flameox

by morluto

Overview Schema Related Servers Score Discussions

Python

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Server Quality Checklist

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Latest release: v0.1.12
Disambiguation4/5
The tool names are highly specific about their target source or entity (e.g., extract_perfetto vs extract_nsight_compute, get_frame_callers vs get_frame_callees). While there are many get_* tools, they apply to different concepts, and descriptions clarify the differences. A few close pairs like extract_benchmark_samples and extract_nvbench could cause hesitation, but their descriptions distinguish them clearly.
Naming Consistency4/5
The vast majority use a verb_noun pattern (extract_*, analyze_*, list_*, plan_*, run_*). However, there are minor deviations such as workspace_status and workload_configuration_status (noun-first), and a mix of execute/run/start for actions (execute_capture_plan, run_experiment, start_detached_capture). These are easily readable but prevent a perfect score.
Tool Count1/5
With 93 tools, the surface is far beyond what an agent can easily navigate. Even if the domain is broad, this number is an extreme mismatch for the given tool-count rubric, which treats 50+ as excessive. The set would benefit from consolidation or a more focused scope.
Completeness4/5
The tool set covers the full lifecycle of profiling, tracing, experimentation, and investigation, including extraction, analysis, planning, execution, and persistence. Missing delete operations are likely intentional because many objects are immutable, and the remaining gaps (e.g., no explicit update for all entities) are minor and do not impede core workflows.
Average 3.4/5 across 93 of 93 tools scored. Lowest: 2.3/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 217 commits in the last 12 weeks
- Last stable release on August 8, 2026
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
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

Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false. The description adds that the tool produces both a summary and a Markdown view, which is a useful behavioral detail. However, it does not elaborate on what 'bounded' means, how missing IDs are handled, or any other runtime behavior, so additional context is limited.
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 a single sentence, but it is under-specified for a tool with a complex request object and output schema. It is not appropriately sized because it omits critical information, making it more of an under-specification than a concise, informative 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?
Given the high complexity (many parameters, output schema, and many siblings), the description is insufficient. It does not explain what a 'bounded canonical proof summary' is, what inputs are required, or what the Markdown view contains. The annotations provide some safety context, but the overall description does not adequately complete the picture.
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. The only parameter is 'request' which contains many fields (run_ids, finding_ids, etc.), but the description gives no hints about how to populate or interpret these fields, failing to compensate for the lack of schema descriptions.
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 uses the verb 'Render' with a resource ('one bounded canonical proof summary and its Markdown view'), but the resource is vague jargon. It does not clearly distinguish from sibling tools like get_evidence or compare_run_sets, which also deal with evidence summaries or comparisons.
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 context for when to use this tool versus alternatives. It does not mention any prerequisites, exclusions, or selection criteria, leaving the agent without guidance on choosing this tool from the long 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?
Annotations place readOnlyHint=false, indicating possible side effects, yet the description provides no behavioral details about what 'bounded' means, whether it mutates state, or what permissions are needed. Since annotations are all false and no extra context is given, the description fails to disclose important operational traits beyond the verb 'Extract'.
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 description is a single short sentence, which is concise. However, it is under-specified and cryptic; it does not front-load key information about usage or parameters. It is not a well-structured description despite its brevity.
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 one parameter, no output schema details, and sparse description, the description is incomplete. It does not explain what 'bounded prompt-free' implies for the result, nor does it describe return values (despite an output schema being present). The agent lacks context to understand the output or prerequisites for invoking this 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 sole parameter 'run_id' is entirely undocumented in both the schema and description. Schema description coverage is 0%, and the description does not explain what 'run_id' refers to or how it relates to the extraction. The description offers no semantic value for the parameter, leaving the agent without enough information to fill it correctly.
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 the action ('Extract') and the resource ('Mooncake request schedule evidence'), with constraints ('bounded prompt-free') that add specificity. It distinguishes itself from sibling extraction tools like extract_inference_result and extract_otlp_trace, though 'Mooncake' may be unclear outside a known 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 provided on when to use this tool versus alternatives. The description does not mention the required run_id, prerequisites, or any context where this tool is preferred over sibling extractors. This lack of usage guidance makes it hard for an agent to choose correctly among many similar extraction 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?
Annotations provide minimal safety info (all hints false), and the description does not add behavioral context such as side effects, return format, or requirements. 'Through Memray's public FileReader' is an implementation detail rather than behavior.
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 description is a single sentence, but the phrase 'through Memray's public FileReader' is unnecessary for operational use and the vagueness of 'supported memory concepts' reduces clarity. It is concise in length but under-specified.
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 one required parameter, no parameter documentation, and no usage guidance, the description leaves the agent with insufficient information to select and invoke the tool correctly. The presence of an output schema reduces the need for return-value docs, but other aspects are lacking.
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 single parameter run_id has no schema description, and the tool description does not mention what run_id refers to or how to obtain it. There is zero parameter guidance.
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 the specific verb 'Extract' and identifies the Memray source, which differentiates it from sibling extraction tools targeting other profilers. However, 'supported memory concepts' is vague and does not enumerate what concepts are included.
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 compared to other extract_* tools or alternatives. It lacks any contextual trigger or prerequisite (e.g., needing a Memray file).
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 all false, providing no safety or side-effect profile. The description adds no behavioral details such as whether extraction is read-only, requires special permissions, has size limits, or affects the data source. The word 'bounded' hints at limits but does not specify them.
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 description is a single sentence with no wasted words, which is structurally clean. However, it is under-specified and omits essential information; it is terse rather than 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?
Although an output schema exists, the description is too vague to give a complete picture. It does not explain what 'bounded semantic observations' are, how they relate to a run_id, or how this extraction differs from the many sibling tools. The low parameter description coverage and lack of usage guidance leave significant gaps.
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 the required run_id parameter at all. The schema provides only the title 'Run Id' and a string type, so the description fails to add any meaning or usage context for the parameter.
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 a specific action and object: 'Extract bounded semantic observations' emitted through 'flameox.sdk'. This distinguishes it from sibling extract_* tools which target different data types like traces, results, or profiling data. However, 'bounded semantic observations' is jargon-y and not fully defined, so it doesn't reach 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 many sibling extract tools, nor does it mention any exclusions or alternatives. It merely states what the tool extracts, leaving the agent to infer appropriate usage from the tool name and 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?
Annotations are all false (not read-only, not idempotent, not destructive), so they provide little safety context. The description adds the notion of 'freeze' implying immutability or persistence, but it does not disclose side effects, reversibility, or whether it modifies existing data. This is insufficient for a mutation-like tool with no safety hints.
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 description is a single, front-loaded sentence with no wasted words, which is commendable. However, it is under-specified for a tool with a complex nested request schema. It is concise but not appropriately sized, leaving critical details unexplained.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having an output schema (which reduces the need to explain return values), the description is inadequate for the tool's complexity. It fails to define core concepts ('bounded cohort', 'corpus snapshot'), explain what 'freeze' entails, or clarify how to specify the cohort. The tool operates in a domain with many analytical siblings, but the description lacks enough context to guide correct invocation.
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 mentions no parameters or request structure. The single 'request' parameter is a complex oneOf with distinct member/run_id modes, but the description gives no clues about how to populate it. The phrases 'bounded cohort' and 'corpus snapshot' vaguely imply the request fields but do not add concrete 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 uses a specific verb ('Freeze') and resource ('a bounded cohort') with a scoping phrase ('against one corpus snapshot'). It clearly indicates the tool's function and differentiates it from siblings like 'compare_run_sets.' However, the terms 'bounded cohort' and 'corpus snapshot' are domain-specific and not elaborated, preventing a perfect score.
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 does not mention any prerequisites, exclusions, or preferred scenarios. The sibling tools (e.g., 'compare_run_sets', 'plan_experiment') suggest related operations, but the description offers no differentiation or selection criteria.
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 already declare the tool read-only, idempotent, and non-destructive. The description adds that it returns timestamps, identities, and missing-parent evidence, which is useful, but it does not explain behavior such as whether the limit parameter controls pagination or if the tool operates only on certain artifact types.
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 description is extremely concise at just seven words, and every word is functional. However, the brevity sacrifices necessary context and definition, making it cryptic rather than efficiently clear.
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 an output schema present, the return structure is known, but the description does not explain what 'lifecycle gaps' are or when this tool should be used. It lacks the context needed to understand the tool's role among the many sibling tools, making the description 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 schema has two parameters (artifact_id and limit) with 0% description coverage. The tool description does not mention either parameter, so the agent gains no semantic understanding of how to fill them. The description fails to compensate for the schema's lack of detail.
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 specifies that the tool returns 'explicit timestamp, identity, and missing-parent evidence,' which indicates a clear output type but leaves the core concept of 'lifecycle gaps' undefined. It does not differentiate itself from sibling tools like get_evidence or extract_* tools, making the purpose only vaguely clear.
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. There is no mention of context, prerequisites, or exclusions, leaving the agent without information about appropriate invocation scenarios.
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 already indicate a non-read-only, non-idempotent write operation, so the description's 'record or revise' adds little beyond that. It does not disclose revision semantics (e.g., whether finding_id triggers an update, if evidence is replaced, or effects on lifecycle), despite the schema showing fields like lifecycle and finding_id.
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 description is extremely concise (7 words) and front-loaded with the verb, which is good. However, it is so brief that it borders on under-specification, similar to a label. It reads more like a title than a description with meaningful structure.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity—with nested evidence objects, lifecycle states, assessments, and a large schema—one sentence is wholly inadequate. The description does not address revision behavior, optional vs. required fields, or how to interact with existing findings, and the output schema does not relieve the need for basic usage context.
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?
With schema description coverage at 0%, the description must compensate but does not. It gives no hints about the 'request' parameter, required fields, or how evidence linkage works. The schema itself is self-documenting with defaults and enums, but the description contributes zero semantic value.
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 a clear action ('Record or revise') on a specific resource ('evidence-linked finding'), which distinguishes it from sibling tools like record_analysis or record_comparison. However, it lacks details on what constitutes a finding or the exact scope of 'evidence-linked', so it is not maximally 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 provides no guidance on when to use this tool versus alternatives such as record_hypothesis, record_analysis, or get_finding. There is no mention of context, exclusions, or relationships to sibling operations, leaving the agent to infer usage solely from the tool name.
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 indicate readOnlyHint=false and destructiveHint=false, so the agent knows it mutates but does not destroy. The description adds a little context with 'existing immutable run artifacts', implying it does not modify artifacts. However, it doesn't disclose side effects, conflict behavior, or the non-idempotent nature, which is a significant gap for a write operation.
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 description is a single, tight sentence with no fluff, but it under-specifies for the tool's complexity. It front-loads the core action but omits essential context, making it concise at the expense of informativeness.
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 rich input schema and presence of an output schema, the description lacks context about prerequisites, workflow integration, or failure modes. It gives no sense of what happens if the pipeline is already registered or if artifacts are missing. The complexity of this tool demands a more complete description.
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 provides no parameter-level meaning. The schema contains many nested fields (run_id, pipeline_name, stages, etc.) with only titles, and the description does not explain critical concepts like 'bounded ordered pipeline' or the stage status discriminator. The agent is left without sufficient semantic grounding.
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 'bind' and identifies the resource ('bounded ordered pipeline' to 'existing immutable run artifacts'). It is distinct from sibling tools, none of which register pipelines. However, 'bounded ordered pipeline' is jargon that is not elaborated, so it does not fully achieve 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 offers no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., artifacts must already exist) or exclusions, nor does it name any alternative tools for similar actions.
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?
All annotations are false, so the description must carry the full burden of disclosing behavioral traits. It mentions the underlying interface but does not disclose whether this is a read-only operation, any side effects, permission requirements, or error conditions. The term 'Extract' implies reading data, but the readOnlyHint is false, leaving ambiguity about side effects or whether it modifies run state.
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, direct sentence with no fluff. It front-loads the action and specifies a key contextual detail ('through NVIDIA's installed ncu_report interface'). It could be slightly more informative, but 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?
Despite the presence of an output schema, the description leaves significant gaps: it does not explain what 'bounded metrics' are, how run_id is used, when the tool should be invoked, or how it relates to other extraction tools. For a one-parameter tool, the lack of parameter and usage context makes the description 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 schema has 0% description coverage for the single required parameter run_id. The description does not mention run_id or explain how it relates to the extraction. Since the description provides no information about the parameter, it fails to compensate for the schema's lack of documentation.
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 the specific verb 'Extract' and identifies both the resource ('bounded metrics') and the mechanism ('NVIDIA's installed ncu_report interface'). The mention of 'ncu_report' distinguishes it from sibling tools like extract_nsight_systems and extract_perfetto. However, 'bounded metrics' is somewhat vague and could be more precise about what kind of metrics are extracted.
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 such as extract_nsight_systems or extract_inference_trace. It does not state any conditions, exclusions, or contexts where this tool should be 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?
Annotations are all false, providing no clear safety profile, so the description carries the burden of behavioral disclosure. It mentions running queries through a local processor, which suggests a read-style operation, but does not disclose side effects, permissions, data volume, or output behavior. No direct contradiction with annotations, but little added transparency.
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 with no redundant wording. It is appropriately front-loaded with the main action, though it sacrifices informative detail for brevity.
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 two underdocumented parameters, a large sibling toolset, and minimal annotations, the one-line description is insufficient. The output schema exists, so return values do not need elaboration, but parameter semantics, usage context, and behavioral details are missing, making reliable invocation difficult.
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 provides no meaning for the two parameters 'run_id' and 'artifact_id'. The phrase 'versioned curated queries' vaguely implies query selection but does not map to either parameter, leaving the agent without sufficient semantic grounding.
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 ('Run') and resource ('versioned curated queries through a configured local Trace Processor'), with the tool name 'extract_perfetto' providing domain context. However, 'versioned curated queries' is vague and does not specify what data is produced or how this differs from sibling extraction 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 other extract_* tools, nor are alternatives mentioned. The phrase 'configured local Trace Processor' hints at prerequisites but gives no exclusions or decision criteria.
