world-model-mcp
Server Quality Checklist
Latest release: v0.15.5
- Disambiguation4/5
Most tools have distinct purposes, e.g., query_fact vs get_constraints vs get_agents_md_constraints. However, some overlap exists between get_constraints (knowledge graph) and get_agents_md_constraints (project files), and between simulate_change and validate_change, though descriptions help differentiate.
Naming Consistency5/5All tools follow a consistent verb_noun pattern in snake_case, e.g., export_claude_md, find_contradictions, get_decision_log, record_event. No mixing of styles or unpredictable patterns.
Tool Count4/530 tools is high but justified by the broad scope covering knowledge graph, audit, constraints, and predictions. While slightly heavy, each tool serves a clear role in the world model domain.
Completeness3/5The set covers creation, reading, and updating of facts, constraints, and events, but lacks explicit deletion tools (e.g., delete fact, remove constraint) and project removal. Missing operations like editing facts directly limit full lifecycle coverage.
Average 3.1/5 across 30 of 30 tools scored. Lowest: 2.3/5.
See the Tool Scores section below for per-tool breakdowns.
- 1 of 1 community issues answered or closed in the last 6 months
- 136 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 MIT License.
This repository includes a README.md file.
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This repository includes a glama.json configuration file.
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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
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description must disclose behavioral traits. It only states it's a 'get' operation but omits details like permissions, potential impact, or response format.
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?
The single sentence is short but fails to provide essential information, making it under-specified rather than concise. It does not earn its place given the low information density.
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?
For a tool with 4 parameters and no output schema or annotations, the description is severely incomplete. The agent cannot determine how to invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description should compensate, but it does not explain any of the four parameters (session_id, file_path, decision_type, limit). The agent has no guidance on how to use them.
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 retrieves decision traces related to agent proposals and human corrections, making the purpose clear. However, it does not explicitly differentiate from sibling tools like query_fact or record_decision.
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 query_fact or get_injection_context. There is no mention of prerequisites or scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden for behavioral disclosure. It states the tool projects blast radius and historical outcomes, implying analysis without side effects, but it does not confirm read-only behavior, specify required permissions, or describe the output format. Important behavioral traits are omitted.
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?
The description is a single 8-word sentence, which is highly concise, but at the expense of necessary detail. For a tool with two parameters and no other documentation, it is underspecified and does not earn its brevity.
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 absence of annotations, output schema, and parameter descriptions, the description is critically incomplete. It fails to provide essential context about inputs, outputs, or tool behavior, making it difficult for an agent to use effectively.
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 description provides no information about the two parameters (file_path and change_description). The agent is left without any guidance on how to specify these inputs or what values are expected, severely hindering correct invocation.
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 uses a specific verb 'Project' and identifies the resource as 'blast radius and historical outcomes', clearly indicating the tool's purpose of assessing impact of a proposed change. However, it doesn't explicitly distinguish from siblings like 'predict_regression' or 'validate_change', which could also involve outcomes.
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. The sibling tools include 'validate_change' and 'predict_regression', which may serve similar or complementary roles. The description lacks any context about appropriate use cases, 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, so the description must disclose behavioral traits. It states it uses historical patterns, but does not mention whether this is a read-only operation, performance implications, or required permissions. The description is too brief to cover key behavioral aspects.
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 concise sentence, which is efficient. However, it could be improved by briefly clarifying parameters or output without becoming verbose. It is front-loaded but lacks 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 the tool has two parameters and no output schema, the description should at least mention what the output contains (e.g., list of file paths) and how the limit parameter behaves. It is too sparse to be considered 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 description coverage is 0%, and the description adds no explanation for the two parameters 'file_path' and 'limit'. It does not clarify that file_path is the input file path or that limit controls the number of suggestions. The description offers no semantic value 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 clearly states the tool returns files commonly edited alongside a given file based on historical patterns. It distinguishes from siblings like export_claude_md or find_contradictions, making its purpose evident. However, it could be slightly more specific about the nature of 'commonly edited' patterns.
