, but the context is strong enough for an agent to infer when this tool is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses behavioral outputs (ICS patch and focus-mode script), which indicates it produces files rather than directly mutating state. Yet it does not mention any side effects, permissions, or limitations, leaving a moderate transparency gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, front-loaded with the core action, and lists specific actions and outputs. Every phrase adds value with no redundancy or extraneous detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (two simple params, no nested objects, no output schema), the description provides a solid overview of the tool's purpose and outputs. It lacks details on the exact form of the ICS patch or focus-mode script, but overall it is sufficiently complete for an agent to understand the tool's role.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with clear descriptions for both 'request' and 'language'. The tool description adds no additional meaning about these parameters, so it does not go beyond the schema. Baseline of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'Re-design' with a clear resource 'calendar' and lists concrete actions (time-block deep work, batch meetings) and outputs (ICS patch, focus-mode script). It differentiates from siblings by its unique calendar-redesign scope, even though no alternative is explicitly named.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'noisy calendar' implies use when the calendar is cluttered, giving a contextual trigger. However, it lacks explicit when-to-use vs alternatives, no exclusions, and no indication of when not to use. This is implied rather than explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry the behavioral burden. It clearly indicates the tool produces a plan, not an executed migration, and enumerates key artifacts. Still, it does not disclose whether the tool inspects schema, connects to live databases, or merely generates a generic plan from the request.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that leads with the action and resource, then efficiently lists the plan's major components. Every phrase adds meaningful scope and no filler or redundancy is present.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool that is explicitly scoped as a planning agent, the description covers the most important context: the zero-downtime constraint and the expected plan components. It stops short of clarifying input/output expectations, but the optional request parameter and lack of an output schema lower the required burden.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% coverage since both 'request' and 'language' have descriptive text. The description adds no parameter-specific meaning, but the schema already documents the optional plain-English request and default language, so the baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Plan') and a clear resource ('a zero-downtime database migration'), then names concrete plan components: expand-contract phases, backfill scripts, dual-write strategy, kill-switches, rollback plan. This clearly distinguishes it from the generic sibling timps_migration_pilot and other DB-related agents.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use the tool: when the user needs a zero-downtime database migration plan. However, it does not explicitly state when not to use it or mention alternatives such as timps_migration_pilot, timps_db_agent, or timps_incident_responder, leaving comparative selection guidance unaddressed.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses the kernel's internal planning and routing behavior, which is useful. However, it does not describe the structure of the result, potential failure modes, side effects, or whether the operation is synchronous, leaving gaps in behavioral transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the action, and every sentence earns its place. The example is useful without being verbose, and there is no redundant content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has only two parameters and no output schema, the description covers the essential context: purpose, usage scenario, and internal behavior. However, it does not describe the shape of the structured result or how to effectively use the 'context' parameter, which leaves minor but non-critical gaps for an agent selecting and invoking the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema provides full descriptions for both parameters (goal and context) with 100% coverage. The description adds no additional parameter semantics beyond the example goal, which is already explicit in the schema. Thus, it meets the baseline but does not elevate understanding of the parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: delegating a multi-step goal to the TIMPS Agent Kernel. It explains that the kernel plans, routes to specialist agents, and returns a structured result, which distinguishes it from simpler task tools. However, it does not explicitly differentiate from siblings like timps_dispatch or timps_run_task, relying on the 'complex goals' example to imply the distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit usage guidance: 'Use for complex goals like...' with a concrete example. This gives a clear criterion for when to use the tool. It does not list alternatives or exclusions, but the implication that simple tasks are not appropriate is clear enough.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses a key behavioral guarantee: 'Logic is never changed — only documentation is added.' This is valuable context. However, with no annotations, the description carries the full burden; it does not mention whether the tool modifies files in place, returns output, or handles errors, leaving some behavioral aspects ambiguous.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, concise, and front-loaded with the main action. Every sentence adds value: the first defines the operation and formats, the second reassures about behavioral safety. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description is sufficient for a straightforward transformation tool with fully documented parameters. However, since there is no output schema, it would be helpful to explicitly state the return value (e.g., updated source code as a string) to fully round out the context. Still, the implied output is clear from the action.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and the description adds a bit of context by naming specific docstring formats (Google, Sphinx, NumPy, JSDoc, Doxygen) that map to the doc_style parameter. However, it does not provide additional semantics beyond the schema for language or source_code beyond basic clarity.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool reads raw source code and inserts production-quality docstrings, with specific format options. It distinguishes itself from sibling tools by focusing solely on docstring generation, not testing, code writing, or analysis.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage (when you need to add docstrings to code) but does not explicitly state when to use it versus alternatives, nor does it provide exclusions or caveats. There is no mention of when not to use it, which would be helpful for a tool among many similar code-related agents.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description bears the burden of explaining side effects. It lists planning and running activities, including a blameless retrospective template, but does not disclose any potential side effects, permissions, or safety guarantees. It reads as a safe facilitator, but that is not explicit.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that efficiently lists key elements without redundancy or filler. It packs significant detail (hypothesis, blast radius, rollback, comms tree, inject schedule, success criteria, retrospective) into a compact structure.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the specialized scope, the description covers the essential aspects of the tool's function. It names the key components of a game-day, which is sufficient context for an agent to decide if this is the right tool. No output schema exists, so no need to explain return values. Slight improvement would be clarity on what the tool produces or returns.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Both parameters have descriptions in the schema, providing 100% coverage. The tool description does not add additional meaning beyond those already clear descriptions (request as plain-English task, language as programming language). Thus it meets the baseline for high coverage without extra value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool's purpose: planning and running chaos-engineering game-days, with specific components listed (hypothesis, blast radius, rollback, etc.). This verb+resource combination is explicit and distinguishes it from the many sibling tools, which are mostly specialized for other domains.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for chaos-engineering game-days but does not explicitly state when to use this tool versus alternatives. No mention of conditions, exclusions, or comparison with other tools. It's clear enough but lacks direct guidance on when to choose it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations at all, the description must do all the work, and it discloses a concrete behavioral sequence: gather (Docker + app logs) → build (timeline) → generate (triage report), giving the name's "incident responder" actionable substance. It stops short of stating side effects (whether anything is mutated, written, or sent) — though for an analysis-oriented workflow, the described behavior strongly implies a read-only posture, so the gap is modest.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences (23 words) front-load the purpose and then walk through the workflow in order; the key differentiator ("triage report") is stated up front. Every clause earns its place, and no word is wasted.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a moderately complex, process-heavy tool with no output schema and no annotations, the description's three-step summary covers the main flow but omits side effects, access requirements, output format of the triage report, and any error behavior. It's adequate for an agent to attempt a first invocation but leaves real gaps for a production-incident workflow.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 50%: window_minutes is documented inline while repo_path is wholly undefined, and the description mentions neither parameter explicitly. The "timeline" language loosely hints at window_minutes' role and Docker/app logs imply repo_path points at source repositories, but the description adds no semantics beyond those weak inferences and fails to compensate for the undocumented repo_path.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
"Multi-source log correlation for production incidents" is a specific verb-resource pairing, and the clause "Gathers Docker + app logs, builds a timeline, and generates a triage report" lays out a concrete three-stage pipeline. This level of specificity (sources, intermediate artifact, deliverable) effectively differentiates it from nearby siblings like timps_log_interpreter and timps_incident_response_coordinator, even without naming them.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