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 already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering safety. The description adds 'bounded' and 'derived' as behavioral hints, which go slightly beyond annotations but are partially inferred from schema (limit/cursor). No contradiction exists.
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 description is a single sentence and avoids verbosity, but it is under-specified and uses jargon ('span signatures', 'bounded derived evidence') that reduces clarity. It is concise but not effectively front-loaded or complete.
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 4 parameters, an output schema, and a specialized purpose, the description is too sparse. It gives no context on how the tool fits into analysis workflows, what 'repeated span signatures' mean, or how results should be interpreted. The output schema exists but the description does not reference it.
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 compensate by explaining any parameters. It fails to mention artifact_id, limit, cursor, or minimum_repetitions. While parameter names are somewhat self-explanatory, the description adds no semantic value.
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 states a specific verb ('Return') and resource ('repeated span signatures'), which distinguishes it from sibling tools that analyze traces. However, 'bounded derived evidence' is vague and does not clearly convey that the tool finds repeated operation sequences. The purpose is understandable but not crisp.
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 workflow context, prerequisites, or exclusions. The agent is left to infer usage from the name alone.
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?
Annotations declare readOnlyHint=true, but the description says 'then run it', implying execution side effects. This contradicts the read-only hint and the description does not clarify the actual behavior.
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 front-loaded sentence with no filler, but its brevity sacrifices semantic clarity.
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 (5 params, nested objects, output schema) and the readOnly contradiction, the description is too thin. It doesn't explain what binding entails, preconditions, or how it relates to run_experiment.
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 covers 80% of parameters with descriptions (adapter, parameters, experiment_name, investigation_id; only hypothesis_id lacks description). The description adds no additional parameter-level detail, so it earns the baseline for high schema coverage.
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 states it binds a declared experiment and runs it, with sequencing after workflow/capability discovery. However, 'bind' is ambiguous and the 'run it' part overlaps with sibling run_experiment, so it doesn't fully distinguish itself.
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 implied sequencing ('After workflow and capability discovery') but no explicit comparison to alternative tools like run_experiment or plan_fault_experiment. It lacks 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.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already declare read-only, idempotent, and non-destructive behavior. The description adds minimal context ('reviewed filters', 'cursors') but does not disclose any new behavioral traits such as pagination semantics, filtering rules, or what 'normalized' entails.
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 description is a single sentence and is free of redundancy, but it is under-specified. It is concise in length but not in substance, offering only a minimal phrase that could be more informative without bloating.
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 6 optional parameters, no parameter descriptions, and an output schema present, the description is insufficient. It fails to explain what normalized measurements are, how filters interact, or the pagination mechanism, making it difficult for an agent to use the tool confidently.
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%, so the description must compensate by explaining parameter meanings. It only vaguely mentions 'filters and cursors' without specifying how limit, cursor, run_id, artifact_id, name_prefix, or include_warmups behave. This leaves the agent without sufficient semantics to choose parameter values correctly.
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 ('Query') and the resource ('normalized measurements'), which distinguishes it from sibling extract/analyze tools. However, 'normalized' and 'reviewed filters' are somewhat vague, leaving some ambiguity about what exactly is being queried.
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 are any exclusions or prerequisites mentioned. The description does not reference sibling tools or indicate a preferred 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?
Annotations indicate this is not read-only and not destructive, but the description adds little context beyond 'record or revise'. It doesn't disclose how revision works, whether previous versions are superseded, or any side effects on existing hypotheses, which is a significant gap for a 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no fluff or repetition. It earns its place by stating the core action, though it would benefit from additional detail; this is still concise rather than 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 the tool has 8 parameters, an output schema, and sits in a complex investigation workflow, the one-sentence description is inadequate. It doesn't explain the investigation context, how hypotheses are used, or any relationship to other tools, making it insufficient for correct invocation in non-trivial scenarios.
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 tool description provides no parameter information. The schema has 8 fields with mostly self-evident names but no descriptions, and the word 'falsifiable' only weakly hints at what a valid hypothesis entails. This forces the agent to rely on guesses about fields like 'discriminating_condition'.
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 'Record or revise' and a clear resource 'falsifiable hypothesis', which distinguishes it from sibling tools like record_finding and record_analysis. However, it doesn't clarify that revision is done via the optional hypothesis_id parameter, so it's slightly incomplete but still distinct.
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 such as record_finding or plan_experiment. The description does not mention any prerequisites, exclusions, or alternative tool names, leaving usage entirely 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?
Annotations are all false, providing no safety or side-effect hints. The description adds 'bounded' but does not disclose whether running the tool modifies server state, requires special permissions, or overwrites prior replays. Given that this is a non-read-only execution tool, more behavioral detail 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
A single sentence with an action-first verb and no redundant words. It conveys the core purpose efficiently, though it could include more useful 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?
For a tool that executes scenarios on servers, the description is too sparse. It does not explain the meaning of 'bounded replay', what happens during execution, how timeout_seconds and expected_plan_id are used, or any side effects. The presence of an output schema does not compensate for missing behavioral semantics.
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 mentions no parameters at all. The agent must rely solely on parameter names; 'expected_plan_id' is particularly unclear without explanation of its format or purpose. This is the lowest level of support.
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 phrase 'Plan and execute' and names the resource 'one bounded replay' against a server, clearly distinguishing it from planning-only siblings like plan_inference_scenario. However, it does not explain what a 'replay' is or how it differs from run_inference_profile, so it falls short of full clarity.
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 when-to-use guidance or mention of alternatives. The phrase 'managed or existing-local server' provides some context about deployment options but does not tell the agent when to choose this tool over run_inference_profile or plan_inference_scenario, nor any prerequisites.
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 provide no safety hints (all false), so the description carries the full burden. It mentions 'import' and 'register' implying side effects, but does not disclose what changes are made, whether the operation is reversible, or what happens to existing pipeline models. Very limited transparency.
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 front-loads the action verbs. It is efficient, though the phrase 'register the existing pipeline model' is slightly vague and could be clearer.
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 3 parameters, 2 required, and an output schema, the description is too brief to be complete. It leaves key terms like 'declared native compiler files' and 'existing pipeline model' undefined, and does not explain how source_root or sensitivity affect the operation.
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 only 33% (only path is documented). The description does not mention any parameters, so sensitivity and source_root semantics remain unexplained. With low coverage, the description should compensate but does not.
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 imports native compiler files and registers the pipeline model, which is a specific action. However, it does not differentiate from sibling import tools like import_nvbench or import_artifact beyond the kernel-build focus.
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 context suggesting the appropriate situation for invoking it. The description only states what it does, not when or why.
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 already declare readOnlyHint=true and idempotentHint=true, covering the safety profile. The description adds the terms 'bounded' and 'current', hinting at limited scope and temporal state, but does not explain cursor behavior or what exactly constitutes a 'projection'. With annotations present, the added value is modest, so a 3 is appropriate.
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 of five words, front-loaded with the verb 'List'. It is efficient with no wasted words, though the jargon 'finding projections' may obscure clarity. This is concise but not optimally clear, so it earns a 4 rather than a 5.
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?
An output schema exists, so return value structure is presumably documented, but the description lacks essential context about pagination, what 'current' means, and the nature of a 'finding projection'. With sibling tools like get_finding and record_finding, more guidance on relationships and result scope is needed for complete understanding.
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 the limit or cursor parameters. The word 'bounded' vaguely references the limit, but cursor semantics and their role in pagination are entirely absent, forcing the agent to rely on parameter names alone.
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 the verb 'List' and identifies the resource as 'finding projections', which clearly indicates a listing operation. It distinguishes from sibling tools like get_finding (single) and record_finding (create), though the term 'projections' is somewhat vague and not explicitly contrasted with related list 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 offers no guidance on when to use this tool versus alternatives such as get_finding or record_finding. It does not mention pagination context, exclusions, or any relationship to other listing tools, leaving the agent to infer appropriate usage solely from the name.
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 annotations already convey read-only, idempotent, non-destructive behavior. The description adds 'bounded' and 'current' which hint at pagination and state filtering, but does not elaborate on what constitutes a 'projection' or how the list is scoped over time. This adds some value beyond annotations but leaves key behavior unspecified.
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, short sentence with no wasted words. It is front-loaded and easy to parse, but it is arguably too terse, leaving key terms like 'projections' and 'bounded' undefined.
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 a paginated listing pattern with 'limit' and 'cursor', and an output schema exists. However, the description lacks context on what 'investigation projections' are, what 'current' refers to, and how pagination works. This is insufficient for an agent to confidently use the tool in a complex workflow.
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%: the description does not mention 'limit' or 'cursor' at all. The word 'bounded' implicitly references limiting but provides no explicit parameter semantics, leaving the agent to infer from the schema alone.
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 listing operation for 'investigation projections', with a verb and resource. However, 'projections' is ambiguous, and no distinction is made from sibling tools like get_investigation or list_findings. The modifier 'current' adds some scope but not full clarity.
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 specify when to use this tool versus alternatives, nor does it mention pagination behavior or what 'current' means in the context of an investigation workflow.
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 already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is clear. The description adds minimal informational value beyond that, mentioning that inputs are immutable and binding occurs 'before execution', which aligns with the read-only, idempotent annotations. No contradiction exists, but no significant extra behavioral context (e.g., side effects, permissions) 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single short sentence, free of fluff, and front-loads the core action ('Bind...'). It is concise, though the structure is minimal and lacks an overview or contextual hook. It earns high marks for brevity, but slightly loses because the sentence is vague and could incorporate more useful detail without bloating.
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 the request schema (two possible reduction types with many fields), the description is far too terse. While an output schema exists (so return values are covered) and annotations are provided, the description fails to explain what 'plan_reduction' accomplishes in the broader reduction workflow, what the 'request' shape should be, or any constraints. It offers minimal context 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 description coverage is 0% (the tool description has no parameter explanations). The sole 'request' parameter is complex, with two discriminated sub-types, and the description provides no guidance on how to choose between them or what fields mean. The schema itself provides some sub-schema descriptions, but the tool description adds no value, failing to compensate for 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 uses the verb 'bind' and identifies resources ('immutable input and approved reducer/predicate identities'). It clearly indicates this is a pre-execution planning step, implicitly distinguishing it from 'execute_reduction' and 'get_reduction'. However, it relies on jargon ('reducer/predicate identities') and doesn't explicitly state that it creates a reduction plan, so it falls short of full clarity.
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. It does not mention 'execute_reduction', 'get_reduction', or any other sibling tools, nor does it describe prerequisite conditions or exclusions. The one-sentence description leaves the agent to infer usage context solely from the name.
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 already convey read/write, idempotent, destructive, and open-world hints. The description adds the useful behavior that the call does not stay open and that reconnection is via run_id. However, it does not explain the destructive implication or what happens to existing runs.
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 short sentence that packs the key async/reconnect behavior without fluff. The phrasing is a bit cryptic, but it is efficiently sized.
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 destructive/async behavior and two required parameters, this one-liner is inadequate. It lacks context about what a detached capture is, when to choose it, and how the idempotency key should be constructed.
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 0%, and the description does not explain plan_id's meaning or the idempotency_key requirements (pattern, length). It only vaguely alludes to a 'current plan' and 'once', which is insufficient to use parameters correctly.
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 states the tool 'starts' a 'plan' and mentions reconnecting by run_id, giving a clear verb and resource. However, the phrase 'one current plan once' is awkward and ambiguous, and it does not explicitly mention 'capture' or distinguish this from synchronous start alternatives.
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 vs. execute_capture_plan, get_detached_capture, or other siblings. The context implies asynchronous start, but no explicit when/when-not or alternative references 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?
The phrase 'explicit timing semantics' provides a small hint about output behavior, but annotations are all false and the description does not disclose side effects, return format, permissions, or other important behavioral traits. Since the annotations do not cover safety or mutability, the description carries the burden but does not satisfy 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 a single, clear sentence that is front-loaded with the key action and resource. It avoids unnecessary elaboration, 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?
Although the tool has only one parameter and an output schema exists, the description lacks essential context for distinguishing it from many similar extract_* tools. It does not explain what 'benchmark samples' are, how they relate to a run, or when to use this tool, so the description is not sufficient on its own.
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 run_id parameter. While the parameter name and title are somewhat self-explanatory, the description fails to clarify what a 'run' refers to in this context or how run_id relates to benchmark samples.
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 ('Extract') and the resource ('raw accelerator benchmark samples'), adding a notable qualifier about timing semantics. It distinguishes itself from siblings like extract_inference_trace, though it could more explicitly contrast with other benchmark-related extraction tools such as extract_nvbench or extract_nsight_compute.
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 about when to use this tool versus alternatives. With a long list of sibling extract_* tools, the description does not mention any exclusions, alternative tools, or specific scenarios, leaving the agent to infer usage solely from the tool's name.
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 all false, so the description must carry the behavioral disclosure burden. It does not mention side effects, permissions, output format, or whether the operation is read-only. 'Extract' suggests a read operation, but readOnlyHint=false leaves ambiguity. No additional behavioral traits 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, front-loaded sentence with no wasted words. It clearly states the verb and object, making it highly concise and easy to parse.
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 presence of many sibling extract tools and an output schema, the description is too minimal. It does not explain when to choose this tool, the significance of the provider enum (including sglang_bench), or any prerequisites like run_id validity. It only covers the core purpose, leaving significant gaps for an agent deciding among alternatives.
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%, so the description must compensate for parameter meaning. It indirectly hints at provider values ('AIPerf', 'vLLM') but omits 'sglang_bench' and says nothing about run_id. The agent must infer parameter semantics from names and enum values alone.
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 the verb 'extract' with a specific resource: 'prompt-free AIPerf requests or vLLM aggregate measurements.' This distinguishes it from sibling tool extract_inference_trace, though it does not explicitly name any alternatives. The resource is somewhat domain-specific but clear enough for an inference-benchmarking 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?
The description gives no explicit guidance on when to use this tool versus the many sibling extract_* tools. It implies usage when needing inference measurements, but provides no exclusions or alternative suggestions, leaving the agent without clear selection criteria.
