update_ai_analysis

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 describes the tool's function (updating HTML reports with analysis) and prerequisites, but doesn't mention potential side effects (e.g., overwriting existing content), error conditions, or output format. The description adds value with the usage checklist and subscription context, but lacks details on mutation behavior, permissions, or response expectations.

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 structured with a purpose statement, a numbered checklist, and a usage condition. However, it's somewhat verbose for a tool description—the checklist could be more concise or moved to documentation. The information is front-loaded with the main purpose, but the detailed prerequisites might be better suited for a separate usage guide.

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 (updating reports with structured data), no annotations, and no output schema, the description does a reasonably complete job. It explains the tool's purpose, provides detailed prerequisites, and specifies usage context. However, it lacks information on what the updated report looks like, error handling, or confirmation of changes, which would be helpful for a mutation tool.

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 100%, so the schema already documents all parameters thoroughly. The description doesn't add any parameter-specific information beyond what's in the schema. It mentions '課題と解決策' (issues and solutions) which aligns with the 'issues' and 'solutions' parameters, but provides no additional syntax, format, or usage details. Baseline 3 is appropriate when the schema does the heavy lifting.

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

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

The description clearly states the tool's purpose: '既存のHTMLレポートにClaude Codeが分析した課題と解決策を追加します' (adds issues and solutions analyzed by Claude Code to an existing HTML report). This specifies the verb (add/update), resource (HTML report), and content (issues and solutions). However, it doesn't explicitly differentiate from sibling tools like 'analyze_survey' or 'extract_keywords', which appear to be separate analysis tools rather than report updaters.

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 guidelines: '使用前に必ず以下を実施してください' (before use, always do the following) with a 5-step checklist for data preparation. It also specifies when to use this tool: 'APIキーなしでClaude Codeサブスクリプションのみで利用する場合に使用します' (use when using only Claude Code subscription without API key). This gives clear context and prerequisites.

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