"For production incidents" supplies clear context that this tool belongs in incident workflows, but no alternatives, exclusions, or when-not-to-use guidance is given. An agent gets no help choosing between this and the many log/incident siblings beyond the implied fit, so usage is only implicitly conveyed.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden of explaining the tool's behavior. 'Check the status' implies a non-mutating query, and 'previously delegated' clarifies the expected run origin, but the description does not disclose output format, possible states, or whether the operation is non-blocking.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that directly conveys the tool's purpose and key parameter provenance. No filler or redundant information is present.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple status-check tool with one parameter and no output schema, the description is largely complete. It could be enhanced by noting what statuses are possible or whether it can be polled, but the basic use case is clear.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already covers the single parameter with 100% description coverage. The description adds marginal value by linking the run_id to a previously delegated kernel run, but it does not provide meaningful semantics beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Check the status') and the resource ('a previously delegated kernel run'), with the key parameter run_id. It distinguishes itself from delegation tools by focusing on status retrieval, though it does not explicitly compare itself to sibling status-like tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'previously delegated kernel run' provides clear contextual guidance that this tool should be used after timps_delegate. It does not mention exclusions or alternatives, but the usage context is understandable for an AI agent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It does disclose the scan scope and produced artifacts (report, compatibility matrix), which is useful behavioral context. However, it does not mention whether the operation is read-only, requires network/package-manager access, or what side effects or limitations exist.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, information-dense sentence with no filler. It front-loads the main action, lists the relevant license categories, and names the deliverables—every clause earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple 2-parameter tool with no output schema, the description covers the core action, input scope, and expected outputs. It could be more complete with explicit safety/read-only notes or usage alternatives, but it is sufficiently self-contained for an agent to understand the tool's role.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%: both 'request' and 'language' are already described clearly in the input schema. The description itself adds no parameter-specific meaning, which is acceptable given the baseline for full schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Scan'), identifies the resource ('source + manifests'), and names the exact output ('per-dependency report', 'copyleft-compatibility matrix'). It clearly differentiates this tool from siblings like sbom_generator or compliance_auditor by focusing on OSS license types and distribution-model compatibility.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the use case—scanning source and manifests for OSS license compliance—but does not explicitly state when to use this tool versus alternatives, nor does it mention exclusions or prerequisites. The context is understandable but not explicitly guided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses the core behavior: reads logs, extracts stack traces, explains crashes, and classifies causes. However, it does not clarify behavior when log_path is omitted, whether it accesses live system logs autonomously, or any permissions/failure modes. This is moderate transparency for a read/analysis tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the primary capabilities, and ends with a clear invocation instruction. There is no filler or redundant repetition of the tool name; every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
This is a simple tool with one optional parameter and no output schema. The description covers purpose, classification logic, and how to invoke it. The only meaningful gap is the ambiguity around behavior when log_path is absent—since the parameter is optional, the agent may not know whether calling without arguments is useful or what logs are read by default. Overall, it is sufficiently complete for the tool's complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% for the single parameter, so the schema already documents log_path. The description only restates 'Pass a log file path' without adding syntax, accepted formats, file globbing, or default behavior. Baseline 3 is appropriate since the schema handles the parameter semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses specific verbs tied to a clear resource: 'Read crash logs and system logs', 'extract stack traces', 'explain each crash in plain English', and 'Classifies as app bug / OS bug / hardware / user error'. It distinguishes this tool from log-related siblings like timps_log_detective and timps_log_pattern_analyzer by emphasizing crash explanation and root-cause classification.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The only usage guidance is 'Pass a log file path to analyse a specific log', which implies when a specific log needs analysis. There is no explicit comparison to alternatives, no when-not-to-use guidance, and no mention of what happens if no path is provided. This is implied usage rather than clear scheduling rules.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must convey the tool's side effects. It mentions 'scaffold' which implies creating a new project (potentially generating files in the current workspace), but doesn't explicit state that it writes files or that it might overwrite existing ones. This is a gap in transparency for a generative tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that packs a lot of information: the action (scaffold), the target (MCP server), and the list of deliverables. No fluff or redundancy, making it easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (2 simple params, no output schema), the description is mostly sufficient. It states the tool's purpose and output artifacts. However, it could have added a note on the typical end result (e.g., a runnable server) or any limitations (e.g., only Python supported). But since it's generically about scaffolding, the current level is adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already describes both parameters: 'request' as 'Plain-English task or context' and 'language' as 'Primary programming language (default: python)'. The schema coverage is 100%, so the description doesn't need to add much. However, it could hint that the 'request' should be detailed enough to define the server's scope, but it doesn't. Still, given the high schema coverage, the baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: it scaffolds a complete MCP server. It lists the specific components (tools, resources, prompts, server.py, pyproject, smoke-test client, README) that will be generated, which is specific enough to distinguish it from the many sibling tools that handle other tasks like 'run', 'organize', or 'optimize'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is for creating a new MCP server, which is a distinct use case from the siblings. However, it provides no explicit cues about when to choose this tool over alternatives (e.g., when you need a new server vs. modifying an existing one). It doesn't mention any prerequisites or expected context (e.g., whether the request should contain a detailed spec).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry the full burden. It states the output format (structured summary with owners/deadlines) and that it returns data, but does not disclose behavior for messy/empty transcripts or how it handles missing owner information. It is transparent about the core operation but lacks edge-case detail.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loads the primary action, and wastes no words. Every word contributes meaning, making it highly efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple 2-parameter tool with no output schema, the description adequately explains the input (meeting transcript) and the structured output (action items, decisions, open questions with owners/deadlines). It could be more explicit about the exact return format, but it is sufficient for an agent to select and invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already provides complete descriptions for both parameters (transcript, attendees) with 100% coverage. The description adds no additional parameter-level context beyond what the schema states, so baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Extract') and names the resource ('meeting transcript') plus the exact outputs ('action items, decisions, and open questions'). It clearly distinguishes this tool from siblings by its unique function of condensing meetings into structured summaries.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is used when you have a meeting transcript and need action items, but provides no explicit when-to-use vs. alternatives or exclusions. It lacks statements like 'Use this instead of X when...'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full responsibility. It mentions 'Analyse' and 'Returns a checklist', which suggests read-only behavior, but it doesn't explicitly state whether the tool modifies code, requires network access, or performs side effects. This lack of explicit transparency about side effects is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise (two sentences) and well-structured, with no unnecessary detail. It efficiently conveys the core functionality and output.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema, the description adequately explains the return value (step-by-step checklist) and the input factors (target upgrade, codebase). It lacks explicit mention of prerequisites or external interactions, but the core use case is covered sufficiently.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Only 'goal' has a description with an example; 'repo_path' lacks a description. The tool's description mentions 'codebase', which gives some context for repo_path, but it's not fully specified. Schema coverage is partial at 50%, and the description adds moderate value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: analyzing a codebase for breaking-change APIs in the context of a library/framework upgrade. It also specifies the output (step-by-step migration checklist), making it distinct from siblings like timps_db_migration_pilot.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use it ('given a target library/framework upgrade') and what it does (identify breaking changes). It doesn't explicitly exclude alternative tools, but the scenario is clear enough.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden. It discloses the generation of a fix script with specific commands (DNS flush, WiFi reset, DHCP renewal), which is a significant behavior. However, it doesn't clarify whether the script is auto-executed or just generated, and potential side effects (e.g., network disruption) are not mentioned.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences covering both diagnostic actions and the output (fix script). No filler, front-loaded with the primary purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the single optional parameter and no output schema, the description covers the main actions and the delivered artifact. Minor gap: doesn't mention prerequisites (e.g., admin rights for network changes) or whether the script is meant to be reviewed before running.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% for the single parameter 'target' with a clear description and default. The description mentions ping/traceroute which implicitly relates to the target, but adds no additional meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses specific verbs and resources ('Diagnose network problems: ping internet/Cloudflare, traceroute, open ports') and clearly distinguishes itself from sibling tools by focusing on network diagnostics with a concrete fix-script generation outcome. It's unambiguous and actionable.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
It implies when to use it (network issues) but doesn't explicitly say when not to use it or compare to siblings like timps_full_checkup or timps_environment_doctor. No exclusions or alternative recommendations are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It discloses that it produces a report and rewrites, which is a behavioral output. However, it does not mention whether the operation is read-only, if it modifies any existing resources, or any side effects. The word 'scan' suggests read-only but it's not explicit. It also doesn't describe limitations or prerequisites.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, compact and front-loaded with the action verb 'Scan'. Every clause adds value, naming inputs (prompts, system messages, tool schemas) and outputs (report, rewrites). No fluff or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's specialized nature and absence of output schema and annotations, the description provides enough context to understand its core function and outputs. It names the specific attack vectors and result types. However, it doesn't specify the return format or any detailed structure, which might be needed for a complex security scanner, but the key behavioral outputs are stated.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and both parameters have descriptions, so baseline is 3. The description does not add any meaning about how 'request' and 'language' relate to the scanning process. The schema descriptions themselves are vague (e.g., 'Plain-English task or context') and the tool description does not clarify that the request likely contains the prompts to scan. No added value beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool scans prompts, system messages, and tool schemas for prompt-injection/jailbreak/data-exfiltration risks, and specifies concrete outputs ('severity-rated report and hardened prompt rewrites'). This is a specific verb+resource+output combination that distinguishes it from broader security tools like timps_security_guard or timps_ai_safety_agent.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for prompt-injection scanning but does not explicitly state when to prefer this tool over the many sibling security tools (timps_ai_safety_agent, timps_red_team_agent, timps_threat_intel_analyst). No clear exclusions or alternatives are mentioned, leaving the agent to infer selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It states the tool 'generates' a report, implying a non-destructive read/transform operation. However, it does not disclose details like whether it modifies any data, requires authentication, or has rate limits. The description is adequate but not rich in behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that front-loads the purpose and lists the key inputs and output. Every word earns its place, with no fluff or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (4 flat parameters, no output schema, no nested objects), the description is complete enough. It explains the transformation (task lists to markdown standup) and the required inputs. The only minor gap is not specifying the exact format of the markdown output, but that is not critical for a simple report generator.