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 any behavioral traits beyond the bare action 'extract'. Annotations are all false, providing no useful signals, so the description carries the full burden. It omits side effects, permissions, rate limits, or return behavior, and the verb 'extract' implies read-only, but no explicit statement is made.
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 of nine words, front-loaded with the verb 'Extract'. It contains no filler or redundancy, making it highly scannable for an AI agent.
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 one parameter and an output schema present, the description should clarify context but does not. It fails to explain what constitutes 'evidence', the nature of a pyperf run, or how this relates to sibling extraction tools. The output schema might cover return values, but the description still lacks essential context for selection and invocation.
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 a single parameter run_id with no description (0% schema coverage). The description mentions 'pyperf run' but does not explain what run_id refers to, its format, or how to obtain it. It adds minimal value beyond the parameter name.
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 extracts evidence from pyperf runs, naming specific evidence types (run, warmup, loop, value). It distinguishes from sibling extract_* tools by explicitly mentioning pyperf, but 'value evidence' is somewhat vague and could be more 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?
No guidance is provided on when to use this tool versus alternatives like extract_pytest or extract_perfetto. There are no usage scenarios, prerequisites, or exclusions mentioned, leaving the agent to guess based on the name alone.
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 already indicate a non-read-only, non-idempotent, non-destructive operation, and the description's word 'durable' adds persistence context. However, it does not disclose side effects such as parent/child relationships, workspace initialization requirements, or exact return behavior beyond what the output schema may imply.
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 filler or repetition. It is appropriately front-loaded and easy to parse.
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 three input parameters and no usage guidance, the one-sentence description is incomplete. It omits optional parameter semantics and relationships between investigations, even though the output schema exists to cover return values.
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 names no parameters. It does not explain the meaning of question, symptom, or parent_investigation_id, leaving the agent without guidance beyond the raw property titles.
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 (create) and the object (a durable diagnostic question), making the tool's purpose evident. It is distinguishable from sibling retrieval tools such as get_investigation and list_investigations, though it could more precisely define what an investigation contains.
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 information is provided about when to use this tool versus alternatives like record_hypothesis, record_finding, or plan_experiment. There are no prerequisites, exclusions, or scenarios 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?
While annotations are present (readOnlyHint: false, destructiveHint: false), the description does not clarify potential side effects or operational behavior. 'Extract' implies reading, but readOnlyHint is false, creating ambiguity. The phrase 'bounded execution-path evidence' adds little about runtime effects or prerequisites like the meaning of 'bounded'.
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 redundancy or irrelevant details. It is front-loaded and easily parseable, appropriately sized for a simple tool.
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 an output schema and annotations, the description is too sparse for an agent to use the tool correctly. It does not explain what 'bounded execution-path evidence' means, what run_id should be passed, or any expected behavior. The presence of an output schema shifts some burden, but the description still lacks essential context to invoke the tool 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?
The input schema has one required parameter (run_id) with no description, and the description does not mention or explain run_id at all. With 0% schema description coverage, the description fails to compensate by clarifying what run_id refers to (e.g., a run identifier from a prior execution), making the parameter's purpose entirely opaque.
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 a clear verb ('Extract') and resource ('bounded execution-path evidence through coverage.py's public API'), making its purpose distinct from sibling tools like extract_pytest or extract_python_startup. It is unambiguous about what the tool does, using 'coverage.py' to differentiate it.
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, no prerequisites, and no exclusions. It simply states the function without contextual cues, so an agent has no basis for selecting it over other extract_* tools beyond the name and general topic.
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 says 'Extract' which conventionally implies a read-only operation, but the annotations specify readOnlyHint=false, indicating the tool is not read-only. This contradiction is not explained in the description, and no other behavioral details (e.g., side effects, auth requirements) 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 sentence with the verb and resource front-loaded. It lists the evidence types without unnecessary words 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?
Given a simple one-parameter schema and an output schema, the description is somewhat adequate but lacks usage context, behavioral transparency, and an explanation of how the evidence types relate to run_id. It also does not help with selection among the many sibling extract_* tools.
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 sole parameter run_id is not mentioned in the description, and the input schema provides no description (0% coverage). The description does not clarify what the run_id represents or how it is used to extract the listed evidence.
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 extracts pytest-specific evidence types (phase, fixture, worker, outcome, failure-latency), using a specific verb and resource. This distinguishes it from other extract_* siblings that target different data sources (e.g., extract_perfetto, extract_python_startup).
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 prerequisites, use cases, or situations where another extractor would be more 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?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, and the description is consistent with these. However, the description adds no additional behavioral context—such as performance implications, required input normalization, or output scope—beyond what annotations and schema already imply. A score of 3 reflects the minimal extra disclosure beyond annotations.
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 with no redundant words, and it is front-loaded with the action verb. It is appropriately short, though it omits usage and behavioral details that could be added without bloat. This is efficient but not maximally informative.
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 an output schema and strong annotations, which mitigate the need for detailed return descriptions and safety disclosure. However, the description does not address the tool's relationship to its data source (normalized Perfetto/Nsight traces are mentioned in the schema but not the description), nor does it explain what the analysis output represents. Given the complexity and the large sibling set, the description is minimally viable but leaves notable usage 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?
Schema description coverage is 50%, with only 'limit' and 'run_or_artifact' described in the schema. The tool description does not explain the remaining parameters ('phase', 'comparison_run_or_artifact') or add any semantics beyond the schema. The description fails to compensate for the undocumented parameters, leaving the agent to guess their meaning.
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 ('Analyze') and identifies the resource types (runtime launches, graph launches, kernels, idle gaps). It clearly focuses on accelerator launch activity, distinguishing it from sibling tools like analyze_hotspots or analyze_memory. However, it lacks an explicit contrast with sibling tools, so it does not fully earn a 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 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 such as extract_perfetto or analyze_execution, nor does it state prerequisites or when not to use it. The context shows many sibling analysis tools, and the lack of usage direction leaves the agent to infer the appropriate 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?
Annotations already indicate destructive behavior (destructiveHint: true) and non-idempotency, so the description does not need to restate those. It adds minor context about the scope ('one bound') and validation step ('independently revalidate'), but does not disclose what specifically is destroyed or what side effects the lifecycle has.
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 redundancy. Every word adds meaning: 'Execute' identifies the action, 'one bound reducer lifecycle' scopes the operation, and 'independently revalidate' adds a key behavioral detail. 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?
Despite a destructive hint and a potentially complex lifecycle, the description provides minimal context. It does not explain side effects, prerequisites, relation to plan_reduction/get_reduction, or what 'candidate revalidation' means in practice. An output schema exists, but the description still leaves significant gaps for an agent invoking this 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?
Schema description coverage is 0%, and the description does not explain the purpose or expected format of plan_id. While the name suggests it identifies a reduction plan, the description fails to clarify how plan_id relates to the 'bound reducer' or how it should be obtained.
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 ('Execute') and a specific resource ('bound reducer lifecycle'), and mentions a secondary action ('independently revalidate its candidate'). It clearly distinguishes from planning tools like plan_reduction and querying tools like get_reduction, though the phrase 'reducer lifecycle' is somewhat jargon-heavy.
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 vs. alternatives. The description does not mention prerequisites (e.g., an existing plan from plan_reduction) or when it should not be used. Usage is only implied by the name and the single parameter.
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 annotations provide no safety profile (readOnlyHint=false, all hints false), and the description does not disclose any side effects, permissions, or output behavior. The word 'extract' suggests a read operation but the annotations contradict that implication, yet the description doesn't clarify the discrepancy or the meaning of 'bounded findings'.
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 no redundancy, making it highly concise. However, the use of 'bounded' without definition is a minor clarity issue, though not a structural problem.
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 one parameter and no parameter descriptions, the description is too sparse to fully support the agent. It lacks information about what 'bounded' means, when to use it, and any behavioral expectations, despite having an output schema.
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 has zero description coverage for run_id, and the description does not mention the parameter at all. The parameter is only self-explanatory through its name, leaving the agent to guess what a 'run' refers to in this context.
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 tool as extracting findings from a Compute Sanitizer XML report, which distinguishes it from sibling extract tools for other formats. However, the term 'bounded findings' is ambiguous without further explanation, slightly reducing clarity.
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 no explicit guidance on when to use this tool versus other extract_* tools, nor any exclusions. The source ('official Compute Sanitizer XML report') implies its usage context, but that is indirect.
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 all false and provide no safety or side-effect hints. The description does not disclose whether this operation is read-only, whether it modifies state, or what it returns. The verb 'Extract' suggests a read operation, but the annotations do not confirm this, creating 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 sentence that is succinct and front-loaded. Every word adds meaning, with no filler or redundancy. It is an efficient and appropriately sized summary.
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 has one parameter and an output schema, the description is minimally adequate but lacks context about the tool's place among many extraction tools. It does not explain what constitutes 'repeated startup' or how this evidence is used, leaving gaps for an AI agent deciding when to invoke it.
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 (run_id), but the description provides no explanation of it. Schema description coverage is 0%, so the description carries no burden to compensate, and it fails to do so. The parameter name is self-explanatory, but the description adds no additional 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?
The description uses a specific verb ('Extract') with a specific resource ('Python startup') and lists three concrete evidence types (repeated startup, peak RSS, package-grouped import). This clearly distinguishes it from sibling extraction tools like extract_pytest or extract_perfetto.
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. There are no preconditions, exclusions, or references to sibling tools. The usage is only implied by the name and description, not stated explicitly.
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 already declare the tool as read-only, idempotent, and non-destructive, which covers the safety profile. The description adds the optional hashing behavior but does not specify what payloads are hashed or any performance implications. No contradiction with annotations.
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 action and resource, and contains no fluff. However, its terseness sacrifices useful detail, making it less effective than a slightly expanded version.
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 the presence of an output schema, the description covers the core action adequately. However, it lacks context on when to use it in the workspace workflow, what 'full' mode specifically entails, and what kind of validation is performed beyond the vague 'manifests and schemas'.
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 only parameter 'mode' has enum values but the description does not explain them. The phrase 'optionally hash every payload' hints that 'full' mode may trigger hashing, but it is not explicitly connected. With 0% schema coverage, this is insufficient compensation.
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 ('validate') with clear resources ('manifests and schemas') and adds an optional action ('hash every payload'). It is clear but does not explicitly distinguish from sibling tools like workspace_status, though the resource scope makes it 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 prerequisites, such as requiring an initialized workspace, or when to choose 'standard' versus 'full' mode. The statement is purely descriptive, not prescriptive.
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 provide no safety profile (all hints are false), and the description does not disclose side effects, prerequisites, or whether extraction mutates state. The term 'Extract' suggests read-only, but readOnlyHint=false implies potential non-read behavior without explanation.
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 content. Every word earns its place, and it is appropriately concise for a one-parameter extraction tool.
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?
Although an output schema exists and parameter count is low, the description omits essential context such as what 'bounded per-case metrics' means, how to obtain run_id, and when this extractor is appropriate. With many sibling extract tools, this minimalism leaves significant 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 only parameter, run_id, is left unexplained; the description does not clarify what it identifies or how it relates to kernel-validation evidence. Schema coverage is 0%, and the description fails to add meaning beyond the basic type/length 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 states the tool extracts bounded per-case metrics specifically from kernel-validation v1 evidence, using a specific verb and resource. It distinguishes itself from sibling extract tools (e.g., extract_inference_trace, extract_perfetto) by naming the 'kernel-validation' 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 guidance is provided about when to use this tool over alternatives or any exclusions. While the name implies kernel-validation context, there is no explicit mention of when to select this extractor versus other extract_* 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?
Annotations already declare readOnlyHint=true and idempotentHint=true, so the description does not need to repeat safety. It adds the behavioral trait 'immutable', which goes slightly beyond annotations, but offers no detail on error behavior, return format, or permissions. This is adequate given the strong annotation coverage.
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 of six words. Every word contributes meaning, and the key information (return, one, immutable, experiment protocol) is front-loaded. There is zero waste.
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 getter with one parameter, an output schema, and strong annotations, the description is minimally viable. However, it lacks usage context (when to fetch a protocol vs. a fault experiment or reduction) and does not clarify the relationship between an experiment protocol and other entities, leaving some gaps for an agent.
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%, meaning the description does not explain the experiment_id parameter. The single parameter name is self-explanatory, but the description fails to add any semantic value, such as a format, source, or how to obtain a valid ID. The description should compensate for the lack of schema documentation but does not.
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 returns a single immutable experiment protocol, using a specific verb and resource. It does not explicitly differentiate from sibling tools like get_fault_experiment or get_reduction, but the resource type is distinct and the qualifier 'immutable' adds useful specificity.
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. There is no mention of prerequisites, exclusions, or conditions that would help an agent decide between get_experiment and similar getter tools 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.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior. The description adds 'bounded' and 'privacy-limited', giving some insight into result size and data redaction beyond the annotations. However, it does not elaborate on what 'privacy-limited' entails or how the bound applies, leaving some gaps.
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 words. Every term ('bounded', 'privacy-limited', 'process observations', 'one run') adds value, 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.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The presence of an output schema and strong annotations reduces the need for detailed return-value explanations. However, the description remains vague about what 'process observations' include and how this tool fits among many extract_* siblings, leaving the context incomplete for an agent to confidently select it.
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 has 0% description coverage, so the description must compensate. It hints at 'bounded' for the limit parameter and 'for one run' for run_id, but does not explain the phase parameter or provide syntax/meaning for any parameter. This is insufficient given the lack of schema descriptions.
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 'Return' with a clear resource 'process observations' scoped to 'one run'. It conveys the core function, but does not explicitly differentiate from sibling tools like extract_observations, so it lacks the explicit sibling distinction that would earn 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 such as extract_observations or get_trace_window. It only states what it does without any context for selection, so it fails to help the agent choose appropriately.
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 adds the precondition that the export must be 'imported,' and 'curated' suggests a filtering/processing behavior. However, it does not disclose potential side effects or mutation despite readOnlyHint being false, so the behavioral profile remains incomplete.
