design-review-mcp
Server Quality Checklist
Latest release: v0.2.0
- Disambiguation5/5
Each tool has a clearly distinct purpose, even among similar groups like list_* tools (e.g., list_adapters vs list_regions) and review_* tools (review_code is a wrapper for review_document with code type, clearly explained). Memory management tools (mark_advice, mark_finding, record_experience, etc.) are well-differentiated. No ambiguity between tools.
Naming Consistency5/5Tool names follow a consistent verb_noun pattern (e.g., apply_text_patch, list_regions, mark_finding, review_document). Exceptions like 'inspect' and 'ping' are single verbs but are standard in many APIs. No mixing of camelCase or snake_case, all lowercase with underscores.
Tool Count4/533 tools is on the higher side but justified given the server's broad scope (design review, code review, planning, consultation, memory management, file operations, system diagnostics). The tools cover many aspects without being excessive. A few tools like list_defaults and list_skills might be rarely used, but overall the count is acceptable.
Completeness5/5The tool surface appears complete for the domain of design review: reading and searching workspace files, applying patches, planning tasks, consulting external experts, reviewing documents/code/plans, recording and managing experiences, marking feedback, inspecting system state, and managing memory. There are no obvious gaps like missing CRUD operations, as the server focuses on review and feedback rather than full file management.
Average 3.4/5 across 33 of 33 tools scored. Lowest: 1.9/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 227 commits in the last 12 weeks
- Last stable release on
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
This repository is licensed under Apache 2.0.
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.
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glama.jsonto the root of your repository:{ "$schema": "https://glama.ai/mcp/schemas/server.json", "maintainers": [ "your-github-username" ] }Then . Browse examples.
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How is the quality score calculated?
The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).
Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.
Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).
Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.
Tool Scores
- Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It does not disclose behavioral traits such as whether it modifies data, requires permissions, or has side effects. The description is silent on behavior beyond the basic action.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very short (two sentences), which is concise. However, it sacrifices essential information for brevity, leaving most questions unanswered. It is not front-loaded with the most critical details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 9 parameters, no annotations, and no output schema, the description is completely inadequate. It does not explain parameters, return values, or usage context. The agent cannot reliably invoke this tool based solely on the description.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%. The tool description adds no meaning to any of the 9 parameters. It does not explain what 'files', 'panel', 'effort', etc., represent or how they affect the review.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states it reviews code implementations, which is a specific verb+resource. However, it explicitly states equivalence to review_document, creating confusion about why this separate tool exists. It does not distinguish itself from siblings like review_document or review_plan.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description only says to use for code review, but no guidance on when not to use it or alternatives. It mentions equivalence to review_document but does not clarify when to choose this over review_document.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits. It mentions workspace restrictions but does not state if the tool is read-only, how it handles non-UTF-8 files, or potential resource limits. The brief description omits critical transparency details about side effects, permissions, or rate limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5Is the description appropriately sized, front-loaded, and free of redundancy?
While the description is a single short sentence, it is under-specified rather than concisely informative. It lacks structure such as separating purpose from usage or behavioral notes. Being too brief for a complex tool reduces effectiveness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool complexity (9 parameters, no output schema, no annotations), the description is extremely incomplete. It does not indicate return format (e.g., list of matches, file paths, context lines), pagination, error handling, or how glob patterns work. The agent cannot fully understand how to use the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema parameter description coverage is 0%, yet the description fails to explain any of the 9 parameters (e.g., query, root, regex, max_results, context_lines, exclude_globs, include_globs, case_sensitive, max_file_bytes). The agent must rely solely on the schema titles, which are minimal ('Query', 'Regex', etc.). This is insufficient for correct usage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('search') and resource ('UTF-8 text files') and the scope ('inside allowed workspace roots'). It distinguishes from sibling tools like 'read_text' (which reads entire files) by focusing on searching. However, it does not specify that it supports regex or case-sensitive search, which could disambiguate from simpler search tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'read_text' or 'inspect'. No context for when to prefer search_text over other file reading or consultation tools. The agent is left to infer usage without explicit when-to-use or when-not-to-use instructions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It mentions the sha256 guard but does not disclose behavior on hash mismatch, whether the operation is destructive, permissions needed, or rollback possibilities.