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all four parameters. The description adds context by explaining the overall purpose (e.g., 'completed tasks' maps to the 'completed' parameter) but does not add syntax or format details beyond what the schema provides. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Generate a formatted daily standup report from task lists.' It specifies the input types (completed tasks, in-progress items, blockers) and the output (polished markdown standup). This distinguishes it from sibling tools like timps_sprint_planning_agent or timps_meeting_condenser, which have different purposes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use it (for daily standup reports) but does not explicitly state when not to use it or mention alternatives. It provides clear context for the use case but lacks explicit exclusions or alternative tool references.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It does reveal the core behavior—ingesting feeds and producing a brief with detection rules and mitigations—but it does not disclose whether network access or credentials are needed, whether any files are written, whether external sources are fetched in real time, or the response format. These are notable transparency gaps, but the described behavior is clearly non-destructive in intent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The entire description is one tightly written sentence that names the data sources, the action, and the expected deliverables. Every word contributes value and there is no repetition of schema or annotation details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple agent-style tool with two optional parameters and no output schema, the description is mostly complete: it identifies the inputs to ingest, the analytical focus, and the final deliverable. It could be stronger by specifying the expected brief structure or any limits of the analysis, but it is sufficiently contextual for an AI agent to select and invoke it meaningfully.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already describes both parameters clearly: 'request' is the plain-English task and 'language' specifies the primary programming language. The description adds no extra parameter nuance, such as how 'language' affects the generated detection rules or whether 'request' should include organization-specific context. With 100% schema description coverage, the baseline is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states a specific action and scope: ingest threat feeds from CVE, MITRE ATT&CK, and CISA KEV, and produce a threat brief with detection rules and prioritized mitigations. This transparently distinguishes it from related security sibling tools by naming the exact sources and deliverables.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool should be used for threat-intelligence ingestion and brief generation, but it does not explicitly state when to use it instead of related tools such as timps_incident_responder or timps_security_remediation. No alternatives, prerequisites, or exclusions are mentioned, so usage guidance is inferred rather than prescribed.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of disclosing behavior. It mentions 'safety guardrails' but does not elaborate on what those are, whether the tool is read-only, or what kind of output format to expect. It also doesn't state if any external data sources or permissions are needed. The description adds some context about the nature of the output (coaching plan) but lacks deeper behavioral specifics, scoring a 3.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence. It front-loads the action and lists the specific data types, then states the intended output. There is no redundancy or fluff; every part contributes to the tool's purpose. This is a model of conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (interpreting multiple data types and generating a coaching plan) and the absence of an output schema, the description is too sparse. It does not specify the format of the coaching plan, how the 'request' parameter provides or requests data, or how the language parameter influences output. The mention of 'safety guardrails' is vague. The description needs more detail to fully prepare an agent, so a 2 is appropriate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description covers 100% of the parameters, so the baseline is 3. The tool description adds no additional meaning about how 'request' or 'language' are used; it doesn't clarify how the plain-English request maps to the wearable data or how the language parameter affects the plan. Since the schema already describes the parameters, and the description adds nothing extra, a 3 is warranted.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: it interprets specific wearable data types (HRV, sleep, RHR, steps, SpO2) and produces a coaching plan. The verb 'interpret' is specific, the resource is well-defined, and the output is explicit. It clearly distinguishes itself from the many other timps_* tools by focusing on health coaching.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear context on when to use the tool—whenever wearable/fitness data needs interpretation—by listing the data types it handles. However, it does not explicitly mention alternatives or exclusions, though the tool's specialty is obvious among the large set of siblings. The guidance is more implied than explicit, so a 4 is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses the analysis scope and outputs, implying a read-only mapping activity, but it does not explicitly state whether the tool modifies anything, whether it requires credentials or special access, or how the evidence pack and gap report are returned. Some behavioral context is present, but significant gaps remain.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that states the action, scope, target standards, and expected deliverables without unnecessary words or repetition. Every element contributes to understanding.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a multi-framework compliance audit tool with no output schema and no annotations, the description covers the core purpose and outputs but omits practical details like what a request should contain, how deep the scan goes, expected runtime, or prerequisites. It is minimally adequate but leaves the agent to infer important operational context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with both 'request' and 'language' already explained in the input schema. The description does not add additional parameter-level detail, so it neither helps nor hurts; baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description uses a specific verb ('Map') with a clear resource ('codebase + infra config') and explicit deliverables ('evidence pack and gap report'). It also names the target frameworks (SOC 2 / ISO 27001 / HIPAA / PCI-DSS / GDPR), which clearly distinguishes it from sibling security, remediation, and single-framework compliance tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description makes the intended use case clear: when an agent needs to map a codebase and infrastructure against common compliance standards and produce an evidence pack and gap report. It does not explicitly name alternatives or exclusions, but the framework list and output format give strong contextual guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavior itself. It says the tool 'produces' artifacts (SQL, ER diagram, etc.), which implies generation rather than execution, but it does not specify the output format, error handling, or whether any actions are taken on a database. The pairing with sql_injection LoRA adds context but does not substitute for deeper behavioral clarity.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded with purpose, followed by a clear enumeration of outputs. The closing sentence about the sql_injection LoRA is useful but not strictly necessary. It is well-structured without being verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is fairly complex, producing multiple outputs (DDL, ER diagram, migrations, query templates), and there is no output schema. The description captures the core functionality effectively, but it would be more complete if it described the structure of the returned result or how the outputs are delivered. Still, the main use case is well covered.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all four parameters. The description mentions the data model description and migration tool, but does not add meaningful detail beyond what is in the schema. Therefore, the baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's role via 'DB Agent — schema design, query optimisation, and migration scripts' and elaborates with a concrete list of outputs from a data model description. This distinguishes it from sibling tools like timps_sql_optimizer and timps_db_migration_pilot by covering the full schema design and migration workflow.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description strongly implies when to use: 'Given a description of your data model it produces...' and lists the scenarios (schema design, query optimisation, migration scripts). However, it does not explicitly mention alternatives or exclusions, so it stops short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so description must handle transparency. It says 'run it immediately' implying execution but doesn't disclose side effects, potential dangers, or whether it may trigger destructive actions. Lacks details on error handling or what happens after dispatch.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences plus examples, zero filler. Front-loaded with action and usage guidance, ideal for quick reading.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Adequate for a simple one-parameter dispatcher: states what it does and when to use. However, lacks discussion of output, asynchronous behavior, or limitations like inability to detect certain requests. Given no annotations or output schema, could be more thorough.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema already describes 'request' as 'plain-English request or complaint', and description repeats that and adds concrete examples. This provides practical context beyond schema, enriching parameter understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clear verb 'auto-detect' and resource 'best TIMPS agent', explicitly states it runs the agent. Distinguishes from sibling agents by being the dispatch mechanism. Examples reinforce purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says 'Use this when unsure which agent to pick', providing a direct decision criterion. Includes examples of typical requests but doesn't clearly state when not to use it or mention alternatives beyond 'which agent to pick'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry the behavioral transparency burden. It discloses the tool's high-level actions (flagging, drafting, identifying newsletters) and any implied non-sending behavior, but it does not clarify whether it actually sends drafts, modifies emails, requires authentication, or returns a summary. This is adequate but leaves meaningful ambiguity.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two focused sentences. The first sentence front-loads the core purpose and deliverables; the second sentence gives the input instruction. There is no filler or redundant explanation.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description provides a clear high-level contract for a moderately complex analysis tool, but it lacks return-format details and side-effect information. Since there is no output schema and no annotations, the description would benefit from stating whether the result is a list of flagged emails, drafted reply text, or a combined triage summary. Still, the core use case is sufficiently communicated.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description reinforces that emails must contain 'from', 'subject', and 'body', which matches the schema, but it adds no new information about format, constraints, or semantics beyond what the schema provides. The optional context parameter is not addressed in the description, though the schema covers it.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Begins with a strong, specific verb 'Triage' and clearly identifies the resource ('a batch of emails'). It enumerates concrete sub-actions (flag urgent ones, draft routine replies, identify newsletters), which sharply distinguishes it from sibling tools focused on tasks, dispatch, or system maintenance.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly states when to use it: when you have a batch of emails to triage. It also specifies the required input shape. It does not explicitly discuss alternatives or when not to use it, but within the sibling context none of the other tools obviously compete for this email-triage scenario.