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. It does not mention when not to use it or any preconditions. Sibling tools like get_related_bugs or get_health_report may overlap in usage context but no differentiation is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden. It does not disclose whether the operation is destructive, requires permissions, or what happens to existing constraints in target projects. The minimal description fails to convey important behavioral traits.
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 sentence, which is concise but too terse. It front-loads the action but omits critical details, trading brevity for completeness.
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, no annotations, and low schema coverage, the description is inadequate. It fails to explain the promotion mechanism, impact on target projects, or any side effects. The agent lacks sufficient context 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?
The description does not explain the parameters at all, despite 0% schema description coverage. The schema shows constraint_id required and target_projects optional, but the description contradicts the schema by implying promotion to 'all' projects. No parameter semantics added.
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 'promote' and the resource 'constraint', and specifies the scope 'from this project to all other registered projects'. It distinguishes from sibling tools like get_constraints or resolve_contradiction.
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, such as when to promote vs. simply retrieving or resolving constraints. It does not mention 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 present, so the description must carry the full behavioral burden. It only states 'link failures to recent code changes' but does not explain how the linking works, whether the operation is idempotent, or what side effects occur (e.g., overwrites existing records).
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?
The description is a single sentence, which is concise, but it lacks necessary detail. It is not well-structured; it front-loads the action but omits critical contextual information, making it under-specified.
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 has two required parameters (one nested), no output schema, and no annotations, the description is far from complete. It does not describe return values, error handling, or the expected outcome, leaving 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.
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 explanation of parameters. It does not clarify 'session_id' format or the structure of 'test_results' (e.g., required fields, expected values for 'error'). The description fails to compensate for the schema's lack of detail.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
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 test results and linking failures to recent code changes. It uses a specific verb 'Record' and resource 'test results with failure linkage', distinguishing it from sibling tools like 'predict_test_failures'.
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 (e.g., 'predict_test_failures' or other logging tools). It lacks context for prerequisites, success criteria, or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must fully disclose behavioral traits. It implies a read operation (scoring risk) but does not explicitly state side effects, idempotency, or authorization needs. Missing details about whether past data is fetched or modified.
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 front-loads the core purpose. It is concise but could benefit from structured breakdown for clarity.
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?
The description lacks completeness for a scoring tool with no output schema and no annotations. It does not describe the return value (e.g., a numeric score or category), limiting the agent's understanding of what to expect.
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 the parameters beyond their names. 'file_path' and 'change_description' are not elaborated, and the basis (past bugs, test failures, constraint violations) is not mapped to input fields.
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 verb (score risk) and resource (proposed change to a file) with specific inputs (past bugs, test failures, constraint violations). It distinguishes from siblings like 'predict_test_failures' and 'simulate_change' by focusing on regression risk, though not explicitly contrasting.
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. It does not mention when it is appropriate or inappropriate, nor does it reference sibling tools for comparison.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description should disclose behavioral traits. It only says 'validate', implying a read-only check, but does not confirm read-only status, side effects, required permissions, or other constraints. The agent lacks insight into the tool's behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is concise but sacrifices necessary detail. It is front-loaded with the key action, but the brevity leaves out critical information that could be added without verbosity.
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 (3 parameters, no output schema, and 25 sibling tools), the description lacks completeness. It does not explain what 'known constraints' are, what the validation result looks like, or how it differs from tools like 'simulate_change' or 'get_constraints'.
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 only 33% (only 'proposed_content' has a description). The tool description adds no additional meaning to the parameters beyond the schema. The 'change_type' enum values are unexplained, and 'file_path' format is not clarified.
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's purpose: validating a code change against constraints. It uses a specific verb ('Validate') and resource ('proposed code change'). However, it does not explicitly differentiate from similar sibling tools like 'simulate_change' or 'find_contradictions', though the action is distinct enough.