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single clear sentence, but it is too brief. It could include essential parameter context without becoming verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has 5 parameters, no output schema, and no annotations. The description fails to explain the replacements format, dry_run behavior, diff byte limit, or the sha256 guard mechanism, making it inadequate for correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, yet the description adds no information about parameters like path, dry_run, replacements, max_diff_bytes, or expected_sha256. The agent gets no help beyond the bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool applies exact UTF-8 text replacements with a sha256 guard, distinguishing it from reading or searching tools like read_text and search_text.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives, no prerequisites or when-not-to-use conditions. The agent must infer usage from the name and schema alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits but only states the action. It does not mention read-only nature, authentication needs, or side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that is short and to the point, but it could benefit from additional structure.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given one parameter and no output schema, the description lacks completeness. It does not explain what reviewer roles are, how the adapter parameter affects results, or what the output format is.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0% and the description does not mention the 'adapter' parameter at all, failing to add meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states it lists available reviewer roles and mentions 'core general + adapter specific', making the purpose clear. However, it does not differentiate from siblings like list_consultants or list_adapters.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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_consultants or list_adapters. The description lacks context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must convey behavioral traits. It states the tool runs a command but does not disclose side effects, failure modes, security implications, or output handling. This is insufficient for a command execution tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence with no redundancy. However, it sacrifices necessary detail for brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 4 parameters, no output schema, and no annotations, the description is far from complete. It lacks essential information about command formats, allowed workspaces, and expected outputs, making it inadequate for safe and effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description must explain parameters. It does not mention any parameter, leaving 'argv', 'cwd', 'timeout_sec', and 'max_output_chars' entirely unexplained. The agent cannot infer what values to provide.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool runs an 'allowed test/lint check command' inside an 'allowed workspace root'. It provides a specific verb and resource, and it distinguishes itself from sibling tools (none of which execute commands). However, the term 'allowed' is vague and not elaborated, reducing clarity slightly.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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. There is no mention of prerequisites, like how to determine which commands or workspace roots are allowed, or scenarios where this tool should be avoided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure, yet it says nothing about side effects, permissions, rate limits, cost, or any other behavioral traits beyond the basic action.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short (two sentences) and front-loaded with the main action. No words are wasted, but it could be expanded slightly to cover more essentials without losing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 9 parameters and no output schema, the description is extremely incomplete. It fails to explain how parameters are used, what the output looks like, or any contextual details necessary for proper invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description adds no meaning to any of the 9 parameters. It does not explain what panel, effort, adapter, dimensions, max_cost_usd, extra_context, output_format, or retrieve_top_k represent, leaving the agent guessing.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it reviews plans (implementation plans) in 'design-question mode' and equates it to review_document with document_type='markdown'. The verb and resource are specific, and the equivalence to a sibling tool is mentioned, though it does not fully differentiate itself.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for reviewing plans as markdown documents via the equivalence statement, but it provides no explicit when-to-use or when-not-to-use guidance, nor does it mention alternatives beyond the implied sibling.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It only states the output fields and gives no behavioral details such as default behavior, read-only nature, pagination, or side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence that front-loads the action and output fields. It is efficient with no unnecessary text, though it could be slightly expanded to include parameter context without losing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one optional parameter and no output schema, the description mentions the output fields which is helpful. However, it omits the parameter entirely (adapter), leaving a gap in completeness. Overall adequate but not fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0% (the description does not mention the 'adapter' parameter at all). With low coverage, the description must compensate, but it fails to add any meaning beyond the schema. The optional parameter with default 'auto' remains unexplained.