get_sector_analysis

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

Annotations already mark readOnlyHint=true, so the safety profile is clear. The description adds value by disclosing the exact return composition (quotes, 30-day K-line, top N constituents), which is more than what annotations provide. It doesn't mention output structure or pagination, but for a read-only composite this is adequate.

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, information-dense sentence. It front-loads the keyword '复合' (composite) and lists the three key data components efficiently. No wasted words.

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 read-only composite tool with 100% schema coverage and no output schema, the description covers the essential behavior and return scope. It could specify the ordering of constituents (by gain) or output format, but the description is sufficiently complete for an agent to know what to expect. Minor gap: no mention of how sector types map to results.

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?

Input schema description coverage is 100%, with all three parameters (topN, type, symbol) documented. The description adds minimal new meaning beyond the schema, only echoing that 'top N' is included in the return. Baseline 3 is appropriate for high schema coverage.

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 this is a composite sector deep analysis tool that returns sector quotes, 30-day K-line, and top N constituents in one call. It distinguishes itself from sibling tools like get_industry_spot or get_concept_kline by being a single aggregated endpoint.

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 implies use when a comprehensive sector data bundle is needed, but it does not explicitly state when to use this vs the alternative single-purpose sibling tools. There are no exclusion criteria or alternative tool references, leaving the decision to the agent.

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