analyze_survey

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the tool generates HTML reports but doesn't cover critical aspects like whether it modifies input files, requires specific permissions, has rate limits, or handles errors. For a tool with 6 parameters and no annotation coverage, this is a significant gap in transparency.

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 a single, efficient sentence in Japanese that front-loads the core functionality. It wastes no words and directly states what the tool does, making it highly concise and well-structured for its purpose.

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 (6 parameters, no output schema, no annotations), the description is incomplete. It lacks information on behavioral traits, output details, error handling, and usage guidelines. While concise, it doesn't provide enough context for an agent to fully understand how to invoke and interpret results from this 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?

The schema description coverage is 100%, so the schema already documents all parameters thoroughly. The description adds minimal value beyond the schema by listing report components (morphological analysis, WordCloud, graphs), which loosely relates to parameters like 'analysis_axes' and 'enable_ai_analysis'. However, it doesn't provide additional syntax, format details, or usage context for the parameters.

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: analyzing survey CSV files and generating HTML reports with specific components (morphological analysis, WordCloud, graphs). It uses specific verbs ('analyze', 'generate') and identifies the resource ('survey CSV files'). However, it doesn't explicitly differentiate from sibling tools like 'extract_keywords' or 'generate_wordcloud', which might offer overlapping functionality.

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 no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'extract_keywords' or 'generate_wordcloud', nor does it specify prerequisites, ideal scenarios, or exclusions. Usage is implied through the description but lacks explicit context for selection.

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