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists knowledge base case indices and specifies the fields returned (id, title, category, triggers). This is specific verb+resource, and while it doesn't explicitly distinguish from sibling list_* tools, the resource 'knowledge base case index' is distinct enough for unambiguous purpose understanding.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 list_adapters or list_consultants. The description does not include any context, prerequisites, or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose any behavioral traits beyond being a read-only listing operation. There is no information about performance, caching, side effects, authentication requirements, or rate limits. For a zero-parametric tool, the absence of this context is acceptable but does not add value beyond the obvious.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is concise and to the point. However, it is in Chinese, which may reduce clarity for an English-dominant agent. The sentence can be restructured to be more front-loaded with an English translation, but it is not verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has no output schema, so the description must compensate by explaining what is returned. It states it lists 'available ProjectAdapter + auto detection results', which gives a general idea but lacks specifics on format or structure. For a simple list tool with no parameters, this is minimally adequate, but more detail (e.g., example items or schema) would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are no parameters, and the schema coverage is 100%. The description is not required to add parameter information, and it does not. With zero parameters, the baseline score is 4, and the description meets that baseline adequately.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists 'available ProjectAdapter + auto detection results', specifying the resource being listed. While the resource name is somewhat technical and in Chinese, it differentiates from sibling list tools which list different entities (e.g., consultants, defaults). A clearer English description or example of what 'ProjectAdapter' represents would improve specificity, but the purpose is effectively communicated.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 numerous sibling list tools (e.g., list_consultants, list_skills). There is no mention of prerequisites, context, or alternatives. An agent would have no basis to choose this over other list_* tools based solely on the description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavior. It states the output (cache statistics) but does not mention side effects, auth requirements, rate limits, or whether it is read-only. For a stateless query tool, the description partially fulfills transparency but has gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that conveys the core functionality without excess words. It is efficient and front-loaded with the key information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has no parameters and no output schema, the description provides the basic output but lacks context about the panel concept or return format. It is minimally adequate but could explain the 'panel' term and provide example output.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are zero parameters, so the schema coverage is 100%. The description adds meaning by explaining what the tool returns, which is sufficient since no parameters exist.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states that the tool provides cache statistics for reviews, including total reviews and duplicate reviews saved by cache hits. The verb 'stats' and resource 'panel' are specific, but the meaning of 'panel' is ambiguous. However, it distinguishes itself from sibling review tools by focusing on cache statistics.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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. There are no prerequisites or exclusions mentioned. The tool is simple with no parameters, but the description lacks any contextual usage advice.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full responsibility for behavioral transparency. It only states that the tool does not return file contents, but omits details on what it does return (e.g., metadata, existence check) and whether there are any side effects or required permissions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is 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 action and a critical constraint.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one parameter, no output schema) and the presence of many sibling tools, the description provides basic differentiation but lacks enough detail for full contextual completeness. It doesn't explain the return format or how the tool integrates with other workspace tools, which is necessary for agents to use it effectively without additional information.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does 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 mentions 'allowed workspace file' but does not elaborate on the 'path' parameter's format, constraints, or relationship to workspace roots. The parameter's purpose is implied but not explicitly clarified beyond the schema's minimal field name.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description specifies the verb 'inspect' and the resource 'workspace file', and adds the key constraint 'without returning contents', which clearly distinguishes it from sibling tools like 'read_text'. This is specific and helps the agent understand the tool's unique purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not explicitly state when to use this tool versus alternatives. While it implies that for content retrieval one should use 'read_text', there is no direct guidance on prerequisites, limitations, or when not to use 'inspect_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?
