analyze_market

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

Since no annotations are provided, the description carries the full burden. It describes the expected outputs (e.g., monthly trends, top organizations) but does not mention any critical behavioral aspects such as data source freshness, authentication requirements, rate limits, or absence handling. The presence of an output schema partially compensates, but the description lacks deeper 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.

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

The description is well-structured with a clear purpose sentence followed by a bulleted list of outputs and an Args section. It is front-loaded and every sentence adds value. Minor redundancy could be trimmed, but overall it is appropriately concise.

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 moderate complexity (3 parameters, 1 required) and presence of an output schema, the description covers the parameter semantics and output briefly. However, it lacks usage guidelines and behavioral details, which leaves some completeness gaps. It is adequate but not fully comprehensive.

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, so the description adds essential meaning. Each parameter is explained: 'keyword' is the analysis keyword with examples ('AI 챗봇', '클라우드'); 'period_months' is described as the analysis period with a default of 12 months; 'business_type' is explained as a business type or 'all' summing 4 types. This goes far beyond the bare schema types and defaults.

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 with a specific verb ('분석') and resource (시장 동향, market trends). It lists concrete outputs (monthly trends, average bid ratio, etc.), making it easy to understand. It also distinguishes from siblings like 'analyze_competitor', which focuses on competitors rather than market trends.

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 does not provide explicit guidance on when to use this tool versus its siblings, nor does it mention any prerequisites or limitations. It only describes what the tool does, leaving the agent to infer usage from context. No 'when-not' or alternative tool names are given.

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