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must carry the behavioral burden. It discloses the core analytical workflow and supported input formats, but it does not mention whether the tool is read-only, what the output structure looks like, or any limitations/edge cases. This is adequate but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, both purposeful. The first sentence front-loads the tool's primary actions, and the second adds input-format context. There is no redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is a two-parameter analysis helper with a clear purpose and complete schema coverage, but it lacks explicit usage guidance relative to sibling log tools and does not describe expected output or side-effect behavior. Given no output schema, the description would benefit from at least a brief mention of what the returned analysis looks like.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline is 3. The tool description adds meaningful value by specifying accepted log formats ('stack traces, JSON logs, syslog, and journald output'), which clarifies what the 'logs' parameter can contain beyond the schema's generic 'Raw log output' phrasing. The 'service' parameter is not enhanced beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb phrase ('Cluster production log errors, identify root cause, and suggest a fix') that names both the resource (log errors) and the expected outcome. It is clearly distinguishable from sibling log tools by focusing on clustering, root cause analysis, and remediation suggestion.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use the tool (when you have production log errors that need clustering and root-cause analysis) via the opening phrase. However, it does not explicitly state when not to use it or contrast it with nearby siblings like timps_log_interpreter or timps_log_pattern_analyzer, leaving the selection guidance implicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It describes the generation outcome in detail and implies that the tool creates new content rather than mutating existing data. However, it does not mention whether any input is required from the user, what happens with the generated notes, or any side effects/assumptions about the environment.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
One sentence with strong front-loading: existing Tool purpose, source, and deliverables. Every item listed serves the description; no wasted words or irrelevant details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a text-generation tool, the output deliverables are fully enumerated, which is valuable absent an output schema. However, the tool has no annotations, no required parameters, and an oddly unrelated 'language' default; the description does not explain the required parameter contract match to the input context, leaving the tool slightly incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline is 3. The description does not add semantics about how `request` should be structured or that the transcript must be supplied there. It also does not clarify whether the `language` param refers to the podcast language or something else, so the description offers little added parameter guidance.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('turn') and explicitly names the resource ('podcast transcript / outline') and target output ('SEO-friendly show notes'), then enumerates the expected elements. This makes the tool's purpose unmistakable and differentiates it from other writing-related sibling tools like demo_video_script_writer or tech_writer_assistant.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description states the input context clearly: use when you have a podcast transcript or outline and want show notes. It does not explicitly say when not to use it or mention alternative siblings, but the context is specific enough to guide selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses inputs and outputs ('Returns a semver recommendation and a migration guide') and implies a read-only diff operation, but it does not state side effects, limitations, or behavior on invalid or mismatched specs. Adequate but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences, front-loaded with the primary action and followed by valuable output details. Every word earns its place; no filler or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a low-complexity analysis tool with no output schema, the description sufficiently covers what the tool does and what it returns. The only minor gap is not clarifying handling of format mismatches or invalid specs, but the schema covers required inputs and the default format.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents old_spec, new_spec, and format. The description adds no parameter-level details beyond what the schema provides, matching the baseline of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Diff') and resource ('two API specs'), identifies supported formats (OpenAPI/AsyncAPI), and names concrete outputs (breaking changes, deprecations, safe additions, semver recommendation, migration guide). This clearly distinguishes it from siblings like api_security_tester or contract_reviewer.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description makes the usage context clear: comparing two API specs and assessing contract compatibility. It does not explicitly name alternatives or exclusions, but the purpose is unambiguous enough for an agent to know when to invoke it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations present, the description carries the full behavioral burden. It does disclose a meaningful trait—that the tool comes 'with a runnable test harness'—which hints at code generation behavior. However, for a security-audit tool that may probe live endpoints, the description is silent on side effects (e.g., whether it sends harmful requests, requires auth tokens, or has rate limits). An agent deciding whether invocation is safe lacks critical context here.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
A single, well-constructed sentence that front-loads the verb and payload, uses an em-dash list for scannability, and ends with the key differentiator ('with a runnable test harness'). Every clause carries meaning—no filler, no repetition of the name.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with only 2 simple, well-documented parameters and no output schema or nested objects, this description provides sufficient context: what it audits, against what standard, with what inputs, and one key output trait (runnable harness). It's slightly light on what the tool returns (test report? generated files?), but given the low complexity, it's nearly complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%—both 'request' and 'language' have descriptive inline help ('Plain-English task or context for the agent', 'Primary programming language (default: python)'). The description's 'runnable test harness' hints at the language parameter's role in code generation but doesn't go beyond what the schema already conveys. Baseline 3 is appropriate since the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb+resource combination ('Run an OWASP API Security Top-10 (2023) audit...against an OpenAPI spec or live endpoint') and enumerates concrete vulnerability classes (broken auth, BOLA, mass assignment, rate-limit, SSRF, injection), distinguishing it from the many sibling tools. This clearly separates it from related tools like timps_security_guard and timps_red_team_agent, which remain generic by comparison.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context on when to use the tool—when an OWASP API Top-10 audit is needed—and even specifies acceptable inputs ('against an OpenAPI spec or live endpoint'). However, it doesn't reference any alternatives or exclusion criteria (e.g., when to prefer timps_red_team_agent or timps_security_guard instead), so it stops short of a full 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses key behaviors like intelligent decomposition, concurrent execution, and aggregation. However, it omits details on failure handling, mutation of files, safety implications, or resource usage, making it adequate but not comprehensive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two concise sentences plus examples. It is front-loaded with the core action, contains no fluff, and every sentence contributes to understanding the tool's purpose and usage.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (parallel sub-agents) and lack of output schema or annotations, the description provides a solid high-level overview: purpose, usage, and examples. It could mention potential side effects (e.g., file modifications) or error handling, but for deciding when to use the tool, it is largely complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 100% coverage with clear descriptions for all 5 parameters. The description adds minimal extra value beyond listing examples of instructions and agent types; it doesn't elaborate on parameters like max_parallel or dry_run. Since the schema already does the heavy lifting, a baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: decompose bulk tasks into parallel sub-tasks, execute concurrently, and return aggregated results. The examples ('add tests for all handlers', 'review all API endpoints') make the purpose concrete and distinguish it from single-task tools like timps_unit_test_writer.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit guidance: 'Use this to do the same operation across many files at once' with concrete examples. It implies when to use the tool effectively, though it does not explicitly state when not to use it or mention alternative tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are supplied, so the description carries full responsibility. It discloses that the tool creates structure, stub files, and runs setup commands, which suggests a mutating operation. However, it omits potential side effects like overwriting existing files, requiring specific permissions, or the exact nature of the 'setup commands' (e.g., package installation, shell execution).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The entire description is a single, front-loaded sentence with the main action first and supporting details after the colon. Every word earns its place; there is no redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple two-parameter tool with no output schema, the description adequately covers what it does and what the agent should provide. It falls short only in not describing the result/return value or any post-scaffold steps, but this is a minor gap given the straightforward nature of the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already provides 100% description coverage for both parameters (request and language). The description adds context by restating 'describe what you're building' and implying language flexibility, but it doesn't offer additional meaning beyond the schema's own parameter descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Scaffold') with a clear resource ('new project') and enumerates the deliverables (folder structure, stub files, setup commands). It clearly distinguishes this tool from siblings by focusing on project generation rather than management, optimization, or monitoring.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides clear context for when to use: when scaffolding a new project. 'Supports any language or framework — describe what you're building' tells the agent exactly what input to provide. It doesn't mention alternatives or exclusions, but no sibling seems to perform the same role, so explicit differentiation isn't necessary.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It explains the transformation from long-form to multiple short-form formats but does not disclose details such as output structure, how tone affects results, or whether all listed formats are always generated. This is a minor gap for a content transformation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence that front-loads the primary action and quickly enumerates the output formats. Every word is purposeful with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with two params and no output schema, the description provides sufficient context: it clarifies input (long-form technical post) and expected outputs (five specific formats). However, it could be slightly more complete by confirming that all formats are produced or indicating how the tone parameter influences the output, but this is not critical.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with both 'content' and 'tone' documented in the input schema. The description does not add extra parameter semantics beyond the schema, so the baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function with a specific verb (Transform) and resource (long-form technical post), listing concrete output formats (tweet thread, LinkedIn post, etc.). This distinguishes it from sibling tools by focusing on content repurposing.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly implies when to use this tool: when you have a long-form technical post and want to create short-form content. However, it does not explicitly mention alternatives or situations where another tool would be more appropriate, so it lacks a 'when not to use' clause.