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, front-loaded sentence with no wasteful words. It is concise but slightly under-specified, earning a high score for efficiency though not perfection.
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 an output schema present, return values are covered, but the description lacks usage guidance and parameter context. It does not help disambiguate from closely related tools like extract_nsight_compute, making the description incomplete for a tool in a large sibling family.
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 mention run_id at all. The sole parameter is left entirely to the schema's minimal 'Run Id' label, so the description adds no semantic value for the parameter.
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 extracts 'curated evidence' from an 'imported official Nsight Systems SQLite export,' giving a specific verb, resource, and scope. It distinguishes itself from sibling tools like extract_nsight_compute by explicitly naming Nsight Systems.
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 neither mentions the appropriate context nor excludes other extraction tools, leaving 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.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and idempotentHint=true, so the safety profile is known. The description adds the nuance of 'current' revision, indicating it returns the latest version, but does not disclose other behaviors like error handling or what happens if no revision exists.
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 words. It states the action and object clearly, achieving maximum efficiency.
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 read-only getter with one parameter and an output schema, the description is mostly complete. It could mention behavior when no revision is found, but the simplicity of the tool and the strong annotations mitigate this gap.
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 0%, so the description must compensate. It mentions 'hypothesis revision' but does not explicitly explain the hypothesis_id parameter, its role, or how it relates to the returned revision. The description adds minimal value for the sole parameter beyond what the schema already shows.
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 clear verb 'Return' and a specific resource 'current hypothesis revision', making the primary action evident. However, it does not distinguish this tool from sibling tools like get_evidence or record_hypothesis, so it lacks explicit 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 guidance on when to use this tool versus alternatives. It simply states the action without context, prerequisites, or exclusions, leaving the agent without usage direction.
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 already declare readOnlyHint true, idempotentHint true, and destructiveHint false, so safety is covered. The description adds the 'bounded time range' overlap behavior, but does not explain normalization semantics or pagination behavior (limit/cursor), which would add value beyond 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 filler. Every word contributes to the core purpose, making it highly efficient.
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?
With a rich output schema and safety annotations, the description is adequate for a simple read-only query. However, missing context about pagination (limit/cursor), what 'normalized' means, and the relationship to artifact_id leaves gaps for a tool with six parameters and potentially complex filtering.
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 compensate by explaining any of the six parameters. While parameter names like start_ns, end_ns, and artifact_id are self-explanatory, the tool description adds no semantics, and terms like 'normalized' and 'overlapping' are not tied to parameter behavior.
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 ('Return'), a resource ('normalized OTLP spans'), and a scope ('bounded time range'). This distinguishes it from siblings like get_trace_window or get_operation_transitions by focusing on normalized OTLP spans within a time window.
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 exclusions, prerequisites, or contrast with similar trace/operation tools, leaving the agent to infer usage 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?
Annotations already flag the operation as non-read-only and idempotent. The description adds that it does not execute the scenario and that it can replace an existing configuration, which is useful context but does not go into further detail about side effects or permissions. No contradiction with 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 entire description is a single concise sentence that effectively front-loads the core purpose and the non-execution behavior. No wasted words, every part adds meaning.
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 19 parameters and a complex configuration task, this description is far too sparse. It omits what a 'typed inference replay scenario' is, how it relates to servers or workloads, and does not guide the user through parameter selection, despite having an output schema that can't convey configuration semantics.
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 only 16% and the tool description provides no parameter explanations, leaving 19 parameters to be interpreted solely from the schema. The description doesn't even mention the required parameters, so it fails to compensate for the low 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 specific verbs 'Create or replace' and identifies the resource as 'typed inference replay scenario', with the qualifier 'without executing it' clearly distinguishing it from execution tools like run_inference_scenario. This differentiates the tool's purpose from siblings such as plan_inference_scenario and run_inference_scenario.
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 'without executing it' implies the tool is for configuration rather than execution, but the description does not explicitly state when to use it over alternatives like run_inference_scenario or plan_inference_scenario, nor does it mention prerequisites or exclusions. This is implied usage rather than explicit 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?
Annotations are all false, so the description carries the burden. The description only mentions a bundle constraint, not behavioral aspects like side effects, idempotency, or error behavior. It does not disclose whether extraction is read-only or if it modifies anything, despite the readOnlyHint being false.
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 the main purpose in the first sentence and an important constraint in the second. No wasted words, and the structure is front-loaded. However, it could benefit from a bit more detail on parameters or 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?
For a simple tool with one parameter and an output schema, the description covers the core purpose and a key constraint. But it lacks usage guidance and behavioral transparency, leaving the agent uncertain about when to invoke it and what side effects to expect. It is minimally viable but not comprehensive.
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 run_id beyond the schema's title 'Run Id'. With a single simple parameter, the description should at least confirm how run_id is used, but it does not, leaving the parameter semantically underspecified.
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 ('Extract'), specific resource ('NVBench sample times and frequencies'), and source ('preserved bundle'). This distinguishes it from siblings like extract_benchmark_samples and import_nvbench, which have 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 Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage by stating a prerequisite ('must contain exactly one primary NVBench JSON artifact'), but it does not explicitly state when to use this tool versus alternatives or any exclusions. It provides a condition for use but not comparative 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?
Annotations already declare readOnlyHint=true and idempotentHint=true, so the description adds limited new behavioral context. It does add that results are 'bounded' and that causality is not interpreted, but doesn't elaborate on pagination or depth limits. This is acceptable given annotation coverage.
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 wasted words. It front-loads the action and resource, and the qualifier adds relevant nuance.
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 five parameters and numerous sibling tools, the description is too terse. It doesn't clarify what a 'parent/child transition' is, how to use pagination or depth, or how this tool differs from related operations. The output schema exists but doesn't compensate for missing usage 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?
Schema description coverage is 0%, and the description doesn't explain any of the five parameters. 'Bounded' hints at limit/max_depth, but cursor, trace_id, and artifact_id semantics are left entirely to the schema, which only provides titles. The description fails to compensate for the lack of schema 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 ('Return') and identifies the resource ('parent/child transitions') with a distinguishing qualifier ('without interpreting causality'). This clearly differentiates it from sibling tools focused on causal analysis or lifecycle gaps.
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 explicit guidance is given on when to use this tool versus alternatives like get_operation_window or get_lifecycle_gaps. The phrase 'without interpreting causality' implies an exclusion, but it's not stated as a clear usage context, leaving 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.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnly=false and idempotent=false, and the description's 'Persist' is consistent with a write operation. It adds the workflow suggestion but does not disclose side effects such as whether the analysis can be overwritten, whether it requires an existing analysis from an analyze_* tool, or any other behavioral nuances beyond persistence.
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 short, front-loaded sentences with zero filler. Every word contributes to the purpose and usage guidance, making it highly concise and well-structured, though it sacrifices depth.
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 a complex request schema with seven recipe variants, the description offers only a high-level purpose and a single usage pointer. It does not explain how to choose a recipe, what input_id refers to, or any relationship to specific analyze_* tools. The existence of an output schema mitigates return-value explanation, but the overall guidance is inadequate for correct invocation.
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 provides no parameter details. It does not mention the single 'request' parameter, the discriminator 'recipe', the various recipe values (memory, scaling, failures, etc.), or other fields like input_id and limit. The description adds no semantic value beyond what the raw schema already shows, which is insufficient for such a complex nested request.
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 a clear verb and resource ('Persist a curated analysis') and explicitly contrasts with 'analyze_* first for read-only preview', distinguishing it from the read-only analysis siblings. However, it doesn't specify the analysis recipe types or exactly which record entity is created, leaving some ambiguity about the tool's full scope.
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?
'use analyze_* first for read-only preview' provides explicit guidance on when to use this tool versus the analyze_* alternatives, establishing a clear workflow: preview with analyze_*, then persist with record_analysis. However, it does not mention other relevant record tools (e.g., record_comparison, record_finding) or explain the recipe selection criteria.
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 already declare destructive behavior and non-idempotency, so the description doesn't need to repeat that. It adds useful scope (every baseline and treatment) and mechanism (loopback proxy), but it does not explain side effects, state changes, or return behavior. 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?
A single, direct sentence with no filler. It front-loads the action (Run) and clearly describes the target scope and proxy mechanism, making it highly 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?
Despite the existence of an output schema and annotations, the description lacks essential context: it doesn't explain how plan_id is obtained, what results are returned, or how this tool relates to planning and retrieval siblings. For a destructive operation, more elaboration is warranted.
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 provides no description for plan_id, and the tool description does not compensate. The parameter name is self-explanatory, but there is no detail about where the plan_id originates or any format requirements, leaving the agent to guess.
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 clear verb ('Run') and a specific resource ('every baseline and declared treatment') through a named mechanism ('managed loopback proxy'). This distinguishes it from sibling tools like run_experiment and clearly indicates a fault-experiment execution 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 given on when to use this tool versus alternatives. It does not mention prerequisites like plan_fault_experiment, nor does it state when not to use it. The agent is left to infer the correct usage 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?
Annotations are all false, so the description carries full burden for behavioral disclosure. It only mentions 'diagnostic-only' which hints at non-intrusiveness, but it does not disclose side effects, whether it starts a profiling session, blocks, or requires server state. No contradiction with annotations, but significant transparency 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?
A single, front-loaded sentence that states the action and scope with no filler. It is appropriately concise for the information conveyed.
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?
An output schema exists, so return value details are not needed, but the description still lacks workflow context. It doesn't explain what a 'profile window' is, how it relates to plan_inference_profile or measurement_run_id, or what prerequisite conditions apply. Incomplete for a complex operation with six parameters.
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 very low (17%; only measurement_run_id has a description). The main description adds no parameter-specific information, leaving the agent to infer meanings from names/enums. It does not compensate for the missing schema 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 ("Run") with a specific resource ("one diagnostic-only profile window") and target ("managed vLLM server"). This clearly distinguishes it from siblings like run_inference_scenario or run_experiment by focusing on a profiling-specific operation.
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 diagnostic profiling on a vLLM server, but it does not explicitly state when to prefer this over alternatives or mention exclusions. It lacks clear context such as 'use when you need to profile' or 'do not use for standard inference runs.'
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 already declare readOnlyHint, idempotentHint, and destructiveHint=false, so the safety profile is clear. The description adds the terms 'current' and 'projection', suggesting a snapshot view, but does not elaborate on behavior like behavior when ID is invalid or whether the projection 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 a single, front-loaded sentence with no redundancy. It is appropriately sized for such a simple tool, saying exactly what it does without extraneous 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 simple get-by-ID tool with annotations and an output schema, the description is mostly adequate but lacks key context: it does not clarify what a 'projection' entails, nor does it provide usage guidance relative to the many sibling tools. It is not fully self-sufficient for an agent unfamiliar with the domain.
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 has one parameter, investigation_id, with no description (0% coverage). The description does not explicitly explain that this parameter is the identifier of the investigation to return, although the parameter name is self-explanatory. Since the description must compensate for zero schema coverage and does not, the score is low.
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 returns one investigation projection, using a specific verb ('Return') and resource ('investigation projection'). It distinguishes itself from sibling tools like list_investigations (which returns multiple) and create_investigation (which creates).
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 such as get_hypothesis or get_finding, nor are any exclusions or prerequisite conditions mentioned. The description only implies a simple fetch-by-ID operation.
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 already declare readOnlyHint=true and idempotentHint=true, so the description carries less burden. It adds a behavioral nuance by describing the result as 'immutable terminal,' indicating the result is final and not subject to change. However, it does not disclose return structure, potential errors, or any other safety-relevant details.
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 no filler words. It is front-loaded with the primary action and object, earning its place without unnecessary elaboration.
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 is a simple read operation with one parameter, output schema, and strong annotations, the description is minimally adequate. However, it leaves gaps about what a 'reduction result' is and why 'reconnect' is used instead of 'get,' which could be unclear in a broader toolset with many similar get_* tools.
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 has 0% description coverage, and the description does not explain reduction_id beyond its name. Although the parameter is self-explanatory (an ID for a reduction), the description adds no meaning about the expected format, source, or relationship to the returned result.
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 'Reconnect' and identifies a concrete resource: 'one immutable terminal reduction result.' This clearly distinguishes the tool from siblings like plan_reduction and execute_reduction, which are about planning and executing reductions rather than retrieving results.
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 use this tool or how it relates to alternatives such as execute_reduction or get_experiment. The description does not mention prerequisites, typical flow, or exclusions, leaving the agent to infer usage 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.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate destructive/non-idempotent behavior, but the description adds useful context beyond them: the token is single-use and the expected follow-up is get_run. This provides concrete behavioral expectations that annotations alone do not convey.
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 short sentences with no filler. It front-loads the core action ('Run one current plan with side effects') and includes the most critical behavioral constraint (single-use token) in a compact form.
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 has a single parameter, an output schema, and annotations, the description covers the basic action and a key side effect, but it omits prerequisites (e.g., that a plan must exist and be 'current') and does not explain what 'side effects' entail. This is adequate for a simple tool but leaves some gaps for an agent to fill.
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 required parameter (plan_id) with zero description coverage. The description mentions 'current plan' but does not explicitly explain that plan_id refers to a plan created by plan_capture, nor does it clarify the format or source of the ID. The agent must infer the meaning from the tool name and context, which is insufficient.
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 a specific verb ('Run'), resource ('current plan'), and key trait ('with side effects'). It distinguishes itself from planning tools (plan_capture) and detached capture (start_detached_capture) by emphasizing 'one current plan' and the single-use token, though it could be clearer about what a 'current plan' refers to.
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 instruction 'then get_run' implies a sequential workflow but does not explicitly state when to use this tool versus alternatives like start_detached_capture or execute_reduction. No exclusions or specific use-case conditions are provided, so guidance is only 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?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, covering the safety profile. The description adds the qualifier 'known', indicating the reference must exist, but does not disclose failure behavior or return format (though output schema covers that). It adds limited context beyond 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 that conveys its purpose without redundant wording. Every word contributes meaning, and it is appropriately concise for a simple lookup operation.
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?