No annotations provided, so the description carries full burden. It indicates a read operation ('list') but lacks details on what is returned, formatting, or safety implications. The description is too sparse to provide adequate transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
A single, clear sentence that conveys the purpose without any unnecessary words. Efficient and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given zero parameters and no output schema, the description is partially complete. It explains what the tool does but does not clarify the output format or when it is appropriate to use. For a simple list tool, it is minimally adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters exist, so schema coverage is trivially 100%. The description does not need to add parameter details, and it provides sufficient context about the tool's purpose.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the verb ('List') and the resource ('workspace roots'), and specifies the purpose ('that BrainRegion file tools may read'). It distinguishes itself from sibling list tools by focusing on allowed roots for BrainRegion tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 like list_regions or list_knowledge. There is no mention of prerequisites, exclusions, or context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, description must disclose behavior. It reveals reading with constraints (line/byte limits, allowed workspace). However, it does not mention side effects, error behavior (e.g., if file not found or limits exceeded), or that it is read-only. Acceptable but not thorough.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence of 12 words, front-loaded with the key action and constraints. No wasted words; perfectly concise for what it covers.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 4 parameters, no output schema, no annotations, and many sibling tools, the description is too sparse. It lacks details on return format, parameter interactions, and when to use this tool. Leaves significant gaps for an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so description must explain parameters. It mentions 'line and byte limits' which hints at start_line, end_line, max_bytes, but does not explicitly describe each parameter or their defaults. Path is implicit but not detailed. Provides some context but insufficient for full understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states 'Read UTF-8 text from an allowed workspace file' – specific verb and resource. Mentions line and byte limits, but does not differentiate from sibling tools like inspect_file or search_text which might also read file content.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use read_text versus alternatives (e.g., inspect, search_text, inspect_file). The description is too brief to provide any contextual usage advice.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description sufficiently discloses the tool's non-destructive nature (no execution or file modification), its panel precedence logic (planner_panel → consult_panel → review panel), and the single-model fallback strategy without multi-model debate. This gives the agent a clear behavioral model.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is somewhat verbose (multiple sentences explaining fallback logic) but is front-loaded with the core purpose. Some sentences could be condensed without losing meaning. Adequate but not maximally concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (10 parameters, no output schema), the description is incomplete. It provides no parameter details, no explanation of return format or structure, and no mention of success criteria or constraints. The behavioral details help, but significant gaps remain.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, meaning the input schema provides no parameter descriptions. The tool description does not explain any of the 10 parameters (e.g., goal, files, panel, effort, context, constraints, etc.). The agent has no semantic guidance beyond parameter names, which is insufficient for correct invocation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: breaking goals into executable and reviewable plans, returning structured plans without executing commands or modifying files. It distinguishes from siblings like review_plan and suggest_workflow by focusing on plan creation rather than review or workflow suggestion.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains the tool's fallback behavior across panels but does not explicitly specify when to use this tool versus alternatives like consult_problem or suggest_workflow. The guidance is implicit from the name and purpose, but no direct comparisons or exclusions 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?
No annotations are provided, so the description carries full burden. It discloses it never calls models/downstream tools, describes false-negative defense mechanism (sentinel, shadow), and outlines returns (activation trace, metrics, suggested actions). It lacks info on rate limits or auth, but the read-only nature is clear.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single paragraph that front-loads the main purpose but uses heavy jargon (e.g., 'false-negative defense', 'sentinel', 'shadow fallback wakes') without explanation. It is not overly long but could be improved with clearer structure and less jargon.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (10 parameters, no output schema, no annotations), the description is insufficient. It does not explain how to set parameters, interpret outputs, or handle edge cases. The lack of parameter documentation and output format details makes it incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not explain any of the 10 parameters (e.g., goal, top_k, sentinel, gold_regions). It references 'sentinel' and 'shadow' but does not map them to schema fields. This is a critical gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's role as a 'Region-routing wake gate with false-negative defense (read-only sidecar)' and details its process (routes through retrieve -> escalate -> wake, adds sentinel and shadow fallback wakes). It also specifies outputs and what it does not do (never calls models/downstream tools), distinguishing it from siblings like route_regions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description mentions it is a read-only sidecar, implying non-destructive use, but does not explicitly state when to use this tool versus alternatives like route_regions or consult_problem. There is no guidance on prerequisites or conditions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It only says 'list', implying a read-only operation, but lacks details such as whether it caches results, requires authentication, or has any side effects. Minimal value beyond the action verb.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence with no unnecessary words. It delivers the essential information efficiently.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description should describe the return format or structure. It does not mention what the output looks like (e.g., a list of strings, structured objects). The agent lacks information about what data it will receive, making the description incomplete for a zero-parameter tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters exist in the input schema, so schema description coverage is 100%. The rule sets a baseline of 4 for 0 parameters, and the description does not need to add anything about parameters. It therefore meets the bar.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists default values from three levels (builtin, config, env) with sources. It uses a specific verb and resource, and distinguishes from sibling list tools like list_adapters which list different entities.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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. The description does not mention any context, prerequisites, or when not to use it. With many sibling list tools, the agent lacks criteria for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavior. It only states the action of marking as superseded and exiting recall, omitting side effects, permissions, or any other behavioral traits beyond the basic operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short and front-loaded with the core purpose. It is concise but could benefit from a clearer structure separating purpose and usage.