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description is the sole source of behavioral info. It discloses that it returns a scorecard and redline, but does not state whether the operation is read-only, requires any permissions, or has side effects. For a 'reviewer' tool, safety is implied but not explicit, which is a moderate gap given the absence of annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence that front-loads the primary action (review a contract) and lists specific red-flag categories, followed by a clear output statement. Every phrase adds value, with no redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has no output schema, so the description must explain return values; it mentions 'clause-by-clause scorecard and a redline' but lacks detail on the structure or format. It also doesn't explain how the contract is provided (presumably via the request parameter). Overall, it gives a solid overview but could benefit from more specifics on inputs and outputs.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description does not add extra meaning to the parameters, but it doesn't need to since the schema adequately describes 'request' and 'language'. However, the 'language' parameter seems irrelevant to contract review and is unexplained in the description, slightly reducing clarity but not enough to drop below baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: review contracts (MSA, NDA, SaaS, vendor agreement) for specific red-flags (indemnification, liability caps, IP, data, termination, SLAs) and returns a clause-by-clause scorecard and redline. This is a specific verb+resource with concrete scope, distinct from generic tool descriptions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context by listing contract types and red-flag areas, but does not explicitly say when to use this tool vs. alternatives (e.g., timps_api_contract_auditor or timps_license_compliance_scanner). There are no exclusions or alternative recommendations, but the context is clear enough for likely use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full transparency burden. It discloses what the tool returns (a structured brief with specific legal components) and its research-only scope, but it does not explain how the judgment text should be supplied, whether the tool retrieves cases itself, or any limitations such as hallucination risk or citation reliability.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the core action, and every clause adds value: the resource, the output components, and the legal-research caveat. There is no filler or redundant repetition of the tool name.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description does a good job of specifying the expected output structure and domain boundary. It could be more complete by describing how to pass the judgment text and what the structured brief looks like, but it is substantially more complete than a minimal description for this domain.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already describes both parameters, and coverage is 100%, so the baseline is 3. The tool description does not add further meaning to 'request' or 'language'; notably, 'language' (with default python) appears mismatched for a legal summarizer and is left unexplained.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb (Summarise) and names the exact resource (court judgment / order), then lists concrete output components: bench, facts, issues, holdings, reasoning, ratio, and citations. It also distinguishes its purpose via 'For legal research, not legal advice,' making it clear among a large set of sibling tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly sets the intended context ('For legal research') and an explicit exclusion ('not legal advice'). However, it does not name alternative tools or provide explicit when-to-use versus when-not-to-use guidance beyond that single boundary.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It does disclose the return values (cleaned records, quality score, SQL insert hint), which is helpful, but it does not explicitly state side effects or safety profile (e.g., whether it's read-only). It lacks details on how 'normalise' works or any error conditions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: two short sentences. It front-loads the core action and supported formats, then lists the outputs. Every word earns its place, with no redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the moderate complexity and absence of an output schema, the description adequately explains what the tool does and what it returns. It covers input formats and output components, but could be more detailed about the exact structure of 'cleaned records' or the quality score. Still, it is sufficient for an agent to select and invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all parameters. The description adds some context by listing input formats and mentioning the SQL insert hint, which relates to target_schema, but it does not significantly enhance understanding beyond the schema. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('Clean and normalise') and resource ('messy data'), and lists concrete input formats (CSV, JSON, PDF extracts, copy-pasted tables). It also distinguishes itself from siblings like timps_data_pipeline or timps_dataset_agent by focusing on data cleaning and normalization.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context on when to use the tool: when you have messy data in formats like CSV, JSON, PDF extracts, or copy-pasted tables. It does not explicitly mention alternatives or exclusions, but the context is clear enough for an agent to infer appropriate usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description's verbs (predict, identify, warn) suggest a read-only, advisory tool, but it never explicitly states that it will not delete or modify files, what the warning mechanism is, or whether any side effects (e.g., notifications) occur. With no annotations to declare safety, the description takes full responsibility but leaves some behavioral ambiguity.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is one sentence, front-loads the core capabilities, and contains no waste. Every clause adds information, and the structure is easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given a zero-parameter, no-output-schema tool, the description gives a reasonable high-level overview of what the tool accomplishes. It is somewhat general and does not define the output or warning format, but for a no-input analytical agent, it is mostly complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so there is no parameter semantics to convey. A baseline score of 4 is appropriate because no parameters need explanation and the description does not introduce unnecessary parameter-related content.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's specific purpose: predicting disk usage trends, identifying safe cache directories to prune, and warning about impending no-space events. The resource (disk space) and three distinct actions are explicit, distinguishing it from broader sibling tools like timps_system_optimizer or timps_privacy_cleaner.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for disk-space planning and safe cache cleanup but provides no explicit guidance on when to use it versus alternative tools. It does not mention exclusions, prerequisites, or scenarios where another tool (such as timps_privacy_cleaner or timps_system_optimizer) would be preferred.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It does disclose key behavioral outputs (license, label, additive, claim checks, checklist). However, it omits limitations, caveats, or information about how the agent handles ambiguous requests, making the transparency adequate but not outstanding.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence with a clear verb and enumerated scope. Every phrase earns its place, with no padding or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and no annotations, the description does a good job of naming both assessment categories and the final deliverable. It is sufficiently detailed for an agent to select and tune the task, though it could be enhanced with how the request should be phrased or what optional details the agent may accept.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% since both 'request' and 'language' have descriptions. The tool description adds no parameter-specific meaning beyond the schema, so the baseline of 3 is appropriate; the parameter semantics are adequately documented but not enhanced by the description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the tool's specific function: assessing F&B products/packaging against India's FSSAI regulations. It lists concrete deliverables (license type, label checklist, additive and claim restrictions, submission-ready checklist), which distinguishes it from the many sibling compliance tools like timps_gst_compliance or timps_dpdp_act_auditor.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies a clear use case: when an F&B product/packaging needs FSSAI compliance assessment. It does not explicitly state when not to use the tool or name alternatives, which is a minor gap, but the domain-specific wording effectively guides the agent toward the right context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It explicitly states 'dry-run' for ffmpeg commands and that it 'suggests' a rename plan, implying non-destructive actions. This is transparent about the tool's behavior without needing annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no fluff. It packs action, scope, and outputs efficiently, making every word earn its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With only one optional parameter and no output schema, the description adequately conveys the tool's purpose and deliverables (plan, commands). It covers what users need to know for invocation, though it doesn't elaborate on the return format or edge cases, which is acceptable given simplicity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, with the single 'path' parameter already described as optional with default directories. The description adds no extra param details but the schema already documents it fully, meeting the baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description uses specific verb 'Scan' with explicit resources (Photos, Downloads, Desktop) and clearly states the outcomes: identifying media chaos types, suggesting rename plans, and generating ffmpeg commands. It distinguishes itself from sibling tools like timps_file_organizer by focusing on media-specific issues.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use (scanning media directories) but does not explicitly say when not to use or mention alternatives. It lacks exclusions or comparisons to similar tools, though the context is fairly clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the transparency burden. It clearly states the tool returns workflow JSON plus a visual description of every node, and that it 'knows' nodes/integrations/expression syntax, making its non-executing generator nature evident. It could mention limitations like credential handling or workflow deployment, but the core behavior is disclosed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences, front-loaded with the main purpose, and every sentence adds value: what it does, what it knows, and what it returns. No filler or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a 3-parameter generator tool with no output schema, the description covers the input style, tool capabilities, and return format. It is sufficiently complete for an agent to select and invoke it, though it could optionally add caveats about output size or credential/config requirements.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema already documents all three parameters. The description adds framing by explaining the tool converts a plain-English task description, but it does not add meaningful syntax, relationship, or behavioral detail beyond the schema. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('converts') and resource ('plain-English task description into a complete, importable n8n workflow JSON'), making the tool's purpose unmistakable. It also distinguishes this tool from the many sibling agents by clearly focusing on n8n workflow generation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use it—whenever an n8n workflow needs to be generated from a natural-language task—but it does not explicitly state when not to use it or mention alternatives such as timps_ai_workflow_orchestrator. This is adequate but lacks explicit exclusion guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description bears full burden for behavioral disclosure. It mentions that the tool 'returns' a structured review, implying it is a read-only analysis, but does not explicitly state side-effect-free behavior, async processing, or any rate limits. It adds core behavioral context (output format), so a 3 is appropriate, not a 2, because it at least signals a non-mutating operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the purpose and outcome, and contains zero filler. Every word adds value: what the tool does, what it reviews, and what it returns.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that no output schema exists, the description compensates partially by naming the score range and verdict type, but the 'structured review' is not elaborated (e.g., fields, categories). For a tool with only two parameters, this is fairly complete, and the output summary covers the most important return aspects, so a 4 is appropriate rather than a 5.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% (both `diff` and `style_guide` have clear descriptions). The tool description adds minimal extra meaning beyond restating the purpose and output; the schema already explains parameters adequately. Per the baseline rule, a 3 is correct when the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states a specific verb ('Review') and resource ('pull request diff'), and adds outcomes ('blockers, suggestions, and nitpicks', '0-10 score', 'approve/reject verdict'). This distinguishes it from sibling review tools like terraform_plan_reviewer or contract_reviewer, which focus on different artifact types.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