With an output schema and safety annotations, the description is minimally sufficient but does not explain how this generic getter relates to specialized siblings or the broader workflow. It lacks guidance on when to prefer this tool over get_run, get_artifact, etc., making it incomplete for a tool in a large sibling set.
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 50%: ref_id has a description and ref_type has an enum but no description. The description reinforces that ref_type and ref_id must be passed separately and after discovery, adding some conceptual context. However, it doesn't elaborate on each parameter beyond the schema's existing information.
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 a clear verb ('resolve') and resource ('known typed reference'), along with the required parameters (ref_type and ref_id). It distinguishes itself from specialized getters by being generic, though it doesn't explicitly define 'evidence' or contrast with 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 phrase 'after discovery' implies the tool is meant for references already obtained through discovery, providing some usage context. However, it does not explicitly state when to use this generic tool versus specialized alternatives like get_run or get_artifact, so guidance is only implied.
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 already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds the 'current revision' aspect, which is useful context, but it does not disclose other behaviors like error handling or what happens if no revision exists. With annotations present, this is adequate.
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 unnecessary words, making it easy to parse and front-loaded with the core 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?
This is a simple getter with one parameter and an output schema, so the minimal description covers the essential behavior. However, it lacks a bit of context about revisions, such as how 'current' is determined or whether historical revisions are accessible, but that is not critical for a basic retrieval 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?
Schema coverage is 0%, and the description does not explain the finding_id parameter or its format. While the parameter name is fairly self-explanatory, the description adds no explicit semantic value beyond the schema, and at 0% coverage it should compensate but does not.
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 'Return the current finding revision' clearly identifies the action (return) and the resource (current finding revision), which distinguishes it from other get_* tools that target different resources. It 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 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 such as list_findings or record_finding. The description merely states what it does without any context or exclusions.
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?
Annotations already declare read-only, idempotent, and non-destructive behavior, so the description does not need to repeat that. It adds value by introducing the 'bounded' concept (suggesting pagination) and the 'pinned corpus snapshot' scope, which are behavioral traits beyond the annotations. No contradiction exists.
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 unnecessary words. It conveys the core purpose and scope without padding, 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.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema and clear annotations, the description is moderately complete. It states the tool's purpose and scope but lacks guidance on when to use it and how parameters affect the result. For a simple list tool with two parameters, this is acceptable but leaves gaps in usage and parameter detail.
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%, so the description must compensate for parameter meaning, but it does not mention 'limit' or 'cursor' explicitly. The schema itself provides type constraints (limit integer 1-1000, cursor string/null) and a default, but 'bounded' only vaguely hints at the limit parameter. The description adds minimal parameter value.
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 'List' and identifies the resource as 'artifact metadata' from 'one pinned corpus snapshot,' which clearly states the tool's function. It distinguishes from siblings like get_artifact (full artifact) and list_runs (runs), though 'bounded' could be more explicit. Overall, it is specific and meaningful.
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 a use case—retrieving artifact metadata from a pinned snapshot—but does not explicitly state when to use this tool over alternatives or mention any exclusions. Sibling tools like get_artifact or list_runs are not referenced, leaving usage guidance only implied.
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?
Annotations already declare readOnlyHint=true and idempotentHint=true. The description adds context by explicitly stating 'This tool never executes the workload,' which clarifies the non-execution guarantee beyond the abstract hints. It also explains the behavioral implication of auto mode regarding 'no enforced descendant containment,' adding useful semantic detail without contradicting annotations.
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 description is relatively brief but contains a potentially confusing sentence: 'The default auto mode runs the declared workload directly in the local environment' could be misread as the tool executing the workload, even though the final sentence clarifies it never executes. The structure is acceptable but could be tightened for clarity.
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 complex input schema (nested objects like TorchProfilerCaptureOptions and ComputeSanitizerCaptureOptions) and 8 parameters, the description only covers the core purpose and capture_mode. It does not explain prerequisites like 'current capture,' preflight modes, or how external_context is used. Though an output schema exists, it does not mitigate the lack of input parameter guidance.
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 only 38%, so the description must compensate. It does add guidance for capture_mode (auto/managed/trusted_local), but it ignores other key parameters such as preflight_mode, external_context, torch_profiler_options, and compute_sanitizer_options. For a tool with 8 parameters, this partial coverage leaves the agent under-informed about most 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 opens with a specific verb+resource: 'Bind one current capture without running it,' which clearly distinguishes it from execution tools like execute_capture_plan. The closing line 'This tool never executes the workload' reinforces the non-execution purpose, making it 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 provides explicit guidance on when to use different capture_mode values: 'Use managed only when the project policy explicitly requires containment, and use trusted_local to request the same direct local execution explicitly.' However, it does not directly contrast plan_capture with sibling tools or state prerequisites, so the guidance is limited to parameter selection rather than tool 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?
Annotations already disclose read-only, idempotent, and non-destructive behavior, so the description need not repeat those. It adds useful context about supporting 'managed or existing-local server' and constructing a 'typed replay plan', but it does not reveal details about the preflight process, potential failure conditions, or what the plan contains. This is a modest addition beyond the 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 sentence of 12 words, front-loaded with the primary action. Every term ('Preflight', 'managed or existing-local server', 'typed replay plan') carries specific meaning, and there is no redundant language 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?
Despite having an output schema and safety annotations, the description is too terse for a tool with two undocumented parameters. It does not elaborate on what 'preflight' entails, how to specify the server via scenario_name, or what a 'typed replay plan' is. The presence of an output schema helps with return values, but the overall context is insufficient for an agent to invoke the tool with confidence.
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 no descriptions (0% coverage), so the description must compensate. However, it does not explain scenario_name or timeout_seconds at all, nor their relationship to the server or plan. The only hint is the tool name itself. For two parameters with zero documentation, the description fails to provide necessary semantic 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 uses specific verbs ('Preflight', 'construct') and clearly identifies the resource ('managed or existing-local server') and the output ('typed replay plan'). It distinguishes itself from sibling tools like run_inference_scenario by focusing on planning rather than execution, making its purpose 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 before running an inference scenario ('Preflight') but does not explicitly state when to use this tool vs alternatives or provide exclusion criteria. There is no mention of 'use this before run_inference_scenario' or similar guidance, leaving it to the agent to infer from the name and 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?
Annotations already convey that the operation is not read-only, is idempotent, and is not destructive. The description adds the term 'cleanup', which gives some extra behavioral context (side effects beyond just cancelling). However, it does not detail what cleanup entails or whether the operation is asynchronous (via 'Request'). No contradiction with 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?
A single sentence that is front-loaded with the action and resource, with no redundant or filler content. It earns its place by conveying the core purpose 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?
Given the simple tool (1 parameter, no nested objects) and the existence of an output schema, the description is minimally sufficient. However, it lacks usage guidance and parameter semantics, which are important for an agent deciding whether to invoke this tool. Not complete enough for a fully self-contained description.
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 mention operation_id at all. The property title 'Operation Id' provides minimal meaning, and the phrase 'capability setup operation' indirectly refers to it, but the description does not compensate for the lack of explicit 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 action ('Request cancellation and cleanup') and the specific resource ('server-owned capability setup operation'). It distinguishes itself from sibling tools like start_capability_setup and get_capability_setup by focusing on cancellation.
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 cancelling a capability setup operation, but provides no explicit guidance on when to use it versus alternatives, nor any mention of conditions or prerequisites. The 'server-owned' qualifier hints at a specific context but is not explained.
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 already cover readOnly, destructive, and idempotent hints. The description adds the prerequisite 'explicitly registered' and the result 'evidence tables', which is useful but not rich. It does not disclose side effects such as table overwriting or whether the artifact is consumed.
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 wasted words. It efficiently conveys the core purpose and key prerequisite without 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 is concise and works with the existing annotations and output schema, but it lacks explicit parameter guidance and usage context. The 'explicitly registered' prerequisite is mentioned but not elaborated, leaving gaps for an agent to fully understand how to invoke the tool correctly.
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 meaning or relationship of run_id and artifact_id. The phrase 'registered OTLP file artifact' hints at artifact_id but provides no guidance on how run_id is used, making it insufficient for low 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 action ('Normalize'), the specific resource ('OTLP file artifact'), and the outcome ('into evidence tables'). It also distinguishes this tool from sibling extract tools by naming the OTLP artifact type.
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 explicitly registered OTLP file artifact needs normalization, but it does not explicitly state when to use this tool versus alternatives such as extract_inference_trace or extract_perfetto. No exclusions or alternative tool names are provided.
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?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds valuable behavioral context: the return value is 'bounded metadata' and an 'opaque resource URI', and it explicitly states 'never a host path or bytes', which is a meaningful security and format guarantee beyond the 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 key action ('Return') and includes a critical negative constraint. Every word is purposeful, with 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 simple getter with one parameter and an existing output schema, the description is mostly complete. It specifies the return boundary and the exclusion of host paths/bytes. It does not mention error conditions or prerequisites, but given the annotations and output schema, this is an adequate level of detail.
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 has one required parameter, artifact_id, with no description (0% coverage), and the description does not explain its format, source, or expected values. The parameter's purpose is partially inferable from the tool name, but the description fails to compensate for the schema's lack of detail.
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 'Return bounded metadata and an opaque resource URI' clearly specifies the tool's output and purpose, and the name 'get_artifact' reinforces that it retrieves a specific artifact. It distinguishes from siblings by explicitly excluding host paths and bytes, but it could have been more direct about 'get the artifact with the given ID'.
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 'never a host path or bytes' clause provides an implicit usage boundary: use this tool for metadata and opaque URIs, not for raw artifact content. However, no specific alternatives are named, and there is no explicit statement of when to use this versus other retrieval 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?
Annotations already declare readOnlyHint=true and idempotentHint=true, so the description is not required to restate safety. It adds context about 'bounded' and 'direct' callees, but does not explain cursor-based pagination or how 'source-linked' is resolved. This is acceptable but not extensive.
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 sentence front-loads the core action and key qualifiers. No redundant phrases 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 description is sufficient for a simple read-only query tool: output schema covers return structure, annotations cover safety, and the description conveys the essential scope. It could mention pagination or contrast with get_frame_callers, but the omissions are not critical given the schema and sibling 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 covers three of four parameters with descriptions (limit, frame_id, run_or_artifact), leaving cursor undocumented. The tool description mentions 'bounded', which aligns with limit, but adds no extra meaning for cursor or other parameters. With 75% schema coverage, the description is not a major additional source of 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 clearly identifies the tool's action: 'Return bounded source-linked direct callees for a frame.' It specifies a distinct resource (callees vs. callers) and includes qualifiers (bounded, direct) that differentiate it from sibling tools like get_frame_callers.
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 use this tool versus alternatives, such as get_frame_callers for the opposite relationship. The description also omits prerequisites like needing a frame_id from an analysis result, even though that is mentioned in the schema.
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?
Annotations already declare the tool read-only, idempotent, and non-destructive. The description adds useful context by stating results are 'bounded' and 'representative', implying a sampled subset rather than exhaustive output. However, it stops short of clarifying pagination behavior or the semantics of the cursor parameter, which could be relevant for large result sets.
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 verb and key qualifiers. Every word contributes to understanding the tool's purpose, with 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 description is adequate for a tool with read-only annotations and an output schema, but it leaves gaps: cursor/pagination is undocumented, and the term 'representative' is ambiguous. Given 4 parameters and the need to navigate pagination, a bit more context on how to use cursor or what 'representative' means would improve completeness.
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 75%, but the cursor parameter has no schema description and the tool description does not explain it. The description only reinforces 'limit' (bounded) and 'frame_id' (containing a frame), adding little new meaning beyond the schema. The cursor parameter remains undefined, which is a significant gap for a paginated tool.
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 ('Return'), names the resource ('stacks'), and qualifies the behavior ('bounded', 'representative', 'containing a frame'). This clearly distinguishes it from siblings like get_frame_callers and get_frame_callees, which focus on direct call relationships.
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 (e.g., get_frame_callers, get_trace_window). It does not mention exclusions, prerequisites, or typical use cases, leaving the agent to infer appropriate usage from the name and purpose.
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 already disclose readOnly, idempotent, and non-destructive behavior. The description adds 'bounded' and 'overlapping' semantics, but does not clarify pagination via cursor, ordering, or detailed boundary handling beyond 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?
A single, front-loaded sentence with no filler. Every word contributes to conveying the tool's action and scope.
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 strong annotations and an output schema, the description is adequate for basic selection. It omits pagination details, but those exist in the input schema, keeping overall completeness reasonably high.
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 80% (all parameters except cursor), so the schema carries most of the meaning. The description's 'overlapping' adds value by indicating slices crossing the window boundaries are returned, but cursor pagination semantics are left undocumented.
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 ('Return') and identifies the resource ('bounded trace slices') scoped to a time window. It is clear and suggests a read operation, but it does not explicitly differentiate from siblings like get_operation_window.
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 time-window context implies when to use the tool, but there is no explicit guidance on when to prefer it over alternatives such as get_operation_window or extract_otlp_trace, nor any 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 already declare the tool read-only, idempotent, and non-destructive. The description adds that it is 'diagnostic-only' and that it builds a plan rather than executing anything. However, it does not explicitly state that no profiling is started or that the plan must be run separately, which would be clearer. No contradiction with 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 entire description is a single 8-word sentence, front-loaded with the verb 'Build'. Every word earns its place; it is concise and well-structured.
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 (2 params, output schema present, strong annotations), the description is minimally viable but lacks some contextual guidance: it doesn't explain what the resulting plan is used for, nor that it should be followed by run_inference_profile. It also doesn't mention any prerequisites like server configuration. For such a simple tool, it is adequate but has clear 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 input schema has two required parameters with no descriptions (0% coverage). The description mentions 'one managed vLLM server' which partially clarifies server_name, but it does not mention the 'profiler' parameter or its enum values. Thus, the description fails to compensate for the lack of schema descriptions, leaving the agent to infer from the enum 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?