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, no output schema, and two required parameters with no descriptions, the description is incomplete. It lacks parameter details, return behavior, and any additional context needed for correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, with no parameter descriptions in the schema. The description does not explain the meaning or format of old_id and new_id, leaving the agent to infer their purpose from context.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool marks an old memory as superseded by a new one, and it explicitly notes it is a convenience wrapper for set_experience_status. This distinguishes it from the sibling tool set_experience_status.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description indicates when to use the tool: when an old memory is superseded by a new one, exiting recall. It does not explicitly provide when-not-to-use or alternatives, but the context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description should disclose behavioral traits. It only states 'List available Brain Regions' without mentioning whether it is read-only, any authentication needs, or side effects. This lack of detail reduces transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no extraneous content. It is front-loaded and efficient, earning its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no output schema, the description does not explain the return format (e.g., list of IDs, objects). However, given the simplicity of listing regions, the description is minimally adequate but could be more complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has zero parameters, and schema coverage is 100%. The description does not add parameter information, but with no parameters, no additional documentation is needed. Baseline score of 4 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('List') and the resource ('available Brain Regions'), making the tool's purpose unambiguous. The presence of sibling 'route_regions' further differentiates it as a simple listing operation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 'route_regions'. For a simple list tool, some implicit understanding exists, but explicit differentiation is missing.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden for behavioral disclosure. It explicitly states that only minimal feedback metadata and user feedback text are saved, and that original prompt, problem text, and full advice are not preserved. This adds valuable context about side effects and limitations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, with the purpose front-loaded in the first line. It provides necessary details in a few sentences without verbosity. Slightly more structure (e.g., listing parameters) could improve readability.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 5 parameters, no output schema, and 0% schema coverage, the description should fully explain inputs and outcomes. It covers some parameters but misses 'reason' and 'outcome', and lacks details on return value or errors. Adequate but not complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does 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 explains the source of advice_id/consultation_id and the meaning of decision. However, 'reason' and 'outcome' parameters are not explained, leaving ambiguity. The description partially compensates but is incomplete.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action 'mark whether an advice is useful' and the resource ('advice'), and specifies that it writes to Advice Memory. However, it does not explicitly differentiate from sibling tools like mark_finding or mark_superseded, keeping it from a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides guidance on where to get parameters (from consult_problem) and lists the allowed decision values. However, it does not explain when to use this tool versus alternatives, nor does it mention prerequisites or exclude cases.
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?
Discloses read-only nature, no generative model calls, no writes. Mentions always fetching memory/run/calibration and conditional activation. Without annotations, this is fairly transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Concise, front-loaded with main purpose, then details. Could be slightly more structured but not overly long.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite lacking annotations and output schema, the description fails to explain parameter usage and only partially describes return format. An agent cannot confidently set parameters without additional context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 13 parameters and 0% schema coverage, the description only hints at 'goal' and 'problem' for activation fetch. No guidance on the other 11 parameters (files, top_k, region, etc.), leaving the agent uninformed.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states the tool creates a brain state snapshot, returns structured data, and is read-only. Distinguishes from siblings by mentioning CLI rendering and the conditional activation fetch.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Explains when to use (visualization, obtaining serializable data) and when activation is fetched (only when problem/goal non-empty). Lacks explicit comparison with alternatives but still clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits. It only states the function without mentioning side effects, permissions, or return format. Minimal transparency for a list operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no wasted words. It is appropriately sized and directly states the purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no parameters and no output schema, the description is somewhat incomplete. It does not specify what information is returned for each consultant (e.g., name, ID, availability). For a simple list tool, this might be adequate but could be more informative.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters exist, so the baseline is 4. The schema coverage is 100%, and the description adds no param-specific info, which is acceptable given zero parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (list) and resource (consultants/外援会诊角色), distinguishing it from sibling list tools like list_adapters or list_skills. It's specific and concise.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives, but the context (sibling tools list various resources) implies usage for retrieving consultant options. Lacks exclusion criteria or preconditions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description adds behavioral context: it lists only manifest-only, sanitized, experimental skills, does not leak body ref, and does not trigger resolve. This is sufficient but could mention idempotency or caching.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short but mixed language (English + Chinese). The key info is present, but the Chinese phrases may reduce clarity for non-Chinese agents. Some redundancy exists.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a list tool with one optional parameter and no output schema, the description adequately covers the output nature (manifest-only, sanitized, experimental) and behavioral constraints. Missing region explanation is the main gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single optional parameter 'region' is not explained at all in the description. With 0% schema coverage, the description should compensate but fails to clarify what region influences.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'List registered Skill manifests' with specific qualifiers (manifest-only, sanitized, experimental). This distinguishes it from sibling tools like list_adapters or list_knowledge.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description mentions it's a 'Phase 4 discovery surface' and a 'Router API call point', implying a specific use case, but does not explicitly state when to use versus alternatives or provide 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?