It implicitly indicates when to use the tool (when you have a pull request diff ready for review) and what it outputs, but does not explicitly state exclusions or alternatives. No sibling appears to duplicate this exact capability, so the lack of an explicit alternative reference is acceptable but leaves room for improvement.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It mentions creating a runnable eval harness and improvement plan, implying file/system changes, but does not disclose potential side effects (e.g., modifying files, installing dependencies) or any required permissions. This is a moderate gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, dense sentence that front-loads the primary purpose (RAG evaluation) and then lists key metrics and deliverables. It is concise without unnecessary words, making it easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description mentions the evaluation aspects and outputs (harness, improvement plan), but does not elaborate on how the harness is delivered or any prerequisites. While not exhaustive, it gives enough context for typical usage, and there is no output schema to detail further.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already provides coverage for both parameters (request and language) with descriptions. The tool description does not add extra semantics beyond the schema, so the baseline of 3 applies given high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: running a RAGAS-style evaluation of a RAG pipeline, specifying key metrics (context precision/recall, faithfulness, answer relevance, MRR/NDCG). It distinguishes from siblings by focusing on evaluation rather than design or other tasks.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for evaluating RAG pipelines and mentions delivering an improvement plan, but does not explicitly state when to use it versus alternatives (e.g., when to pick this over other RAG tools). It is clear but could be more direct about the situation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears the full burden. It does describe the sources searched and the return format (structured brief with findings, gotchas, approach, sources), but doesn't disclose potential side effects, permissions, rate limits, or error behavior. For a read-only research tool, this is adequate but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences: the first states the purpose and timing, the second describes the return value. No wasted words and front-loaded information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given it has a simple input schema (3 params, all covered) and no output schema, the description adequately covers the return structure. It doesn't mention timing or async behavior, but for a research tool that returns a brief, it's sufficiently complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, meaning all parameters (topic, depth, sources) already have descriptions in the schema. The tool description adds no additional meaning beyond what's in the schema, so a baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the tool as a research agent that runs before coding tasks, searches multiple sources (documentation, GitHub issues, Stack Overflow, web), and returns a structured brief. The verb 'research' and explicit resource scope distinguish it from other agents, though it shares similarities with deep_research_agent but here the differentiation is enough.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
It states it runs 'BEFORE any coding task' and mentions it gathers context for downstream agents, implying it's a prerequisite step. However, it doesn't explicitly compare to alternatives like deep_research_agent or research_scout, but the general usage context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden. It discloses that the tool returns findings and commands, suggesting a read-only reporting behavior, but it does not mention required permissions, potential side effects of port scanning, or whether it modifies anything. This is moderate transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single well-structured sentence, front-loaded with 'Security scan', then listing scan targets and output. Every phrase adds value with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter tool, the description covers the core aspects: what is scanned, what is returned, and even a platform note (macOS TCC). It lacks caveats about prerequisite privileges or limitations, but overall provides enough context for an agent to invoke it appropriately.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so the description is not required to explain any. The baseline for 0 params is 4, and the description correctly avoids inventing parameter details.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool performs a security scan with specific targets: open network ports, running process anomalies, and macOS TCC permissions. It also specifies the output (CVSS-rated findings and mitigation commands), making its purpose and scope unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for security scanning but does not explicitly differentiate it from sibling security tools like timps_security_remediation or timps_container_image_scanner. No 'when to use' or exclusion criteria are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full behavioral burden. It discloses the intended deliverable—step-by-step patch plan, working code diff, and rollback—but does not clarify whether the tool modifies files, requires special permissions, or has side effects. This leaves meaningful ambiguity for an agent deciding whether invoking it is safe.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that conveys the input class, output artifacts, and purpose without any filler. Every word contributes useful information, making it highly efficient and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple two-parameter tool with no output schema, the description covers the core input scenario and output expectations well. It could be slightly more complete by noting that 'request' is effectively required despite being marked optional in the schema, but overall the definition is adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, and both parameters already have clear definitions in the input schema. The tool description adds no additional parameter-level context, so it meets the baseline for schema-heavy definitions but does not improve parameter understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Convert'), a clear resource ('a security finding'), and a precise deliverable ('step-by-step patch plan with a working code diff and rollback'). This clearly differentiates it from security-related siblings such as timps_security_guard or timps_incident_responder.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly implies the usage context: when a security finding needs to be converted into a remediation plan. It does not explicitly name alternative tools or exclusion criteria, but the input examples (CVE, SAST, secret, misconfig) provide sufficient contextual guidance for an agent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears the full burden. It states 'Show' which implies a read-only operation, but it does not explicitly confirm no side effects, permissions, or data freshness. It lacks details on whether the output reflects real-time status or cached data, which is a minor gap for a status tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is one concise sentence, front-loaded with the action and resource. Every word contributes to the purpose. There is no redundancy or wasted space, achieving high clarity with minimal length.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema, the description must convey what the tool returns, and it does: it lists installed tools and their connection status. It does not describe output format or detail (e.g., whether it shows versions or connection details), but for a simple status tool, this is sufficient. The low complexity and zero parameters mean the description covers the essential aspects.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so the baseline is 4. The description does not add parameter-specific semantics because none exist, and the schema is fully covered by the absence of fields. The description's mention of 'installed' and 'connected' clarifies the output dimensions but not parameter meaning, which is irrelevant here.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a clear verb ('Show') plus a specific resource ('AI coding tools') and defines the scope (installed and connected to TIMPS Swarm MCP server). It is distinct from siblings like timps_full_checkup or timps_kernel_status, which focus on broader system status, whereas this tool specifically targets AI tool installation and connection state.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use it (to check AI coding tool installation/connection), but it does not explicitly state when not to use it or mention alternative tools. Given the large sibling list, there is no guidance on how this differs from status-related tools like timps_full_checkup or timps_kernel_status, making it only implied rather than explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must convey the behavioral profile. It communicates a read-style monitoring operation and names the return fields, which is helpful. It does not disclose whether there are side effects, permissions required, time windows observed, rate limits, or how 'spikes' are determined.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The entire description is a single, front-loaded sentence that conveys the core responsibility and return value without redundant detail. Every phrase adds information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple two-parameter tool with no output schema, the description gives enough context about inputs, scope, and outputs. It stops short of explaining digest content, time ranges, or threshold behavior, but these are not severe gaps given the tool's simplicity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already covers both parameters clearly, but the description adds meaning by enumerating the default tracked sources and stating what kinds of results are returned. It could be stronger by mentioning allowed values for 'sources' or the expected format of keywords, but the overall semantics are already useful.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Monitor'), names distinct content sources (Hacker News, Reddit, GitHub, Dev.to), and states concrete outputs (trend direction, sentiment, digest summary). It is easy to distinguish from sibling tools like timps_web_search or timps_research_agent, which are broader.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The intended use case is implied: watch keywords across developer-centric communities for spikes in interest. However, it does not explicitly say when to choose this tool over alternatives or when not to use it, and the large sibling list includes other research/monitoring tools that overlap without clear differentiation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the transparency burden. It mentions deduplication, content extraction, and citation generation, but omits details about data usage, external API calls, or potential limitations. It implies read-only behavior but does not explicitly state it.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, consisting of two sentences that effectively separate the tool's capabilities from its recommended usage. It avoids redundancy and extraneous detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Considering the tool's moderate complexity, the description covers primary features and use cases, including output characteristics (citations). It does not delve into error handling or edge cases, but for a search tool it is sufficiently complete. The mismatch with the 'language' parameter slightly reduces completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema provides descriptions for both parameters (request and language), achieving 100% coverage. However, the tool description adds no extra clarification about how these parameters should be used, and the 'language' parameter's meaning is ambiguous given the tool's web search nature. Baseline of 3 applies due to high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states that the tool performs multi-engine web search with deduplication, content extraction, and an LLM-synthesized answer with citations. It also identifies specific engines, making it unambiguous and distinct from other sibling tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit use cases: live lookups, news, vendor docs, and competitive intel. While it doesn't contrast with alternatives, these scenarios give clear guidance on when to employ the tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of conveying side effects. It states the tool 'detects' and 'returns' a plan, implying a read-only, analytical operation. However, it does not explicitly state whether it modifies the repo or if it performs any network/installation actions, leaving some ambiguity.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is succinct and well-structured, conveying the essential behavior and output in one sentence without redundancy. Every word adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with a single optional parameter and no complex output requirements, the description is complete. It explains what the tool does, its scope (Python and Node), and the nature of its result, which suffices for an agent to invoke it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The only parameter, repo_path, is fully described in the schema with a clear default and purpose. The tool description adds no further semantic detail, but the schema coverage is 100%, so the baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: detecting dependency conflicts, vulnerabilities, and outdated packages for Python and Node. It also specifies the output (a fix plan and remediation script), making the purpose unambiguous and distinct from other generic tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