The description uses the specific verb 'Build' with the specific resource 'profile plan' and explicitly scopes to 'one managed vLLM server.' The phrase 'diagnostic-only' and the contrast with sibling 'run_inference_profile' clearly distinguish this planning tool from execution 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 states what the tool does but does not explicitly say when to use it or name alternatives. The word 'plan' implies it is a precursor to running a profile, but there is no mention of 'use run_inference_profile to execute this plan.' Thus, usage 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.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds a key behavioral detail not captured by annotations: it does not return native artifact content. This clarifies the output nature beyond the readOnlyHint, which only indicates safety. However, it does not elaborate on compatibility criteria or potential errors.
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 main verb and object. Every word contributes meaning, and 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?
For a comparison tool with two required parameters, an output schema, and rich annotations, the description is adequate but minimal. It clarifies that native artifact content is not returned, which is helpful, but it leaves 'compatible' ambiguous and does not explain the purpose of the comparison beyond the tool name. Given the output schema, the agent can infer return structure, so this is above the minimum but not fully fleshed out.
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 0% description coverage, so the description must compensate. While the parameter names (baseline_pipeline_id, candidate_pipeline_id) are fairly self-explanatory, the description adds only 'compatible ordered stages' which implies the two pipelines are expected to have compatible structure. It does not explicitly tie the parameters to their roles or explain any format expectations.
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 action ('Compare') and the object ('compatible ordered stages'), and the phrase 'without returning native artifact content' distinguishes it from artifact extraction tools. The tool name 'compare_artifact_pipelines' reinforces the resource being compared.
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. It does not mention scenarios where comparison is appropriate, nor does it reference similar tools like compare_run_sets or artifact extraction tools. The context from siblings is not exploited.
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 already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds 'immutable' and 'completed', which are useful but not deeply behaviorally rich. No contradiction with 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 filler. Every word adds value, and it is appropriately sized for the tool's simplicity.
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 read-by-id tool with a full output schema and strong annotations, the description is adequate. It conveys the essential nature of the operation, though it omits behavior for missing or invalid IDs, which is a minor gap.
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%, so the description should compensate by explaining result_id. It does not. The only parameter, result_id, is self-evidently an identifier, but no format, origin, or relationship to fault experiments is described.
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 the explicit verb 'Read' and specifies the exact resource: 'one immutable completed fault experiment result.' This clearly distinguishes it from sibling tools like plan_fault_experiment and run_fault_experiment, which operate at different stages.
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 word 'completed' implies the result must exist and be finished, but the description gives no explicit guidance on when to choose this tool over alternatives like get_experiment or list_experiment_trials. No exclusions or alternative tool mentions are provided.
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?
Annotations already cover safety (readOnlyHint, idempotentHint, destructiveHint). The description adds behavioral context beyond annotations by noting that pagination must preserve the original filters, which warns about a common misuse. No contradiction with 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 entire description is one sentence with two purposeful clauses. It front-loads the core purpose and adds a key pagination caveat without any filler 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 description plus annotations and rich input/output schemas cover most safety and structural aspects. However, it lacks a clear statement of when to use list_runs versus get_run or other run-related tools, and does not mention that 'limit' controls page size or that 'filter' is optional. It is minimally viable but leaves some usage context implicit.
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 provides almost no parameter-level detail. It mentions filters generically and refers to next_cursor, but does not explain the 'limit' parameter or the input 'cursor' parameter. With 0% schema description coverage and no property descriptions, the agent must infer semantics from the schema names alone, which for filter fields like lease_id may be opaque.
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 verb 'discover' combined with 'filtered run cohort' clearly indicates this is a list/search operation for runs with filtering. It is distinguishable from sibling tools like get_run, which targets a single run, though it doesn't explicitly name an alternative.
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 instruction 'follow next_cursor without changing filters' provides specific, actionable guidance on pagination, emphasizing that filters must remain constant during traversal. This gives clear usage context, though it doesn't explicitly state when to prefer this over other list or get 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?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is known. The description adds the specific evidence types (peak, retained-end, allocation) but does not disclose additional behavioral traits such as return format or edge cases. It provides some value beyond annotations but is not richly 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, front-loaded sentence that clearly states the action, resource, and evidence types. Every word earns its place, with no redundancy or filler. It is a model of conciseness.
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 presence of an output schema, full parameter descriptions, and annotations covering safety, the description is sufficiently complete for a read-only analysis tool. It does not need to explain return values, and the stated scope ('peak, retained-end, allocation evidence') gives adequate context. A minor gap is lack of explicit guidance on what constitutes a 'memory-profile run or artifact', but this is covered by discovery via list_runs/list_artifacts.
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 each parameter clearly described: limit (1-1000 max observations) and run_or_artifact (with discovery hint). The tool description adds no further meaning to parameters, so the baseline of 3 is appropriate; schema carries 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 ('Analyze') and names the resource ('memory-profile runs or artifacts') with clear focus areas ('peak, retained-end, allocation evidence'). This distinguishes it from sibling analysis tools like analyze_hotspots or analyze_execution, which target different evidence types.
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 need memory evidence from runs/artifacts) and the parameter hint to discover IDs via list_runs/list_artifacts provides some context. However, there is no explicit comparison to alternatives or stated exclusions, so it falls short of clear 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?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds valuable context about durability ('durable') and the timing ('after the original request disappears'), which goes beyond the annotations. It does not contradict the annotations and provides context that the state persists beyond the original request, aiding the agent's mental model.
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 conveys the core function and an important contextual detail. It is front-loaded with the verb 'Read' and resource, with no wasted words. Every part of the sentence adds meaningful 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 tool is simple (one parameter) and has a full output schema, so the description does not need to explain return values. It covers the key context of durability and timing, which is essential for correct usage. It could be slightly more explicit about what the state contains or the implication if called before disappearance, but overall it is adequate for the tool's complexity.
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 mention the 'operation_id' parameter or explain how it relates to the 'original request'. While the parameter name and title are somewhat self-explanatory, the description fails to compensate for the lack of schema descriptions, especially since it uses the phrase 'original request' without linking it to the parameter.
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 reads durable capability setup state, with a specific verb 'Read' and a specific resource 'capability setup state'. It distinguishes from siblings like 'start_capability_setup' and 'cancel_capability_setup' by focusing on reading, though it does not explicitly name those alternatives. The phrase 'after the original request disappears' adds temporal context but leaves some ambiguity about what exactly the state contains.
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 after the original request disappears, implying it is for retrieving persisted setup state. It does not explicitly mention alternatives or when not to use it, but the temporal condition is a useful guideline. Sibling tools like 'get_operation_window' or 'get_process_snapshot' are not referenced, so the guidance is moderate.
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 adds context beyond the annotations by revealing that the tool inspects 'allowed parameters and validation metadata,' which is a behavioral trait not covered by readOnlyHint or idempotentHint. It doesn't contradict the annotations and provides useful insight into what the operation does.
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 of ten words, front-loaded with the action and purpose. It is concise and free of filler, earning a top score.
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 nature of the tool (2 params, output schema available, annotations provided), the description is sufficient. It explains the core purpose and the follow-up action, while the output schema covers return values. A bit more detail about parameter semantics would elevate it, but it is not incomplete for a straightforward lookup 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?
Schema description coverage is 0%, so the description should compensate for the lack of parameter details. However, it only mentions 'allowed parameters' without explaining the purpose of 'kind' or 'name.' The enum and parameter names are self-explanatory to a degree, but the description does not explicitly connect them to the tool's function.
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 the verb 'Inspect' and specifies the resource ('declared workflow') via the tool name, while mentioning 'allowed parameters and validation metadata' as the focus. This clearly identifies the core function, though it doesn't explicitly differentiate from list_declared_workflows beyond implying a single-workflow lookup.
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 'then call the matching plan tool' provides a clear usage pattern: inspect metadata first, then proceed to planning. This gives the agent actionable guidance on when to use this tool, though it lacks explicit exclusions or alternatives.
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?
Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds the crucial behavioral trait that the command is never executed, which is essential because the tool name could suggest running it. It also hints at the 'installed' status, implying a dependency on 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, front-loaded sentence with no filler or redundant information. Every word earns its place, and the key behavior (return but not execute) is placed upfront.
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, the helpful annotations, and the existence of an output schema, the description is minimally adequate but leaves ambiguity about the meaning of 'native viewer command' and the role of artifact_id. It does not fully compensate for the lack of parameter semantics, but the overall context is sufficient for a basic understanding.
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 0% description coverage for artifact_id, and the description provides no information about what 'artifact_id' refers to or how it relates to the native viewer command. The single parameter's role is entirely unexplained, leaving the agent to infer from the name alone.
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 the verb 'Return' and the resource 'installed native viewer command', and explicitly clarifies 'never execute', which distinguishes it from execution-oriented sibling tools like execute_capture_plan. This is a specific and unambiguous purpose statement.
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 'but never execute' provides clear context that this tool is for planning/intent retrieval rather than execution, implying when to use it. However, it does not explicitly name alternatives or state when not to use it, leaving a minor gap in 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?
The annotations already declare read-only, idempotent, non-destructive, and open-world false, so the description doesn't need to cover safety. It adds the constraint that the run must be selected from list_runs, which is a useful behavioral detail, but it doesn't describe what 'hydrate' returns or any error 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 one short sentence that front-loads the primary purpose and includes an alternative in the second clause. Every word is meaningful; no waste.
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 simple with one parameter, output schema present, and strong annotations. The description adequately covers the core usage and distinguishes from siblings, though terms like 'hydrate' and 'bounded interpretation' are left unexplained. Overall, sufficient 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?
The schema has a single run_id with no description, and the tool description only hints that it comes from list_runs. This provides some context but doesn't fully explain the parameter format or constraints, leaving the agent to infer from the name and usage note.
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 the verb 'hydrate' to indicate loading a full run object, specifically one selected by list_runs, which distinguishes it from listing runs and from the analyze_* tools that provide interpretation. This is specific enough for an agent familiar with the domain.
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 explicitly states that get_run is for hydrating a run selected by list_runs, and that bounded interpretation should be done with analyze_* tools. This provides a clear when-to-use and an alternative, though it could be more explicit about not using it for interpretation.
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?
Annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior. The description adds a useful behavioral edge case about first-use recovery, beyond what annotations provide. No contradiction with 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?
One concise sentence with the main verb first, followed by a brief edge-case instruction. No filler or redundant 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?
With no parameters and an output schema, the description is fairly complete for a simple status query, but the 'WORKSPACE_NOT_FOUND recovery' instruction is cryptic and does not explain what recovery entails or how status values should be interpreted. Adequate but leaves some 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 schema coverage is 100%, so the description carries no parameter burden. The baseline for a no-parameter tool is met.
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 a specific verb+resource: 'Return workspace status.' It is clear about the tool's purpose, though it does not explicitly distinguish from sibling tools like validate_workspace or initialize_workspace.
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 one usage condition ('on first use, follow WORKSPACE_NOT_FOUND recovery') but does not explain when to use this tool versus alternatives, nor does it give exclusions. Usage context is only implied.
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 already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds 'read-only' (redundant with annotation) and the note that record_analysis is for preservation, implying this tool does not persist. This is minimal added context, but no contradiction exists, so the score reflects adequate coverage by 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 that states the purpose and an alternative without any fluff. Every word earns its place, and the structure is highly scannable.
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 terse and does not define 'compatible pair', which is essential for using comparison_run_or_artifact. It also does not position this tool among the many analyze_* siblings. However, the schema and output schema fill in the data contract, leaving the description adequate but with clear gaps in contextual 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 the parameters are already well-documented. The description's phrase 'execution-coverage runs or a compatible pair' hints at run_or_artifact and comparison_run_or_artifact but does not explain what makes a pair 'compatible'. Therefore, it adds no significant 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 clearly states the action ('Inspect') and the specific resource ('execution-coverage runs or a compatible pair'), and explicitly notes the read-only nature. It also distinguishes itself from the sibling record_analysis by directing preservation to that tool, leaving no ambiguity about its 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?
The description explicitly names record_analysis as the alternative for preservation, providing a clear when-not-to-use signal. It does not contrast with other analyze_* siblings, but the core use case is well-scoped. That meets the criteria for explicit alternatives, though not exhaustive exclusions.
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?
Annotations already declare readOnly, idempotent, and non-destructive behavior. The description adds useful context about the content scope (bounded, normalized, no prompt/error text), which goes beyond the annotations and helps set expectations.
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 core behavior and a key limitation. 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?
With a strong annotation set and an output schema present, the description is adequate for a straightforward list tool. It could clarify what 'bounded' and 'normalized' mean, but for simple pagination use, it is sufficiently complete.
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%, so the description must compensate. It does not explain run_id, limit, or cursor, nor does it explicitly map 'page through' to these parameters. The parameter names are somewhat self-explanatory, but the description adds minimal 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 clearly states the tool pages through 'bounded normalized inference requests' and specifies that it excludes prompt or error text. This distinguishes it from sibling extraction tools and conveys a specific verb and resource.
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: the tool is for listing inference requests with pagination, and the exclusion of prompt/error text hints that other tools should be used for those details. However, no explicit alternatives 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.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint, idempotentHint, and destructiveHint. The description adds behavioral context by requiring an explicit filtered cohort and indicating it is meant to follow list_runs. This goes beyond the annotations without contradiction.
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 packs essential information: action, resource, read-only nature, and workflow context. It is concise with no 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?
While output schema and annotations are present, the description does not clarify what 'analyze' produces (e.g., statistics, list of failures) or what constitutes a 'failure' (execution_status vs validation_status). This ambiguity leaves some gaps for such a complex 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?
Schema descriptions are completely absent (0% coverage), and the description only vaguely refers to an 'explicit filtered' cohort without explaining the filter fields or the role of the required 'limit' parameter. This does not sufficiently compensate for the lack of schema descriptions, especially given the complexity of the RunFilter object.
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 the action ('Analyze'), the resource ('explicit filtered failure cohort'), and the mode ('read-only'), which distinguishes it from sibling analysis tools like analyze_hotspots and analyze_memory. Adding 'after list_runs discovery' provides workflow context, making the purpose unambiguous.
