Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description adds value beyond annotations by clarifying the read-only nature ('Mode: Read-only') and detailing the return of quality scores and findings. Annotations already indicate readOnlyHint=true and idempotentHint=true, and the description reinforces these without contradiction.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with sections for purpose, usage, result, mode, criteria list, and workflow. It is comprehensive but not excessively verbose. Minor redundancy exists (e.g., result and typical workflow), but overall it is efficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the presence of an output schema, the description appropriately focuses on behavior and usage. It covers the tool's purpose, criteria, read-only mode, and typical workflow. Missing parameter explanations reduce completeness, but the overall context is sufficient for most agents.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description should compensate by explaining each parameter. While it lists the seven quality criteria assessed, it does not clarify that the 'criteria' parameter allows selecting which ones to evaluate. The 'project_path' and 'docs_path' parameters are not explained in the description, relying solely on their schema names.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool assesses documentation quality against 7 specific criteria, with scores and actionable findings. It distinguishes itself from sibling tools like docmgr_validate_docs by focusing on quality assessment rather than validation or detection.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly provides usage contexts: auditing documentation health, before major releases, and tracking improvements. It also suggests a typical workflow. However, it does not explicitly state when not to use the tool or mention alternative tools for other scenarios.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already indicate read-only, non-destructive, and idempotent behavior. The description reinforces this and adds context about modes (checksum vs git_diff) and results (categorized changed files), providing extra value beyond annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with sections for purpose, usage, result, modes, and workflow. Every sentence adds value without repetition, making it efficient and easy to parse.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the presence of an output schema and comprehensive annotations, the description covers all necessary aspects: purpose, usage, behavior, parameters, and workflow. An agent has enough information to select and invoke the tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 0% coverage, but the description explains the mode and include_semantic parameters, and implies since_commit's role in git_diff. It does not elaborate on project_path, but the overall parameter guidance is sufficient for correct usage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool detects code changes without modifying baselines, specifies it is pure read-only, and distinguishes it from sibling tools like docmgr_update_baseline by emphasizing detection over modification.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit use cases ('when checking if documentation is out of sync after code changes') and a typical workflow, guiding the agent on when to invoke. However, it does not explicitly list alternatives or when not to use.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true and destructiveHint=false. The description reinforces this with 'Mode: Read-only' and adds behavioral context (checks config files, returns recommendations). It goes beyond annotations by explaining the detection process.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Description is brief (3 short paragraphs), front-loaded with purpose, then usage, result, mode, detection details, and workflow. Every sentence adds value without redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple detection tool with one parameter and an output schema, the description covers purpose, usage, mode, detection mechanism, and typical workflow. Minor omission: no mention of error handling if no platform detected, but overall complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%—the 'project_path' parameter has no description. The description implies its purpose (project root where config files reside) through context like 'checks for platform-specific config files', but does not explicitly define the parameter or its expected format. Partial compensation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool auto-detects documentation platforms (MkDocs, Sphinx, Hugo, etc.) or recommends one. It specifies the detection method (checking config files), making it distinct from sibling tools like docmgr_init or docmgr_validate_docs.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides explicit 'Use when' context (first-time setup, unsure platform) and a 'Typical workflow' (run before docmgr_init). This helps agents decide when to invoke it, though it does not explicitly list situations to avoid.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description states 'State-modifying (creates files and directories)' and lists specific outputs (config, baselines, optionally documentation structure). This adds significant context beyond annotations, which only provide idempotentHint=true. No contradiction with annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is relatively concise and uses a clear structure with sections for 'Use when', 'Result', 'Mode', and 'Typical workflow'. It packs useful information without being verbose, though the parameter section is missing.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite having a output schema (not shown), the description lacks critical details about parameters and return values. For a tool with 7 parameters and state-modifying behavior, the description is incomplete, leaving the agent to guess about most inputs and outputs.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With schema description coverage at 0%, the description does not explain any of the 7 parameters except for 'mode' by referencing 'existing' and 'bootstrap' in the Modes section. Other parameters like project_path, platform, exclude_patterns, docs_path, sources, and use_gitignore are entirely undocumented. This is a critical gap.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool initializes doc-manager for a project, with two modes for existing or new docs. This verb+resource combination is specific and distinguishes it from sibling tools like docmgr_assess_quality and docmgr_detect_changes.