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 (e.g., 'simulate_change', 'get_constraints'). There is no mention of prerequisites, limitations, or when not to use it, leaving the agent without 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 disclose behavioral traits. It does not state whether the tool is read-only, requires permissions, or what the output format is. The description only mentions the detection criteria without safety or side-effect context.
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 of 13 words, very concise with no redundant information. However, the brevity sacrifices necessary details, making it less helpful than a slightly longer but more informative description.
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, no annotations, and two undocumented parameters, the description lacks essential details about how contradictions are identified, what the output contains, and how parameters work. It is incomplete for reliable tool 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%, so the description bears full responsibility. It does not explain how 'query' and 'limit' parameters affect the contradiction search. The agent cannot determine valid inputs or behavior.
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 finds contradictory fact pairs using similarity and status differences. The verb 'Find' and resource 'pairs of facts that contradict each other' are specific, though the source of facts (e.g., a database) is not specified. It distinguishes from siblings like 'resolve_contradiction' in purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 'query_fact' for general fact retrieval or 'resolve_contradiction' for resolving contradictions. The agent must infer usage context from the tool name and siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must fully disclose behavior. It only states the read operation but omits details on error handling (e.g., missing file), default behavior for optional constraint_types, authentication needs, or return structure.
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 with 10 words, efficiently conveying the core purpose without extraneous detail. It is front-loaded with the key action and resource.
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 and no annotations, the description is incomplete. It fails to specify the return format, default behavior when constraint_types is omitted, prerequisites, or how this tool differs from siblings like 'get_agents_md_constraints'.
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%. The description adds context for constraint_types (listing examples) but does not explain file_path format (absolute/relative) or the meaning of each enum value. The optional nature of constraint_types is not clarified.
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 verb 'Get', resource 'constraints', and scope 'for a file'. It provides examples of constraint types (linting rules, patterns, conventions), making the purpose distinct from siblings like 'get_agents_md_constraints' which targets a specific file type.
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 (e.g., 'get_agents_md_constraints', 'resolve_contradiction'). There are no explicit contexts, exclusions, or recommendations provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must disclose behavioral traits. It does not mention whether the tool is read-only, requires special permissions, or has side effects. The term 'assess' could imply computation but is not clarified.
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?
One sentence with no unnecessary words. However, it combines two actions without separation, which could be clearer if structured as bullet points or two sentences.
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?
With no output schema and no annotations, the description does not explain the output format, whether it returns a list of bugs, a risk score, or both. It lacks details on constraints or behavioral context.
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 50%, meaning file_path lacks schema description, and the description does not add details for either parameter. change_description already has a schema description, so no added 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 the tool retrieves bugs fixed in a file and assesses regression risk. However, it does not differentiate from sibling tools like predict_regression, which may also assess risk.
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 versus alternatives. The description implies usage for file-related bug and risk assessment, but lacks exclusions or alternative suggestions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden. It only implies a write operation but fails to disclose side effects, storage behavior, or any 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.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The single-sentence description is concise and front-loaded. It is efficient but risks being too short for the tool's complexity.
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?
With 7 parameters, no output schema, and no annotations, the description is incomplete. It does not cover error handling, return values, or usage patterns.
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 coverage is only 29%, and the description adds no additional parameter details beyond the enum list. Key parameters like session_id and reasoning are left unexplained.
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 'Record a development event' with examples, making the purpose straightforward. However, it does not distinguish from sibling record_* tools like record_correction or record_decision.
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 such as record_decision or record_test_outcome. 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, the description bears full responsibility for behavioral disclosure. It fails to mention any traits such as whether the search is read-only, pagination behavior, or access control requirements. The description is too vague to inform the agent about side effects or constraints.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that is concise and front-loads the purpose. It could be improved by adding more information without becoming verbose, but it is not overly brief at the expense of clarity.
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 and moderate tool complexity, the description is incomplete. It does not explain the return format, what 'entities' means, if sorting or filtering is applied, or any limitations. This leaves significant gaps for effective agent usage.