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 clear usage context: use after list_runs discovery, and the phrase 'explicit filtered failure cohort' implies a filter is needed. However, it does not explicitly mention when not to use it or name alternative tools, so it falls 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.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and idempotentHint, but the description adds a valuable behavioral nuance: the tool does not collect missing trials. This goes beyond the generic read-only annotation and helps the agent understand the tool's scope of action, even though it doesn't describe return formats 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, grammatically complete sentence of eight words. It is front-loaded with the verb and contains no redundant or extraneous 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?
The tool is simple (one param) and has an output schema, so return value details are covered elsewhere. However, the description leaves ambiguity about what 'scaling' specifically refers to and what the summary includes, especially in the context of many sibling analyze_* tools. Basic guidance exists but lacks domain-specific 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 has one parameter (experiment_id) with no description, and the description does not explain what this ID refers to, how to obtain it, or any constraints. With 0% schema coverage, the description fails to compensate, leaving the agent to infer the parameter's meaning from 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 states a specific verb ('Summarize') and resource ('existing experiment'), and adds a distinguishing qualifier ('without collecting missing trials') that separates it from related tools like run_experiment or plan_experiment. This clearly identifies what the tool does and how it differs from siblings.
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 provides a clear usage context: use when you want to summarize an existing experiment. The phrase 'without collecting missing trials' serves as an exclusion, telling the agent not to use this tool if trial collection is needed. However, it does not explicitly name alternative tools, so it stops short of full 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?
Annotations already indicate it is a write operation (readOnlyHint=false), idempotent (idempotentHint=true), and non-destructive (destructiveHint=false). The description adds behavioral nuance by explaining the tool 'validates' the declaration and, crucially, does not start the server—information beyond what annotations alone convey.
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 with no fluff. It front-loads the core action and immediately conveys the key constraint ('without starting it'), 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.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
While an output schema exists and annotations cover basic safety, the description is too terse for a tool with 13 parameters and low schema coverage. It does not explain the create/replace distinction, mode dependencies, or what 'validated' entails, leaving gaps for complex usage.
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 provides no parameter information. With schema description coverage at only 31%, the burden falls on the tool description to explain key parameters, but it remains silent. The few schema descriptions (e.g., mode, workload) exist but are insufficient for a 13-parameter tool.
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: 'Create or replace one validated vLLM server declaration without starting it.' It uses specific verbs (create/replace), names the resource (vLLM server declaration), and includes the key constraint 'without starting it', distinguishing it from execution tools like run_inference_scenario.
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 'without starting it' provides clear context that this tool is for declarative configuration, not execution. However, it does not explicitly name alternatives or state when not to use this tool, so it falls 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?
Annotations already declare the tool as read-only, idempotent, and non-destructive, so the description does not need to reassert that. The description adds the traits 'bounded' and 'source-linked', which are useful behavioral hints not present in annotations. However, it does not describe pagination behavior (cursor) or the output format, where the output schema partially covers that.
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 verb 'Return', and every phrase ('bounded', 'source-linked', 'direct callers') adds meaningful qualifiers. No unnecessary 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?
Given that the tool has an output schema, annotations describing safety, and a schema covering 75% of parameters, the description is sufficient for a simple retrieval operation. It communicates the core purpose and limit-based bounding, though it omits explicit guidance on pagination or alternative-tool selection. Overall, it is adequate 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 75%, with limit, frame_id, and run_or_artifact already described in the schema. The description adds minimal parameter insight beyond the word 'bounded', which maps to the limit parameter. Cursor semantics remain unspecified in the description and are only structurally defined in the schema, but the high schema coverage sets a 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 ('Return') and clearly identifies the resource and scope ('bounded source-linked direct callers for a frame'). The term 'callers' naturally distinguishes it from the sibling tool 'get_frame_callees', so the purpose is unambiguous.
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 this tool: when you need direct callers of a frame. However, it does not explicitly mention alternatives or exclusions (e.g., 'for the reverse direction, use get_frame_callees'). The naming convention gives some context, but the description itself does not provide explicit guidance beyond the basic 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?
Annotations already declare read-only, idempotent, and non-destructive behavior. The description adds 'bounded page' (pagination) and 'immutable' (data stability), which are meaningful behavioral traits beyond what the annotations provide.
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 action and key qualifiers. Every word contributes value, with 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 simple read-only listing tool with a rich output schema and full annotations, the description covers core semantics. However, it omits how to navigate pagination (cursor usage) and whether ordering is defined, which would be useful given the cursor parameter.
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 0% description coverage, and the description does not explain the parameters. 'Bounded page' hints at limit/cursor but does not define them or explain pagination semantics. The parameter names are self-explanatory but not elaborated.
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 'Return' with a clear resource ('one bounded page of immutable trials') and explicitly scopes to 'an experiment'. This distinguishes it from sibling list/get tools like list_runs or get_experiment.
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 to retrieve trials for an experiment, but it does not provide explicit when-to-use/when-not-to-use guidance or name alternative tools. The scoping phrase 'for an experiment' is present but no exclusions are offered.
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?
Apart from annotations (all false), the description adds that planning neither downloads nor starts Toxiproxy and that Toxiproxy must be pre-prepared. This discloses some behavioral boundaries but leaves the side effects of 'binding' undefined—whether it creates persistent state, is idempotent, or modifies existing plans. With no annotation hints, more behavioral detail would be 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?
Two concise sentences: the first states the primary action, the second gives a critical prerequisite and non-behavior. No filler 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 provides the essential prerequisite and non-actions, and the schema covers parameter details; the output schema exists so return values are not needed. However, the exact meaning of 'bind' and post-planning steps (e.g., run_fault_experiment) are left implicit, which is acceptable given the tool's focused role but not fully explicit.
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 descriptions, including guidance to inspect get_declared_workflow and source IDs from other tools. The description adds no parameter-specific information, so the baseline of 3 applies given the schema's completeness.
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 binding a declared loopback Toxiproxy experiment with its toxic scenarios, using a specific action ('bind') and target. It differentiates from siblings by noting that planning neither downloads nor starts Toxiproxy, which separates it from start_capability_setup and run_fault_experiment.
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 explicitly states that Toxiproxy must already be prepared by start_capability_setup, indicating this tool is for the planning phase after setup. It clarifies what the tool does not do (download/start), providing context for when to use it versus setup/run tools. However, it doesn't explicitly name alternative tools for execution.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint=false, idempotentHint=true, and destructiveHint=false. The description builds on this by adding non-obvious behavioral details: it 'preserves existing workloads and experiments,' 'never executes the command,' and 'returns the next discovery step.' These disclose side-effect scope and non-execution, going beyond the structured hints. No contradiction exists.
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 and front-loaded with the primary purpose. It repeats the 'without executing' idea twice ('without executing it' and 'It never executes the command'), which is slightly redundant but not wasteful. Overall, it earns its sentences in a short, readable format.
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 explains the tool's immediate behavior and one update scenario, but lacks broader workflow context. It does not explain how configure_workload fits with sibling tools like run_experiment or plan_experiment, what 'validated' entails, or how to use the create operation effectively. Given the tool's complexity and the rich sibling set, this is a notable gap.
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 only 17%, so the description must compensate. Yet it only explains one usage pattern involving operation and a 'current configuration_id' (which likely refers to expected_configuration_id, but uses an imprecise name). The other 11 parameters—name, argv, cwd, oracle, identity, requirements, etc.—receive no added explanation, leaving a significant gap for such a complex input 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 opens with a clear verb-resource pair: 'Write one validated named workload without executing it.' It immediately distinguishes this configuration tool from execution-oriented siblings by stating 'It never executes the command,' and further clarifies its scope with 'Writes only the project workload configuration.' This 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 Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides a concrete usage pattern: 'Use operation='replace' with the current configuration_id to update an existing workload.' This gives clear context for the update case. However, it does not explicitly name alternatives (e.g., run_experiment for execution) or state when not to use the tool, so it falls 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.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With annotations providing no meaningful safety signals (all false), the description carries the full burden and does so admirably. It discloses atomic bundling, sidecar discovery from the primary JSON, rejection of arbitrary sibling files, and float32 byte-length verification after import—beyond what a simple 'imports' statement would provide.
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 purpose is front-loaded in the first sentence, and the two following sentences add concrete behavioral value without repetition or fluff. The description is compact yet information-dense.
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 covers the core import workflow, sidecar selection, and size verification. It omits guidance on sensitivity or source_root semantics, but since an output schema exists and the described behavior is enough to select the tool, this remains slightly above the minimum viable level.
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 explain any parameter semantics. Schema coverage is 50% (only path and expected_sha256 have descriptions), while sensitivity and source_root remain undocumented. Given the partial schema coverage, the description should compensate but does not.
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 and resource: 'Import an NVBench JSON and its provider-declared sidecars as one atomic bundle.' This clearly states what the tool does and distinguishes it from sibling extraction tools by emphasizing the atomic import bundle behavior.
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 an import workflow and details sidecar handling, but it never explicitly says when to use this tool instead of alternatives like extract_nvbench. The context is clear, but there are no exclusions or alternative recommendations.
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?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, but the description adds meaningful context about informational-only fields in global mode and the safety property that setup never executes a workload. This enriches behavior understanding beyond the annotations.
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 front-loaded with the core purpose and then adds necessary clarifications. It is somewhat verbose but each sentence contributes useful behavioral guidance, so no sentence is wasted.
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 output schema exists, the description does not need to detail return values. It covers the key contexts: global vs. adapter-scoped, and the safety of managed setup. Missing mode semantics is a minor gap but does not make the tool unusable.
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 documents the adapter parameter with a clear description, and the description reinforces its meaning, including the effect of omitting it. However, the mode parameter (passive, active_cached, active_refresh) is only an enum with no explanation in schema or description, leaving a semantic gap.
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 'List capabilities and setup actions scoped to a selected capture adapter,' which is a specific verb and resource. It also distinguishes the global read-only mode from adapter-scoped mode, setting it apart from sibling tools like start_capability_setup and get_capability_setup.
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 gives clear guidance: omit adapter for a read-only inventory, and select an adapter before mutating the managed environment. It also notes that managed setup never executes a workload, though it does not name alternative tools explicitly.
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 confirms this is a write operation ('Persist'), aligning with readOnlyHint=false. It adds the qualifier 'reviewed', implying a workflow prerequisite, but does not elaborate on side effects or idempotency. Since annotations already provide idempotentHint=false and destructiveHint=false, the description adds minimal extra 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 with no waste, front-loading the action and immediately providing the alternative. It is highly concise and well-structured.
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 covers tool selection and the core persistence action, relying on the schema for invocation details. The schema name 'CompareRunSetsRequest' and output schema provide additional context. However, it does not explicitly mention the two request variants or that the request should mirror compare_run_sets, leaving some gaps for a complex 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?
The schema has 0% description coverage and the description does not mention any parameter specifics. The term 'comparison' gives a vague hint, but the agent receives no guidance on which request variant to use or how fields relate. This fails to compensate for the lack of schema 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 clearly states the tool's purpose with a specific verb ('Persist') and resource ('comparison'), and distinguishes it from the sibling tool 'compare_run_sets' by labeling that as 'read-only preview'. This leaves no ambiguity about what the tool does.
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?
The description explicitly instructs to 'use compare_run_sets for read-only preview', providing a direct alternative and clarifying when not to use this tool. This is clear guidance on tool 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?
Beyond the annotations (destructive, idempotent, open world), the description adds that cancellation is limited to the exact detached task owned by this server, which is meaningful behavioral context. It also reinforces idempotency in natural language, though that is already in 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?
A single sentence of 12 words contains all essential information: action, scope, and idempotency. Every word earns its place with no filler, 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.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple schema (one required parameter), existing annotations, and presence of an output schema, the description covers the primary purpose and key behavior. It does not detail edge cases (e.g., if task already completed) but is reasonably complete for a simple cancellation 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 has no parameter description (0% coverage), so the description must compensate. It implies that run_id identifies the exact detached task ('Cancel only the exact detached task'), but does not explicitly explain run_id's format or origin. This is adequate but minimal for a single-parameter tool.
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 action ('Cancel') and the specific resource ('the exact detached task owned by this server'), which is precise and distinguishes it from sibling tools like cancel_capability_setup. The qualifier 'only the exact...owned by this server' adds scope and avoids ambiguity.
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 conveys when to use the tool: to cancel a specific detached task belonging to this server. It also notes that repeated calls are safe, implying idempotent usage. However, it does not explicitly name alternatives or exclusions beyond the scoping, so it misses full marks.
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 adds valuable behavioral context beyond the annotations by stating that the operation has 'no persistence' and is a 'preview'. This goes beyond the readOnlyHint and idempotentHint, clarifying that it does not save anything. It is concise but informative.
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 exactly two sentences, front-loading the core purpose and then pointing to the alternative. Every word earns its place, with no redundancy or filler. This is an ideal structure for a tool description.
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 that annotations cover safety and an output schema exists, the description is minimally adequate for a read-only preview tool. However, it fails to explain what 'compatible' cohorts means, what prerequisites exist (e.g., run sets must be frozen), or any details about the comparison scope. The description is complete enough for a basic understanding but lacks depth for this complex oneOf schema.
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 has 0% description coverage and the description provides no information about the 'request' parameter or its sub-fields. While the schema names parameters like 'baseline_run_set_id' and 'candidate_run_set_id', their meaning, relationships, and selection criteria are unexplained. The description does not compensate for the lack of parameter documentation.
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 'preview' and resource 'compatible frozen cohorts', clearly indicating it does a dry-run comparison without saving. It also explicitly differentiates from the sibling tool 'record_comparison', which is used to persist comparisons. This makes the tool's 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 Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly tells the agent to use 'record_comparison' when persistence is needed, providing a clear alternative and exclusion. It also implies this tool is for previewing, giving clear contextual guidance on when 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?
Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, covering the safety profile. The description adds meaningful context by describing it as 'Reconnect to bounded progress and lifecycle status', indicating that the tool provides progress and lifecycle information, not just the raw capture data. This goes beyond the tool name and helps set expectations, though it doesn't detail edge cases like invalid run_id.