While the description does not explicitly mention when to use this tool over alternatives, its focus on dependency analysis is clear enough for an agent to infer appropriate use cases. It lacks explicit 'when not to use' guidance, but the specialized scope compensates.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses what the tool does (detect duplicates, assign severity, suggest labels/owner) but does not describe side effects (likely none, as it's analysis), auth requirements, or output format. It is adequate but not comprehensive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is succinct, front-loaded with the primary purpose, and provides a clear action instruction. Two sentences with no fluff or redundancy earned every word.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema is present, so the description should at least hint at the expected return format. It describes the analysis steps but does not explain what the agent will receive (e.g., duplicate IDs, severity levels, labels). Given the tool's complexity, this is a notable gap, but the description is otherwise sufficient for core usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% as both parameters have descriptions. The description adds value by clarifying that the 'request' should contain raw issue title and body text combined, and repo_path is already explained in schema as 'Optional: local repo for duplicate detection.' The description enriches the user's understanding of how to construct the input.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: to triage a bug report or GitHub issue by detecting duplicates, assigning severity, suggesting labels, and owner. It specifies the verb 'triage' and the resource (issue), and distinguishes it from other timps tools by focusing on triage tasks specifically.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives a direct usage instruction: 'Pass the raw issue title and body text.' This tells the agent how to invoke the tool. However, it does not explicitly state when to use this tool vs. alternatives or mention exclusions (e.g., when not to use it), but the guidance is clear enough for the primary use case.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses the output ('Returns the spec + a design rationale document'), the behavioral scope ('Enforces REST/GraphQL best practices, versioning strategy, and consistent naming'), and the non-code-generating nature implied by 'BEFORE code generation starts.' This is solid but not exhaustive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Three focused sentences: what it generates, what it enforces, and what it returns. Every sentence adds value and the main purpose is front-loaded. No filler or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and no annotations, the description adequately explains the return value and the design workflow. It covers the core behavior and input intent, though it could mention side effects or file-writing behavior for full completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description reinforces that 'description' is a natural-language input but does not add meaningful detail about 'style', 'version', or 'auth_scheme' beyond what the schema already documents.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states a specific action ('generates a complete OpenAPI 3.1 spec (YAML)') on a specific resource from natural-language input. It also distinguishes itself from sibling tools like timps_api_contract_auditor or timps_api_security_tester by focusing on design before code generation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'BEFORE code generation starts' provides clear timing context for when to use this tool. It does not explicitly name alternatives or exclusions, but the design-focused purpose is evident compared to sibling tools that audit, test, or profile APIs.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It discloses the output format (3-sentence briefing) and content areas, but doesn't mention whether it reads from persistent storage, whether it modifies state, or any side effects. The 'refresh' parameter hints at caching behavior but isn't fully explained.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with the core purpose, includes usage trigger phrases, and zero wasted words. The description is compact and immediately actionable.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one optional parameter and no output schema, the description is quite complete. It explains what the tool does, what it returns, and when to use it. The only minor gap is not explaining the caching mechanism or what happens if no context exists, but given the tool's simplicity, this is adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% for the single parameter (refresh), and the description adds context by explaining the default behavior ('default: false') and purpose ('Force refresh even if cache is fresh'). However, the description doesn't elaborate on when refresh would be needed or what 'cache is fresh' means, but the schema already covers the parameter well.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Get a 3-sentence resumption briefing from the Context Keeper' with specific content (what you were working on, current state, recommended next step). It distinguishes itself from siblings like timps_context_switcher and timps_full_checkup by focusing on resumption briefing.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use: 'Use when the user says "what was I doing" or "catch me up"'. This provides clear trigger phrases and implies it's for resuming work, distinguishing it from other context-related tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the transparency burden. It explains a concrete behavior: it reads current system/git context, detects distraction apps, and generates a script to quit them. It also scopes the effect accurately as a generated script rather than implying it directly kills apps. It does not clarify where the script is placed or whether it is returned as text, but for a zero-parameter tool this is enough.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two tight, purposeful sentences. The first gives the analysis scope; the second explains the actionable output. No redundant language or restatement of the tool name.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter tool with no output schema and no annotations, this description covers the main required concepts: inputs examined, purpose, behavior, and deliverable. It falls slightly short of full completeness by not saying what the generated script looks like, where it goes, or how this tool fits into a larger context-switching workflow.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters and an empty input schema, so the baseline is 4. The description does not provide parameter details because none are needed; it instead explains what the tool analyzes, which is appropriate for this schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description names a specific verb and resource: 'Analyse current work context', with concrete scope including active apps, estimated browser tabs, git branch, and recent commits. It separates itself from siblings by adding a unique deliverable: 'Identifies distraction apps and generates a focus-mode script to quit them.'
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The intended use is implied rather than explicit: the description suggests this is useful when someone wants to understand or recenter their work context and reduce distractions by generating a focus script. However, it does not say when to prefer it over sibling tools like timps_context_briefing or timps_full_checkup, and it offers no explicit when-not-to-use guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden. It transparently lists concrete checks the tool performs (slow evals, duplicate PATH entries, syntax errors), making it clear this is a diagnostic scanner. However, it does not explicitly state whether the tool is read-only or may modify files, leaving a slight gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two well-structured sentences that front-load the core purpose and then provide specific examples. There is no fluff or repetition—every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has no parameters, no output schema, and no annotations, the description provides a solid overview of what it does and what it checks. It is self-contained and likely sufficient to decide when to use it, though a note about whether it only detects (vs. fixes) and about the output format would make it a 5.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so the input schema adds no detail and the description must provide the meaningful context. The baseline for zero params is 4; the description adds enrichment by naming the exact file types and scan domains, which is sufficient.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Detect') with a well-scoped resource ('errors and performance issues in shell config files') and explicitly lists the affected file types and example findings. This clearly distinguishes it from a generic health-check tool and from the many broader sibling tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description makes the tool's context clear—when you need to inspect shell config files for specific issues—but does not name alternatives or explicitly state when not to use it. Given the many overlapping sibling tools (e.g., timps_environment_doctor, timps_full_checkup), more explicit guidance would improve this score.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations available, the description carries the full burden, and it handles the most critical behavior well by stating 'dry-run — no files moved until user approves.' This clearly warns the agent and user that the tool does not execute changes itself. It doesn't cover edge cases or side effects like whether the script file is written to disk, but the core safety is transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences with no filler. It front-loads the main action, enumerates specific clutter types, and immediately states the resulting outputs and safety. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple, one-parameter tool with no output schema, the description covers the scanning scope, detection targets, generated outputs, and the dry-run safety behavior. It could be slightly more complete by describing the format/location of the generated plan and script, but it is sufficient for an agent to know when and how to invoke it.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already fully describes the one optional `path` parameter, including its default scope of `~/Downloads` and `~/Desktop`, so the description adds no new parameter-level detail. This meets the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies what the tool does: scans Downloads and Desktop for clutter such as duplicates, large files, and unnamed junk. It also names the concrete outputs (folder organisation plan, move script) and clearly distinguishes it from the many sibling tools by focusing on user-directory organization.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description makes the intended use obvious: run this tool when needing to identify clutter and prepare an organization plan for Downloads/Desktop. It does not explicitly name alternative tools or state when not to use it, but the scope and output are clear enough for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description communicates a read-only, 'safe' profile by using words like 'detect,' 'review,' and 'safe plan review,' and it lists the non-mutating outputs it produces. Still, with no annotations, it does not explicitly say that changes will not be applied or describe credential/permission requirements, leaving some ambiguity about side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence that front-loads the action and resource, then concisely enumerates three distinct outputs. There is no filler, repetition, or unnecessary qualification.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
