get_industry_intelligence

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

No annotations provided, so description carries full burden. It does not disclose behavior like idempotency, data freshness, error handling, or authentication needs. Only lists output content.

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 short sentence, which is concise but underwhelming. It lacks structure and does not front-load the primary action.

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 no output schema and moderate complexity (2 parameters, industry focus), the description fails to fully convey what the tool returns or its relationship to sibling tools like risk_assessment.

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% (parameters have no descriptions). The tool description does not explain the 'ticker' or 'market' parameters, leaving the agent uninformed about their meaning or default behavior.

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 lists specific outputs (sector sub-domains, demand drivers, CAGR, risks) which clearly indicate the tool provides industry-level intelligence. It distinguishes from siblings like get_financials (company-level) and compare_peers (peer comparison).

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?

No explicit guidance on when to use or avoid this tool. No mention of prerequisites or alternatives. The agent must infer usage from the output list.

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