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 only states 'search entities across projects' without explaining the 'query' parameter (search terms, format) or 'limit' parameter (pagination, default value). No parameter details are provided.
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 this tool searches entities across all registered world-model projects, indicating a broad search scope. However, it does not explicitly differentiate from sibling tools like 'query_fact' which might also perform searches, so it loses a point for lacking sibling distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 'query_fact' or other search-related tools. There is no mention of prerequisites, context, or exclusions, leaving the agent without decision support.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool 'returns' data but does not confirm read-only behavior, error handling for missing files, or any side effects. The description gives minimal transparency 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, direct and to the point, with no redundant information. It front-loads the key action and additional context about automatic enforcement, earning its length.
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 and sibling tools that could overlap, the description fails to explain the return format, parameter usage, or how this tool relates to get_constraints. It is incomplete for an agent to reliably call without additional knowledge.
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?
The input schema has two parameters (project_dir, file_path) with 0% description coverage, and the description does not explain their purpose or expected values. No added meaning beyond the schema; the agent must guess how to use these 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's action: parsing specific files (AGENTS.md, CLAUDE.md, etc.) and returning declarative constraints. It distinguishes itself from siblings by specifying the exact file sources and noting its automatic enforcement role, making it clear what resource it targets.
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 this tool is for inspection of constraints that are automatically enforced via PreToolUse, but it does not explicitly compare to alternatives like get_constraints or provide when-not-to-use guidance. The usage context is hinted but not fully articulated.
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 behavioral traits such as whether the tool is read-only, what side effects (if any) exist, or any authentication or rate limit requirements. For a diagnostic tool, the lack of read-only assurance is a gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that front-loads the purpose and enumerates key elements without redundancy. Every word is purposeful and contributes to understanding.
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?
No output schema is provided, and the description does not explain the return format (e.g., counts, detailed lists, or summaries). For a tool with no parameters, the output description is critical but missing.
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 no parameters, so schema coverage is effectively 100%. The description adds meaning by listing the diagnostic categories (orphans, stale facts, etc.), which provides semantic context beyond the empty 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 clearly states it provides 'Memory health diagnostics' and enumerates specific aspects (orphans, stale facts, contradictions, decay candidates, DB sizes). However, it does not explicitly differentiate from nearby sibling tools like 'find_contradictions' or 'get_compaction_audit' which overlap in scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 such as 'find_contradictions' or 'get_compaction_audit'. The agent is left to infer use cases from the description alone, which is insufficient for correct tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, and the description does not disclose any behavioral traits (e.g., side effects, read-only nature, permissions needed). It solely states the function without elaboration.
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 of 12 words, efficiently conveying the tool's purpose with no 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 the low complexity (1 required parameter, no output schema, no annotations), the description adequately states the function but omits details like return format (e.g., list of test names) or probabilistic information.
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 adds basic meaning that 'file_paths' are the edited files, but lacks details on format, constraints, or behavior for invalid inputs.
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 uses the verb 'Surface' with the resource 'tests likely to fail' and context 'given a set of edited files', clearly distinguishing it from siblings like 'predict_regression' which likely addresses broader regression risks.
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 versus alternatives such as 'predict_regression' or 'get_related_bugs'. The description only implies usage context without exclusions or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description must carry the full burden. It describes a fetch operation ('hydrate') but does not disclose read-only behavior, permissions, rate limits, or side effects. The behavioral traits are largely implicit.
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 with no redundancy. Every word adds value, and the structure clearly separates action from purpose.
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 lack of annotations, output schema, and param descriptions, the description is incomplete. It does not clarify omitted parameters, output format, or constraints, making it inadequate for a 3-parameter tool.
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 explanations for session_id, line_start, or line_end. The agent must infer meaning from parameter names alone, which is insufficient.
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 uses a specific verb ('Hydrate') and clearly identifies the resource ('Claude Code session transcript by line range'). The second sentence provides the use case of tracing facts back to conversations, distinguishing it from sibling tools like get_decision_log.