With no annotations provided, the description fully covers behavioral traits: read-only, no model calls, ignores file contents, uses file paths as metadata. This is transparent and sets correct expectations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Description is extremely concise: two clear sentences. First sentence states purpose, second lists exclusions. No wasted words; front-loaded and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Tool has 6 parameters, no output schema, and no annotations. The description only addresses file metadata, omitting details on other parameters and return behavior. Incomplete for reliable agent use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description only briefly mentions 'files' as weak metadata. It does not explain the purpose or expected values for goal, context, problem, top_k, or min_score, leaving agents without essential guidance.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool recommends Brain Regions using local deterministic rules, distinguishing it from siblings like list_regions. It specifies what the tool does not do (call models, read memory, etc.), leaving no ambiguity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Description explicitly states the tool is read-only and lists what it does not do (call models, read memory, trigger other tools), guiding appropriate use. However, it lacks explicit comparison to sibling tools or when to prefer 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?
With no annotations, the description discloses reversibility, automatic stamping on status change, superseded_by usage, and effect on recall. Missing details on permissions or return values.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Description is concise and uses structured bullet points, though it could be more clearly organized into sections.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers main behavioral aspects and parameter details, but omits return value, error cases, and permission requirements given no output schema or annotations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 0% coverage; description explains status values, superseded_by condition, and valid_until_ts meaning. Id is implied but not described. Adds significant value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it updates the governance status of an experience, listing allowed status values. However, it does not differentiate from sibling tools like mark_superseded.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides needed context on allowed statuses, side effects, and default recall filtering, but lacks explicit guidance on when to use this tool versus 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?
No annotations are provided, so the description fully carries the behavioral transparency burden. It clearly states the tool is advisory, uses a 'local deterministic router', and returns candidate actions without executing them. This provides sufficient insight into its non-destructive, read-only nature.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: two sentences that front-load the purpose and then add essential behavioral clarification. Every sentence adds value with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has no output schema, 6 optional parameters (0% schema coverage), and no annotation safety net, the description is too sparse. It explains the overall behavior but leaves the agent guessing about parameter usage and return format, which is inadequate for effective tool invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%. The description does not mention any of the 6 parameters (goal, files, top_k, context, problem, min_score) or their meaning. An agent has no guidance on how to set these parameters to influence the suggestions, making this a critical gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Suggest explicit manual next tool calls from Brain Region routing.' It specifies the verb (suggest), resource (next tool calls), and context (Brain Region routing). It also lists example candidate tools (plan_task, consult_problem, etc.), distinguishing it 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 Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states it is 'advisory only' and that it 'never calls those tools or models,' clarifying when to use it (for suggestions) and what it does not do. It implies when not to use: when direct execution is needed, use sibling tools directly. However, it does not explicitly state alternatives or exclusions.