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly says 'Use when: Setting up doc-manager for the first time in a project' and 'Typical workflow: Run once at project setup, before any other doc-manager tools.' It provides clear context but does not explicitly state when not to use it or list alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already indicate readOnlyHint=false and destructiveHint=false. The description adds behavior about preserving git history, rewriting links, and regenerating TOC, but does not fully disclose potential risks like file deletion or revertibility. It adds moderate context beyond annotations but lacks comprehensive behavioral coverage for a migration tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Description is well-structured with sections ('Use when', 'Result', 'Mode', 'Options'), making it scannable. It is slightly verbose but each sentence adds value. No wasted words, though could be more compact.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given complexity (8 parameters, 0% schema coverage) and existence of output schema, the description covers workflow and boolean options but omits details on target_platform, target_path defaults, and error handling. Incomplete for a migration tool, leaving gaps for the agent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, so description must compensate. It explains the boolean options (preserve_history, rewrite_links, regenerate_toc, dry_run) with their effects, but does not explain required parameters like project_path and source_path, nor optional target_platform. The explanation is partial, meriting a mid-range score.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool migrates or restructures documentation with specific verb and resource. It distinguishes from sibling tools by stating 'Use when: Moving docs to new location...' which differentiates it from other doc management tasks.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicit 'Use when:' section provides clear context for when to employ this tool. It also includes a typical workflow with dry_run recommendation, guiding the agent on proper usage and previewing before execution.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations provide readOnlyHint=false and idempotentHint=true. The description adds value by explaining that mode='check' is read-only and mode='resync' modifies baselines atomically, and detailing the orchestration steps. No contradiction with annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with an overview, usage guidance, result summary, mode explanations, and a typical workflow. It is front-loaded with the purpose, and every sentence adds value without being verbose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (orchestrating multiple sub-tools) and that an output schema exists (not shown), the description provides a thorough overview, workflow, and mode details. It could mention prerequisites (e.g., initialized docs) but is otherwise quite complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, so the description must compensate. It explains the 'mode' parameter and its two values (check, resync) in detail. However, it does not describe 'project_path' or 'docs_path' explicitly, though their purpose is implied. Partial compensation, but could be more explicit.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool orchestrates a complete documentation sync, listing specific actions (detect changes, validate, assess quality, update baselines). It distinguishes from siblings like docmgr_assess_quality or docmgr_detect_changes by being a higher-level orchestrator.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly says 'Use when: After code changes to get complete documentation health report, or after doc updates to reset baselines' and outlines a typical workflow. It contrasts modes (check vs resync) but does not explicitly mention when to use sibling tools instead.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already indicate idempotentHint=true and not read-only. The description adds valuable context: 'Mode: State-modifying (rewrites baseline files)', 'Atomically updates three baseline files', and 'This resets change detection to current state'. No contradiction with annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with clear sections (Use when, Result, Mode, Workflow) and is concise. Minor redundancy (e.g., 'update all baseline files' and 'resets change detection') prevents a perfect score.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has 2 parameters and 0% schema coverage, the description should explain the parameters. It does cover purpose and behavior thoroughly and the output schema exists so return values are not needed. The missing parameter semantics reduce completeness.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% and the description does not explain the two parameters (project_path, docs_path) beyond their names. With no documentation in schema or description, the agent gets no guidance on what values to provide or their format.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('update all baseline files') and lists the specific files affected (repo-baseline.json, symbol-baseline.json, dependencies.json). It distinguishes from siblings like docmgr_detect_changes (detects changes) and docmgr_sync (syncronizes).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit usage guidance: 'Use when: After updating documentation to match code changes, resetting the clean baseline' and includes a typical workflow. It does not explicitly state when not to use or list alternatives, which would elevate it to 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already provide readOnlyHint=true, destructiveHint=false, and idempotentHint=true. The description adds that it is 'Read-only (only analyzes documentation)' and notes that validate_code_syntax is 'slower'. This provides useful behavioral context beyond the annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise and well-structured with sections for usage, result, mode, optional checks, and workflow. Every sentence adds value, and there is no redundancy or wasted text.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 7 parameters, 1 required, 0% schema descriptions, and an output schema, the description covers the main checks and the result format. It could be more explicit about the path parameters, but it provides sufficient context for effective use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema has 0% description coverage. The description compensates by explaining each optional boolean check (e.g., 'Validate internal links', 'Verify images/assets exist'). However, it does not elaborate on the project_path or docs_path parameters, which could benefit from additional clarity.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Validate documentation for broken links, missing assets, code snippet syntax, and convention compliance.' It uses a specific verb and resource, listing distinct validation categories. This differentiates it from sibling tools like docmgr_assess_quality or docmgr_detect_changes.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly provides usage scenarios: 'Use when: Before releases, after major doc updates, or as part of CI/CD' and mentions a typical workflow. While it does not explicitly mention alternatives, the context implies when to use this tool over others.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.