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 tracing facts but does not explicitly state when to use this tool versus alternatives or when not to use it. No exclusions or comparisons are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It only implies a write operation but fails to mention side effects, permissions, validation, or return behavior (no output 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?
A single sentence that efficiently conveys the core purpose. No unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 4 parameters, nested objects, no output schema, and no annotations, the description is too brief. It lacks guidance on formatting nested fields, valid session_id, or expected 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?
Schema coverage is 75%, but the description adds no additional meaning beyond the schema. It doesn't clarify how to structure the nested objects (claude_action, user_correction) or what the reasoning field should contain.
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 'Record' and the resource 'user correction to Claude's output', and adds the purpose 'high-priority learning signal'. It distinguishes this tool from siblings like record_decision or record_event by specifying corrections.
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 vs alternatives like record_decision or record_event. The description mentions 'high-priority' but doesn't exclude other scenarios or state prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavior. It mentions 'compact constraint+fact bundle' and 're-inject' but gives no details on side effects, permissions, rate limits, or what happens if data is missing. This minimal disclosure is insufficient for safe invocation.
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 efficiently conveys the core purpose. It is well-structured and front-loaded. A small amount of additional detail would be acceptable without sacrificing conciseness.
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 absence of output schema and annotations, the description is incomplete. It does not describe the return format, error conditions, or behavior for different event_types. The tool has four parameters but no guidance on how they affect the output.
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 any of the four parameters (event_type, project_hint, max_constraints, max_facts). It does not explain the enum options for event_type or the meaning of the other parameters, forcing the agent to rely solely on the 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 returns a 'constraint+fact bundle' for specific hooks ('PostCompact / UserPromptSubmit') after context loss. It uses a specific verb ('return') and resource ('constraint+fact bundle'), and differentiates from siblings like 'get_constraints' and 'get_context_for_action' by focusing on re-injection after context loss.
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 for when to use the tool: after context loss for PostCompact/UserPromptSubmit hooks. However, it does not explicitly exclude other scenarios or mention alternatives, leaving some ambiguity about when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description lacks critical behavioral details such as whether authentication is required, whether the operation is idempotent, how conflicts with existing constraints are handled, or any side effects on the knowledge graph.
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 that is clear and front-loaded. Every word contributes to understanding the tool's purpose without 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 lack of annotations and output schema, the description omits important context such as return values, error handling, and the relationship with other knowledge-graph tools. It is minimally viable but incomplete for a tool that modifies state.
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?
The input schema descriptions already cover both parameters comprehensively, including defaults and auto-detection for 'repo'. The tool description adds no additional context beyond what is already in the 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's action ('Pull GitHub PR review comments and convert them into learned constraints') and identifies the resource (GitHub PR reviews, knowledge graph). This distinguishes it from sibling tools like 'get_constraints' and 'record_event'.
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. It does not mention when not to use it or provide context for selecting this tool over other ingestion or constraint-related tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavioral traits. It mentions 'confidence-weighted strategy' but does not explain what 'auto' does, whether the operation mutates the fact base, or if it requires special permissions. Missing important context about the resolution process.
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?
Single sentence that front-loads the action and includes a list of strategies. Could be more structured but is efficient and to the point.
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 0% schema coverage, the description is insufficiently complete. It does not explain return values, side effects, prerequisites, or how strategies differ internally. A more comprehensive description is needed for a resolution tool.
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%. The description lists the strategy options but does not explain them. fact_a_id and fact_b_id are obvious from context, but notes is not described. Minimal value added 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 verb 'pick a winner' and resource 'two contradicting facts' with specific strategies listed. It distinguishes from sibling tool find_contradictions which finds contradictions.