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 no annotations provided, the description fully carries the transparency burden. It explicitly states the tool is read-only, does not call models, does not write, and does not recompute, with wake_gate verified as a read-only sidecar.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded with purpose, followed by bullet points for views. It could be better structured to cover all parameters, but it is efficient for what it covers.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of 15 parameters and lack of annotations or output schema, the description is incomplete. It adequately covers the main view parameter but neglects most other parameters and return values.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds meaning for only 2 of 15 parameters (view and memory_manifest), leaving 13 parameters undocumented. The schema has 0% description coverage, so the description should compensate more.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool is a read-only debug window that exposes internal system states, with specific verbs and resources. It differentiates from siblings like 'inspect_file' and 'wake_gate' by being a comprehensive multi-view inspection tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains the context of debugging and each view's purpose, but it does not explicitly state when not to use this tool or mention alternatives. Usage is implied but not comprehensive.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It only states the purpose (health check) but does not describe the response format, side effects, or any prerequisites. For a simple ping, more detail on output would improve transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence with no unnecessary words, efficiently conveying the core purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with no parameters and no output schema, the description adequately states the purpose. However, it could be more complete by indicating the type of response (e.g., success/failure), making it slightly better than minimal.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are no parameters, so schema coverage is 100%. The description adds no parameter-specific information, but the baseline for zero parameters is 4, which is appropriate here.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose as a health check to confirm server reachability, using a specific verb and resource. It implicitly distinguishes from sibling tools that perform more complex actions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is used for checking server availability but does not explicitly state when to use it or provide alternatives. No exclusions are given, which is acceptable for a simple tool but lacks explicit guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It states the tool operates without calling models, implying a safe, read-only action. However, it does not elaborate on side effects, authentication requirements, rate limits, or other behavioral traits beyond the core function.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences: the first states the purpose clearly, and the second lists strategies and usage context. No wasted words; information is front-loaded and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the main purpose and how the output is used, but given the absence of output schema and parameter details, it leaves gaps about return value structure and parameter specifics. For a recommendation tool with clear intent, it is adequate but not comprehensive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does 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 lists the strategy options but does not explain the other parameters (task, panel, max_models, require_available_key). Their names are somewhat self-explanatory, but the description adds minimal value over the schema for parameter understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool recommends a model panel from route/profile metadata without calling models, lists specific strategies, and explains how the output can be used in other tools like plan_task or consult_problem. This distinguishes it from sibling tools that execute tasks rather than recommend panels.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context: it is a zero-cost operation that recommends a panel for later use when the user chooses to spend tokens. It implies when to use it (before calling plan_task or consult_problem) but does not explicitly state when not to use it or mention alternatives like suggest_workflow.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description discloses that the tool is read-only and does not call a model. It explains the behavior of include_inactive (production mirror vs. debugging) and describes the return format. This is transparent and adds value 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences: purpose, use case, and parameter/return detail. It is concise, front-loaded, and every sentence adds value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and no annotations, the description covers the main purpose, key parameter, and return format. However, it omits details about top_k and region filtering, which are necessary for full understanding without additional context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description must compensate. It explains the text parameter (keyword) and include_inactive behavior and defaults. However, it does not describe top_k (limiting results) or region (filtering), leaving gaps for two of four parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool recalls experiences by keyword, specifies it is read-only and does not call a model, and distinguishes it from writing or model-driven tools. The resource and verb are specific and unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains the tool is used to inspect what Experience Memory will recall, and describes the include_inactive parameter's effect. However, it does not explicitly state when to use this tool versus alternatives like search_text or record_experience, leaving some guidance implicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, description carries full burden and discloses key behaviors: no model calls, no API key exposure. This is sufficient for a read-only diagnostic tool, though it doesn't mention auth or performance impacts (likely negligible).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two short, focused sentences with no redundancy. The first sentence gives the core action, the second adds critical qualifiers without extra words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given low complexity (1 optional param, no output schema), the description covers purpose and behavior well. The only gap is the missing parameter explanation, which is minor since the parameter is optional and default null.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has one parameter (panel) with no description, and the tool description does not explain it. With 0% schema description coverage, the description should compensate but fails to clarify what 'panel' does or how it affects output.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool shows how model specs resolve to providers or endpoints, provides concrete examples (bare model strings vs endpoint refs), and distinguishes itself as diagnostic only. This makes the purpose 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 Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states it is a diagnostic tool only, does not call models, and never returns API keys, giving clear context for when to use. However, it doesn't compare to siblings like list_adapters or list_defaults, missing full guidance on alternatives.