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 action 'Reconnect', and every word contributes meaning. There is no redundancy, filler, or overly technical jargon. It is concise and well-structured.
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 low complexity (one param), the presence of an output schema, and strong annotations, the description is largely complete. It states what the tool does and what statuses it returns. It could be more explicit about the exact meaning of 'bounded progress', but the output schema likely covers return structure, so no critical information is missing.
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 has one required parameter run_id with no description (coverage 0%). The description compensates by specifying 'for one detached run', which directly links run_id to a detached capture run. This adds clarity beyond the schema's bare 'Run Id' and disambiguates from general run IDs. Despite not explaining where to obtain run_id, the single-param context is simple enough that this 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 'Reconnect' and resource 'one detached run', and further specifies what it provides: 'bounded progress and lifecycle status'. This clearly distinguishes it from siblings like start_detached_capture or cancel_detached_capture, which are about starting or stopping captures, and from generic get_run which doesn't target detached captures.
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 tool's usage is implied by the description: it is for reconnecting to status of a detached run. However, there is no explicit when-to-use vs alternatives, no mention of alternatives like get_run or start_detached_capture. It does not state exclusions or prerequisites, so it falls to 'implied usage' rather than 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?
Annotations already provide idempotentHint=true and destructiveHint=false, so the description adds the precondition about verification. It does not detail side effects like file changes or workspace state modifications, but given the annotation coverage, it meets a minimum viable level.
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 redundancy. Every word contributes meaning, efficiently conveying action, target, and precondition.
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 an output schema present, return values need not be described. The 0-parameter schema and annotations cover safety and idempotency. The description adds the essential verification prerequisite, making the tool well specified for its 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 tool takes zero parameters, and the description explains the fixed project root context, making the lack of parameters intuitive. The baseline for 0 params is 4, and the description does not need to compensate for missing schema 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 identifies the action ('Initialize'), the target ('Flameox'), and the scope ('fixed project root'). It also specifies a precondition ('after it has been verified'), making it distinct from sibling tools like validate_workspace or workspace_status.
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 usage time: after verification. However, it does not explicitly mention alternatives or when not to use the tool, so it lacks the explicit exclusions that would merit a 5.
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 adds the behavioral guarantee 'never runs them' beyond the annotations, which already mark it as read-only and non-destructive. This is useful context for the agent, but it does not address pagination or other edge-case 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 two sentences, front-loaded with the core purpose, and avoids redundancy. There is no wasted text.
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 covers default behavior, kind variants, and safety, while the output schema handles return values. It lacks explicit pagination details, but for a simple list tool with rich annotations, 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 0% description coverage, so the description must compensate for parameter semantics. It explains the 'kind' parameter by listing values and their effect, but it does not explain 'limit' or 'cursor' beyond their schema titles and defaults. This partial compensation places it at a mid-level.
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 the verb 'Discover' and specifies the resource 'declared workflows', with explicit clarification that it never runs them. This distinguishes it from execution tools like run_experiment and retrieval tools like get_declared_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?
It says 'before planning', implying the appropriate context for use. It also states 'this never runs them', which tells the agent this is a safe read-only discovery operation. However, it does not explicitly name alternative tools or exclusions.
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 adds the 'single-use plan' trait, indicating the plan is consumed by execution. This complements the annotations (destructiveHint=true, readOnlyHint=false) without contradiction, and clarifies an important side effect beyond what annotations provide.
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 concise sentence that front-loads the action and includes the key post-condition. No wasted words or redundant 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?
The description covers the core action, notes the single-use nature, and points to get_experiment for result inspection. Given the tool's simplicity and existing annotations, this is sufficiently complete. It lacks explicit prerequisites but these are inferable from workflow 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 schema has 0% description coverage for plan_id. The description indirectly refers to 'one single-use plan', which implies the parameter is the plan ID, but does not explicitly explain its source, format, or how to obtain it. This is minimal viable guidance but leaves ambiguity.
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 'Execute' and resource 'all current trials from one single-use plan', clearly distinguishing this from sibling tools like plan_experiment (plan creation) and get_experiment (result inspection). It also states the follow-up step, reinforcing its role in the 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 implies the tool is used after a plan exists and advises inspecting get_experiment afterwards. It does not explicitly mention alternatives or exclusions, but the context is clear enough for an agent to infer when to use 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?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is clear. The description adds that hotspots are 'bounded' and 'source-linked,' offering some context beyond annotations, but does not detail output behavior or side effects. This matches the mid-range where annotations carry the core burden.
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 includes the alternative in the second sentence. Every word earns its place with no fluff.
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?
The tool is simple (2 params, output schema present), and the description fully covers purpose, use case, and alternatives. With annotations declaring safety traits and an output schema defining the return structure, no additional behavior explanation is needed.
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 'run_or_artifact' and 'limit'. The tool description adds no parameter-specific meaning beyond the schema, 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 clearly identifies the action (analyze), the resource (sampled-profile runs or artifacts), and the result (bounded source-linked hotspots). It also differentiates from sibling tools by explicitly naming extract_pyperf/query_measurements as the alternative for benchmark_samples.
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?
The description provides direct when-to-use guidance ('sampled-profile runs or artifacts') and an explicit exclusion ('use extract_pyperf/query_measurements for benchmark_samples instead'). This tells the agent when to prefer other 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?
The description adds meaningful behavioral context beyond annotations: it explicitly states the tool never triggers extraction and gives a recovery path if data is missing. This is valuable because it prevents the agent from assuming the tool will handle raw traces or extraction. Although annotations already declare readOnlyHint and idempotentHint, the description enriches the behavioral model with the 'never extracts implicitly' caveat and the typed recovery result guidance.
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 highly concise: two sentences with no filler. The first sentence front-loads the primary purpose, and the second delivers an essential usage caveat. Every word earns its place, and the structure is ideal for quick parsing by an AI agent.
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 (2 parameters) and the presence of an output schema, the description is sufficiently complete. It covers purpose, usage timing, and fallback behavior. The only minor gap is that it doesn't describe what the summary output contains, but that is likely covered by the output schema. The reference to a 'typed recovery result' is slightly opaque but 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 coverage is 100% for both parameters, and the schema descriptions are already descriptive: 'Run ID or artifact ID for an imported torch.profiler trace' and 'Maximum operators to return (1-1000).' The description adds no further parameter-specific details beyond restating the input domain. Baseline of 3 is appropriate because the schema carries the 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 clearly states the tool's function: 'Summarize normalized Perfetto evidence from a torch.profiler run or artifact.' The verb 'Summarize' and resource 'normalized Perfetto evidence' are specific, and the domain (torch.profiler) distinguishes it from sibling analyze_* tools. The reference to extract_perfetto further clarifies its role as the analysis counterpart.
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?
The description provides explicit guidance: it is read-only and 'never extracts implicitly.' It also tells the agent what to do when normalized rows are absent: 'follow the typed recovery result and call extract_perfetto for the exact run.' This clearly differentiates when to use this tool versus extract_perfetto, and implies it should be used on existing normalized data rather than raw traces.
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?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint false. The description adds the valuable context 'without probing or execution,' which goes beyond the annotations by specifying that no probing or execution occurs. This is useful and aligns with the annotation hints.
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 filler. It front-loads the verb and resource, and the qualifier 'without probing or execution' is efficiently placed. 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 zero-parameter, read-only list tool with output schema and strong annotations, the description is fully sufficient. It specifies what is listed and that no probing/execution occurs, covering all necessary context for an agent.
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 input schema has zero parameters, so there is nothing to describe. Per baseline rules for 0-parameter tools, a score of 4 is appropriate. The description correctly focuses on the operation rather than arguments.
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 'List' plus resource 'declared inference servers and scenarios,' clearly distinguishing it from execution-oriented siblings like run_inference_scenario and configure_inference_*. The phrase 'without probing or execution' further differentiates this from tools that inspect or execute.
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 to see declared configurations without probing or executing. While it doesn't explicitly name alternatives, the 'without probing or execution' phrase implies when not to use it (e.g., when execution is needed). This 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.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses that the action 'records agent-created provenance under the workspace lock' and explicitly negates installation/import/execution, enriching the idempotentHint and non-destructive annotations. No contradiction exists; the lock and provenance details go beyond the structured 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?
Three short sentences front-load the core action and then add necessary safety and workflow context. There is no filler, repetition, or unnecessary elaboration.
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 the simple two-parameter interface, rich annotations, and an output schema, the description covers the operation's effects, exclusions, and next step. 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 describes both parameters precisely: adapter is 'returned by list_capabilities' and distribution is the 'exact installed distribution name reported for this adapter.' The description adds only the general notion of 'exact installed package identity' without syntax or format details, 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 opens with 'Approve one installed third-party adapter by exact installed package identity,' giving a specific verb and resource. It clearly distinguishes the approval action from installation, importing, or executing a workload.
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 provides workflow guidance by instructing 'Call list_capabilities again' and clarifies that the tool does not install, import, or execute a workload. However, it does not explicitly name alternative tools or state when not to use it, leaving some usage context implied.
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 adds valuable behavioral detail beyond annotations: it discloses that only flameox.toml requirements are installed, that the tool never executes the workload, and that the result includes an active preflight plus a recommendation to plan or inspect. This aligns with annotations (readOnlyHint false, idempotentHint true) and provides context for the agent's next action.
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, each with dedicated purpose: action, scope constraint, and outcome/next-step. No filler or redundancy.
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 single-parameter tool with an output schema, the description covers the action, constraints, non-execution, and subsequent decision guidance. It gives enough for an agent to invoke correctly and interpret the result, especially with the output schema available.
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% with a clear description of workload_name. The tool description adds the crucial nuance that only dependencies already declared in flameox.toml are considered, refining the meaning of the parameter beyond the schema's generic wording.
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 a concrete action: install declared workload Python distributions into the active managed runtime. It clarifies scope (only requirements in flameox.toml) and explicitly differentiates from execution (never executes a workload), separating it from sibling run_experiment 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 guidance on what the tool does and the decision after calling it (plan or inspect a remaining host capability), and it explicitly excludes workload execution. However, it does not name alternative sibling tools for execution or configuration, so it stops short of explicit when/when-not comparisons.
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?
Beyond annotations, the description discloses automatic trace detection ('identified automatically') and ambiguity handling ('set producer='torch.profiler' for ambiguous'), adding useful behavioral context. Annotations indicate a non-readonly, non-idempotent, non-destructive operation, and the description does not contradict this.
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 (three sentences), front-loaded with the primary purpose, and each additional sentence provides actionable guidance without redundancy. No fluff or tangential 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 complexity (7 parameters, 3 required) and the presence of an output schema, the description covers the critical workflow context: import → extract_perfetto → analyze_pytorch. It doesn't explain all edge cases (e.g., import conflicts), but the schema and sibling context fill most gaps.
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 high (86%), with detailed parameter descriptions already present. The description adds contextual value by mapping kind to execution_trace for Chrome/Torch traces and producer to torch.profiler for ambiguous cases, which is beyond the schema's generic enum 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 states a specific action and resource: 'Import one project-local artifact and preserve producer identity.' This clearly distinguishes the tool from sibling extract/analyze tools by focusing on the import step and identity preservation.
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?
Provides explicit procedural guidance: 'Use kind='execution_trace' for Chrome/Torch traces, then run extract_perfetto before analyze_pytorch' and 'If detection is ambiguous, set producer='torch.profiler'.' This tells the agent exactly when and how to use the tool, including naming the next pipeline steps.
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?
Annotations already indicate idempotentHint=true, readOnly=false, and destructive=false. The description adds behavioral context beyond this, such as the operation being 'detached', returning a 'durable operation ID', and that it creates 'owned work' that can be cleaned up via cancel_capability_setup. No contradiction with 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 three sentences, front-loaded with the primary purpose. Each sentence earns its place: purpose, idempotency usage, and follow-up workflow. 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?
The tool is well-covered by annotations and output schema. The description explains the detached nature, durable ID, and polling/cancel flow, which is sufficient for a start-operation tool. It could mention prerequisites like listing capabilities first, but the adapter description already hints at that by referencing list_capabilities.
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%, so baseline is 3. The description adds extra meaning for idempotency_key by explaining its reconnect use-case, which goes beyond the schema's 'Stable key for replaying this exact request.' For adapters, it references list_capabilities as the source, reinforcing the enum values without repeating them.
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 and resource: 'Start detached capability provisioning and return its durable operation ID.' This clearly states the tool's function and distinguishes it from sibling tools like get_capability_setup (poll status) and cancel_capability_setup (cleanup), which are explicitly mentioned.
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?
The description provides explicit usage guidance: 'Use the same idempotency key to reconnect after a lost request' explains how to handle connectivity issues. It also directs the agent to 'Poll get_capability_setup' and 'cancel_capability_setup requests cleanup', giving clear follow-up actions and alternative 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?
Annotations already declare readOnlyHint=true and destructiveHint=false, and the description reinforces this with 'without writing or executing anything.' It adds useful detail beyond annotations: 'Invalid configuration is reported without replacement,' explaining what the tool does in failure cases and that it doesn't modify configuration. No contradictions.
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 tight: three short sentences, each adding distinct value (scope, usage point, failure behavior). No redundant phrasing or restating of the name.
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 the tool's zero-parameter input, rich annotations, and the existence of an output schema, the description fully covers the essential context. It explains the intended use case and the decision workflow, leaving no operational gaps for an agent.
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 the input schema is empty. With no parameters, schema coverage is trivially 100%, and the description has no need to elaborate on parameter semantics; it intentionally focuses on the tool's behavior and role. Baseline 4 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 the specific verb 'Inspect' and the resource 'flameox.toml', immediately clarifying the tool's scope (read-only inspection of workload configuration). It also distinguishes itself from siblings by explicitly positioning the tool as the decision point between configure_workload and list_declared_workflows.
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?
It states exactly when to use: 'after workspace initialization' to decide between configure_workload or list_declared_workflows. This is explicit usage guidance naming sibling tools, satisfying the dimension.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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