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 implicitly conveys that the tool is used when a contradiction is identified between two facts, but it provides no guidance on when to use which strategy or when to avoid this tool. No explicit when-not or alternatives are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It discloses the content sources but does not clarify whether the operation is read-only (e.g., no side effects), the output format, or file overwriting behavior. Listing included content provides moderate transparency, but security/permissions and return specifics are missing.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-front-loaded sentence that immediately conveys purpose and content scope. Every part is essential and adds value without 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 simple input schema (one undocumented optional parameter) and no output schema or annotations, the description should fully compensate by explaining parameter behavior and return format. It fails to do so, focusing only on content aggregation without covering usage details or output characteristics.
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?
The single parameter max_constraints (integer, optional) has 0% schema description coverage and is not explained in the description. The description provides no guidance on what this parameter controls or its default, leaving agents to guess.
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 generates a CLAUDE.md document from the knowledge graph, specifying included content categories (constraints, decisions, bugs, co-edit patterns). This distinguishes it from sibling tools like get_constraints or get_decision_log, which focus on individual aspects.
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 for generating a comprehensive document aggregating multiple knowledge graph elements, but does not explicitly state when to use it instead of more specific siblings (e.g., get_constraints). No exclusions or alternatives are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description lists return components (constraints, decisions, bugs, etc.) but does not state whether the operation is read-only, requires authentication, or has side effects. With no annotations, this gap 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, well-structured sentence that front-loads the tool's purpose and lists components clearly. No superfluous words.
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?
While the description lists what the tool returns, it does not address the format of the risk score or how the context bundle varies by action_type. The enum includes create, delete, refactor, but the description implies only editing, leaving completeness gaps.
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%, and the description does not explain either parameter. The phrase 'for a file' hints at file_path, but action_type is completely omitted, leaving its meaning to the schema alone.
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 provides a bundle of context items (constraints, decisions, bugs, etc.) for a file before an action. However, it only mentions 'editing' while the action_type parameter allows create, delete, and refactor, causing a slight misalignment.
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?
Use is implied by 'pre-action' and 'before editing', but no explicit guidance on when to prefer this bundle over individual context tools (e.g., get_constraints, get_decision_log) is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description outlines basic behavior (recording proposals and responses) but fails to disclose side effects, storage, or permissions. With no annotations, the description should carry this burden but only partially does.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that efficiently communicates the tool's purpose with no unnecessary words.
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 seven parameters (including nested objects), two required, no output schema, and no annotations, the one-sentence description is insufficient. It omits critical details about parameter usage and tool behavior.
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 coverage is 0%, meaning no parameter information is provided in the description. The description mentions agent proposal and human response but does not map them to parameters or explain required fields like session_id and decision_type.
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 a decision trace with agent proposal and human response. It uses a specific verb and resource, distinguishing it from sibling tools like record_correction or record_event.
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 versus alternatives such as record_correction. The description does not mention prerequisites or scenarios where this tool is appropriate or not.
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 alone must disclose behavioral traits. It implies mutation ('populate') but does not clarify side effects (e.g., overwriting existing data, performance impact, destructive potential of 'force'). The 'force' parameter hint is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is 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 scope.
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 simplicity (2 optional params, no output schema, no annotations), the description covers the basic purpose but lacks behavioral context and use-case guidance. It is minimally adequate but could be improved with usage notes or limitations.
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 100%, so the baseline is 3. The tool description does not add extra meaning beyond the schema's parameter descriptions. It omits details like default behavior, but schema already provides minimal 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's function: scanning a project codebase to populate a knowledge graph with entities and relationships. This verb+resource combination is specific and distinguishes it from sibling tools like 'export_claude_md' or 'query_fact'.
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 lacks guidance on when to use this tool versus alternatives. It does not mention prerequisites, typical scenarios, or exclusions (e.g., for incremental updates vs. initial seeding). No explicit 'when-to-use' or 'when-not-to-use' context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description must fully disclose behavior. It indicates a read operation but does not mention safety, auth requirements, rate limits, or side effects. The schema note about 'content_type' and procedures adds minimal behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with no redundant information. It efficiently conveys the tool's 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 4 parameters, no output schema, and a brief description, the tool description is minimal but acceptable. It lacks return value details, pagination, and comparison to siblings. Schema coverage somewhat compensates, but completeness is average.