This description covers the core purpose, scope, and major outputs in a compact way, which is sufficient for an agent to decide initial invocation. It does not fully specify CLI/return-value structure or safety guarantees, but the schema is simple and the prose covers the main behavioral expectations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already covers 100% of the parameters with clear descriptions of 'request' and 'language.' The tool description adds no additional parameter-level explanation or examples, so it is appropriately at the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description starts with a specific action verb ('Detect') and names the exact resources being evaluated: Terraform/Pulumi/CloudFormation state versus live cloud. It also lists concrete outputs (ranked diff, blast-radius estimate, safe terraform plan review), which clearly establishes what the tool does and differentiates it from general-purpose sibling tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly establishes the core use case: detecting infrastructure drift. However, it does not explicitly address alternatives such as the sibling terraform_plan_reviewer, which overlaps with the phrase 'terraform plan review.' The context is clear but exclusions and alternatives are not stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations provided, and the description does not explicitly mention that the operation is read-only or side-effect-free. Although listing is inherently benign, the lack of explicit transparency about side effects or permissions is a minor gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, uses clear language, and is appropriately structured for its purpose. It does not contain extraneous information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description adequately explains what the tool does and its high-level outcome, but it does not specify details like output format or edge cases (e.g., empty list). However, given the simplicity of the tool, this is sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has no parameters, so the schema is vacuously complete. There is nothing to describe, and the description correctly implies that no input is required.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states that the tool lists all TIMPS Swarm agents and their purpose, which is unambiguous. It also distinguishes itself from sibling tools by being the agent listing tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when needing to choose an agent, but does not explicitly contrast with directly invoking specific agents. It could be more explicit about when to use this listing tool versus directly calling a known agent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the transparency burden. It discloses that the tool returns a prioritized update plan (security-first) and a safe ordered shell script, signaling that it is a check-and-report tool rather than an automatic mutation. It doesn't detail operational prerequisites like network/permissions, but enough behavior is conveyed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact, well-structured, and includes all necessary high-level details in two sentences: input scope, output type, prioritization scheme, and key characteristic of the script. There is no wordiness or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given this is a zero-input tool with no annotations and no output schema, the description fully covers the relevant context: what systems/packages are scanned, what the output is, and how it is ordered. Enough for an agent to know when and how to invoke it.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool takes zero parameters, so there is no parameter semantic gap to fill. The baseline score of 4 applies because the description doesn't need to explain input fields; the schema and context already confirm the absence of inputs.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states what the tool does: checks for pending updates across specific categories (macOS/Linux OS, Homebrew, npm, pip). It uses a definitive verb ('Check for pending updates') and enumerates the exact resources, distinguishing it from broader or generic update tools in the sibling list.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The usage context is only implied: use this when you want to see pending updates and obtain an ordered script. It does not explicitly state when to prefer this tool over related sibling tools like timps_dependency_rebel or timps_system_optimizer, nor does it mention when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden, and it does well by enumerating the concrete outputs (persona, SSML, escalation rules) and constraints (latency budget, barge-in). It misses a few behavioral specifics like idempotency or whether it modifies state, but it's still quite transparent for a design/generation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, dense, front-loaded sentence with a valuable colon-separated list of features. Highly efficient, though it abstracts a great deal of detail that might merit a `sibling` callout.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the zero required parameters and no output schema, the description covers the design scope exceptionally well. It could be more complete with a note on expected output format, but it's quite thorough for the tool's purpose.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% — both 'request' and 'language' are documented. The description's rich enumeration of deliverables adds significant context the schema lacks, showing how it complements the structured parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Design') and enumerates a comprehensive list of voice-agent artifacts (persona, system prompt, SSML, tool calls, etc.), clearly distinguishing it from sibling tools like timps_routing_agent or generic design agents. The scope is unmistakable and actionable.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies a design-time, blueprints-style use case (as opposed to other agent tools like simulators or debuggers), covering context and deliverables. However, it does not explicitly state when NOT to use it or name an alternative for different needs, so it loses a point.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It clearly states it reads battery info (non-destructive) and generates kill commands (not executes them), which is transparent about its mutating potential. However, it does not fully explain the exact nature of the kill commands (e.g., whether they are suggestions or ready-to-run) or any side effects, leaving a small gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three concise sentences, front-loaded with the main purpose. Every sentence adds value—method, data sources, and output. No redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and no annotations, the description adequately explains the tool's function and its output. It could provide more detail on the format of the generated kill commands or whether they are executed automatically, but it covers the essential behavior for an agent to decide and invoke.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so the schema covers everything (100% coverage). The description adds no parameter-specific meaning because there are no parameters. Baseline score of 4 is appropriate given the absence of params.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a specific verb+resource ('Identify battery drainers') and elaborates the method (reads battery %, health cycle count, ranks by CPU usage) and output (generates kill commands). It clearly distinguishes this tool from siblings like system_optimizer or full_checkup by focusing on battery-specific diagnostics.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context about when to use (battery drain detection) but does not explicitly mention alternatives or when-not scenarios. Since it clearly targets battery issues, it is usable without confusion, but lacks explicit exclusions or comparisons to other diagnostic tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses the key safe behavior: the tool audits and returns a cleanup manifest, and 'no data is deleted until user reviews.' This effectively communicates a read-only/consent-gated nature. It could further state whether it writes any files or changes any settings, but the non-destructive promise is strong.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two tight sentences. The first states the purpose and scope; the second describes the output and safety guarantee. No filler, repetition, or unnecessary detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter audit tool with no annotations or output schema, the description gives enough context: what is audited, what is returned (cleanup manifest), and the crucial non-destructive behavior. It doesn't detail the manifest format, but for an agent selecting and invoking the tool, the provided information is sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters and an empty schema, so there is no parameter ambiguity to resolve. The description compensates by clarifying the audit scope (specific browsers and permission categories), which is the only semantic information an agent needs.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses specific verbs ('count', 'list') and identifies exact resources (cookies per Chrome/Firefox/Edge/Brave, macOS app permissions for camera/mic/location/contacts). It clearly establishes itself as a privacy audit/cleanup-manifest tool, distinguishing it from the many sibling tools focused on security, compliance, or system maintenance.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context: use this tool for a privacy audit of browser cookies and macOS permissions, and it explicitly notes that no data is deleted until the user reviews the manifest. It does not name alternative tools or state when not to use it, so it stops short of full usage guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. The description states it 'Show[s]' all configured providers and the active one, implying a read-only operation with no side effects. While it does not explicitly say 'does not modify state' or list permissions, the verb and context make the read-only nature clear. It adds value by framing the output for debugging, which is useful for the agent's decision-making.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, both front-loaded and directly relevant. The first sentence states the action and scope, and the second adds a practical use case. There is no wasted wording; every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple listing tool with no parameters, no output schema, and no nested objects, the description is complete. It explains what the tool does (list providers and active one) and why to use it (debugging). No additional information is needed; the agent can determine when to invoke this tool without ambiguity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters and the schema is empty. With no parameters, the description does not need to explain any. Per the rubric, 0 params receive a baseline score of 4. The description adds no parameter-specific details because none exist.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Show all configured LLM providers and which one is currently active.' It uses a specific verb ('Show') and a distinct resource (LLM providers), and the purpose is unambiguous. It stands apart from sibling tools like timps_list_agents (which lists agents) and timps_dispatch (which sends), so no confusion.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides a clear usage context: 'Useful for debugging which model is handling agent calls.' This indicates when to use the tool (debugging) and gives a practical scenario. It does not explicitly mention when not to use it, but the context is sufficient for an agent to select it appropriately among related tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

GitHub Badge

Glama performs regular codebase and documentation scans to:

Confirm that the MCP server is working as expected.
Confirm that there are no obvious security issues.
Evaluate tool definition quality.

Our badge communicates server capabilities, safety, and installation instructions.

Card Badge

Copy to your README.md:

[![timps-swarm MCP server](https://glama.ai/mcp/servers/Sandeeprdy1729/timps-swarm/badges/card.svg)](https://glama.ai/mcp/servers/Sandeeprdy1729/timps-swarm)

Score Badge

Copy to your README.md:

[![timps-swarm MCP server](https://glama.ai/mcp/servers/Sandeeprdy1729/timps-swarm/badges/score.svg)](https://glama.ai/mcp/servers/Sandeeprdy1729/timps-swarm)

Latest Blog Posts

Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)
By Om-Shree-0709 on July 25, 2026.
mcp
Agent Identity
OAuth 2.1
Your AI Chatbot Just Exposed Your CEO's Salary to an Intern
By Om-Shree-0709 on July 2, 2026.
Agent Identity
MCP Security
OAuth Delegation
Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)
By Om-Shree-0709 on June 30, 2026.
Agentic Ai
Prompt Injection
WebAssembly

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/Sandeeprdy1729/timps-swarm'

If you have feedback or need assistance with the MCP directory API, please join our Discord server