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 no annotations provided, the description bears full responsibility for behavioral disclosure. It explains that the tool only returns structured suggestions, does not execute commands or modify files, and includes security measures such as sensitive information desensitization, input length control, and consultant whitelist validation. It also details mode options and fallback logic, offering comprehensive transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is moderately concise. It starts with a clear purpose statement, then lists what it does/doesn't do, then explains options. Some redundancy exists, but overall it is well-structured and essential information is front-loaded. A slight improvement could be grouping parameters more explicitly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and 17 parameters, the description explains input handling (desensitization, length limits) and fallback behavior, but lacks details on output format (only 'structured suggestions' without specifics). The behavior for required parameter 'problem' is assumed but not elaborated. Completeness is adequate but not exhaustive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does 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 explains the 'mode' parameter with explicit options (debugging/architecture/performance/etc.) and describes fallback behavior for 'panel' and 'consultants'. However, 17 parameters exist; many (goal, logs, files, effort, context, attempts, question, why_stuck, constraints, max_cost_usd, desired_output, current_attempt, max_input_chars) are not explained, leaving a significant gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: '外援会诊', meaning external consultation, when the main model is stuck or needs a third-party perspective. It distinguishes from siblings by explicitly stating it only returns structured suggestions and does not execute commands or modify files.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit when-to-use scenarios: when the main model is stuck, not confident, continuous debugging failure, or needs a third-party perspective. It also states what the tool does not do (no command execution, no file modification) and describes fallback behavior for panel and consultants. This provides clear guidance for an AI agent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description fully covers behavior: multi-model fan-out, knowledge retrieval, cost control limits, model-specific effort handling, and caching (cache_hit/reuse_count). Exceptionally transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Structured with a summary, technical process, return info, and bulleted Args. Each sentence adds value; no redundancy. Front-loaded with the core purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (12 params, no output schema), the description covers return structure, cache, budget enforcement, and model-specific behavior. Virtually no gaps for an AI agent to understand correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description includes a detailed Args section explaining every parameter's purpose, defaults, constraints (e.g., effort affects only specific models, max_cost_usd triggers budget trimming). Fully compensates for missing schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool reviews documents (markdown/code/adr/rfc/config) with multi-model AI and knowledge retrieval. The verb 'review' and specific resource types make the purpose explicit.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool over siblings like review_code or review_plan. The description focuses on internal mechanics rather than usage context.
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 no annotations provided, the description fully carries the burden. It discloses that the tool writes to Review Memory, affects reliability weighting, and invalidates cache. It also details the decision options (accepted/rejected/partial) and the fallback lookup for params_hash. 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with multiple sentences, each providing essential information. It is front-loaded with the main action, then explains details and fallbacks. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 5 parameters, no output schema, and no annotations, the description covers purpose, input details, effects, and cache behavior. It lacks explicit mention of return value or error cases, but overall is quite complete for a state-updating tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description must add meaning. It explains finding_id and params_hash come from review_document, decision values, and note purpose. The invalidate_cache parameter is not explicitly named, but its default behavior (cache invalidation) is described. Overall, it compensates well.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb '标记' (mark) and the resource 'finding', detailing that it records acceptance status into 'Review Memory' for future reliability weighting. This distinguishes it from sibling tools like mark_advice and mark_superseded.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains when to use the tool (after review_document returns finding_id/params_hash) and describes behavior for optional params_hash. It mentions cache invalidation and that it affects future weighting. However, it does not explicitly state when not to use it or compare to alternatives.
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 no annotations provided, the description fully explains behavioral traits: append-only nature, return format {ok, id}, parameter semantics (status, valid_until_ts, supersedes), and configuration gating (memory_inject). This is comprehensive 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise (4-5 sentences) and front-loaded with the main purpose. Each sentence adds value, with no redundancy or irrelevant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 8 parameters, no output schema, and many sibling tools, the description adequately covers functionality, parameter meanings, return type, and relationships to recall_experiences and set_experience_status. It could mention the exact trigger matching mechanism, but overall it's sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description compensates by explaining key parameters: summary (required), triggers (keywords), region (global), status (enum), valid_until_ts (Unix seconds), supersedes (auto-mark). It omits details on source and details but covers core semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: recording an experience to Experience Memory for later recall. It uses a specific verb-resource pair and distinguishes it from sibling tools like recall_experiences and set_experience_status.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides context on when to use the tool (to record experiences) and mentions related tools for recall and status changes. It doesn't explicitly state when not to use it, but the guidance is clear enough.
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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