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 100%, so baseline is 3. The tool description adds no extra parameter meaning beyond the schema's own descriptions. The content_type enum includes a note about summoning procedures, but that is in the schema, not the tool description.
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 queries the knowledge graph for facts, specifying entity types like APIs, functions, classes. This verb-resource combination is distinct enough among siblings to indicate when this tool is appropriate.
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 entity facts but offers no explicit guidance on when to use it over alternatives like search_global or get_constraints. No exclusions or when-not-to-use are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses that entries are listed most-recent first and that filtering is available, but it lacks details on what 'recent' means, pagination, or authentication requirements. This is basic but not comprehensive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that front-loads the main purpose and covers key details without any wasted words. It is optimally concise.
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 simplicity of the tool (2 optional parameters, no output schema), the description is adequate but not fully complete. It lacks details on response format, error handling, or ordering guarantee beyond 'most-recent first'. The word 'recent' is vague.
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 input schema has 0% description coverage, and the description adds only that the parameters are for filtering ('session_id' and 'limit count'). It does not specify formats, allowed ranges, or default values, leaving significant ambiguity for the agent.
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 'List' and the resource 'recent compaction audit entries', with ordering 'most-recent first'. It distinguishes from the sibling 'record_compaction_audit' as the read operation, providing clear purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for retrieving audit entries and specifies filtering options ('Filter by session_id or limit count'). However, it does not explicitly state when not to use this tool or mention alternatives among siblings, though the context makes it clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It discloses persistence into annotations table, Merkle audit log chaining, and a 8 KB rationale limit. Does not contradict any annotations, and provides adequate behavioral context for a mutation 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?
Two sentences with no wasted words. First sentence states primary action; second adds persistence and logging details. Front-loaded with the most critical 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 6 required parameters, no output schema, and no annotations, the description covers purpose, storage, and logging. Could mention immediate visibility or confirmation, but overall sufficient for a mutation tool.
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 83%, so baseline is 3. Description provides context about rationale size (redundant with schema) and mentions signing (not a parameter). Does not add substantive parameter-specific meaning beyond what schema offers.
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 uses specific verb 'Attach' and specifies resource 'signed human annotation' with three named subtypes. It clearly distinguishes from siblings like record_correction or record_decision by focusing on annotations attached to event spans.
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?
Description implies usage for creating human annotations on event spans but does not explicitly state when to prefer this over alternative tools (e.g., record_correction, record_decision). No exclusion criteria provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully convey behavioral traits. It does disclose that the tool is read-only (returns head state and chain), tamper-evident, and uses hybrid signatures. It also states the server flag requirement. However, it does not discuss potential failure modes, performance implications, or response size, which would be helpful.
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 two sentences that are front-loaded with the tool's output and followed by its usage context and requirement. Every sentence adds value and there is no redundancy or wasted words.
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 complexity (audit log head with epoch chain and signatures) and the absence of an output schema, the description provides a reasonable overview but lacks details on the response structure or format. It hits the key points but could be more complete for compliance auditors who need to understand the full 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?
The input schema has no parameters (0 parameters, 100% schema coverage), so the description is not required to add parameter information. According to the guidelines, the baseline for 0 parameters is 4, and the description meets this by not needing to elaborate.
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 that the tool returns the current head state of the tamper-evident audit log, including specific fields (last log entry seq, closed epoch seq, unclosed-entry count) and the full closed-epoch chain with hybrid signature envelopes. This is a specific verb-resource combination that distinguishes it from sibling tools like get_compaction_audit and get_health_report.
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 says 'Compliance auditors call this periodically to verify no operator misbehavior has occurred since the last check,' which provides a clear use case. It also mentions a prerequisite: 'Requires WORLD_MODEL_AUDIT_LOG=on at server startup.' However, it does not mention when not to use this tool or provide 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?
Without annotations, the description carries the transparency burden. It clearly indicates a write operation ('Record') and specifies the logged data (token counts and re-injected items). It lacks details on side effects, permissions, or idempotency, but for a straightforward logging tool the core behavior is well communicated.
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, front-loading the action and resource. Every word adds value; no superfluous content. It is efficiently structured for quick parsing.
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 7 parameters and no output schema or annotations, the description is minimal. It explains the purpose but does not cover parameter details, expected return values, error conditions, or whether the tool is idempotent. More information could be provided for a more complete picture.
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 mentions 'token counts' (mapped to pre/post_compact_tokens) and 'what was re-injected' (mapped to facts_injected, constraints_injected, injection_event, raw_summary), but does not explicitly define each parameter or their formats. The parameter names are self-explanatory, but the description could provide more explicit mapping.
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 records a 'context-compaction event' with token counts and re-injected content, using the specific verb 'Record'. It distinguishes itself from sibling tools like 'get_compaction_audit' (which reads audits) and 'recall_transcript_range' (which retrieves context).
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 second sentence explicitly states the tool helps developers 'audit what was remembered across compaction boundaries', providing clear context for use. It does not explicitly list when not to use it or suggest alternative tools, but the context is sufficient for an agent to decide when this audit logging is appropriate.
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 key behaviors: uses independent Coach LLM, never raises exceptions (returns LOW with error), returns confidence levels and claim lists. No annotations, so description carries burden well, though could mention idempotency.
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?
Three concise sentences with front-loaded purpose and no fluff. Version number is minor but acceptable.
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?
Covers main behavior and return structure given no output schema. Could add more detail on return format (e.g., type of lists) but sufficient for most use cases.
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 covers 100% of params. Description adds value: 'Missing IDs are silently dropped' for fact_ids and default model info for verification_model.
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 uses specific verb 'verify' and resource 'answer grounded in facts', with unique approach 'Adversarially' and 'Coach LLM'. It clearly distinguishes from sibling tools like find_contradictions.
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?
Implied usage for thorough verification, but no explicit when-to-use or when-not-to-use guidance compared to alternatives like find_contradictions or query_fact.
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?
Despite no annotations, the description thoroughly discloses behavioral traits: it explains what the proof bundle includes (entry, signed epoch with Ed25519+SLH-DSA hybrid signature, RFC 6962 Merkle inclusion proof, full epoch chain), notes the version (v0.13), and specifies prerequisites and error scenarios. This far exceeds the burden of unannotated tools.
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 efficiently structured: first sentence defines the action and output, second sentence details the bundle contents, third sentence covers prerequisites and error conditions. No extraneous words; each sentence serves a distinct 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?
Given the complexity of a cryptographic proof tool, no output schema, and no annotations, the description provides substantial context: it lists the components of the returned bundle, explains the requirement, and covers error cases. It does not explain how to interpret the proof or the exact format, but for an AI agent the details given are sufficient to decide when and how to use the 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?
With 100% schema description coverage, the baseline is 3. The description adds meaning by clarifying that row_id is for 'fact, constraint, event, or decision ID', which goes beyond the schema's 'ID of the fact / constraint / event / decision'. It also explains the purpose of the parameter in context. However, no additional format or constraints are given, so one point above baseline.
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: 'Return a cryptographic inclusion-proof bundle for a persisted row_id'. It specifies the verb 'return', the resource 'cryptographic inclusion-proof bundle', and the input 'row_id (fact, constraint, event, or decision ID)'. This distinguishes it from sibling tools like get_audit_log_head or get_compaction_audit.
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 explicitly states when to use the tool: for proving inclusion of a persisted row_id in the tamper-evident audit log. It also provides clear context: requires WORLD_MODEL_AUDIT_LOG=on at startup, and describes error conditions (opt-in off, row_id not found, entry in unclosed backlog). No alternative tool is named, but the context is sufficient to avoid misuse.
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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