Industry News

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

Beyond the annotations (readOnlyHint, idempotentHint), the description adds behavioral context: data refreshed every 30 minutes, the return payload includes detected market/operator entities, and the scope is limited to industry news. It also corrects a common parameter mistake ('category', not 'topic'). No contradictions with annotations.

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 longer than necessary but front-loaded with the most critical decision (execute_plan vs get_news). Each sentence earns its place, covering purpose, sources, refresh, return fields, filters, a common pitfall, and exclusions. Slight verbosity keeps it from a perfect score.

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 7-parameter tool with no required parameters and an output schema, the description covers purpose, usage boundaries, data freshness, return fields, a parameter example, and explicit exclusions. It is fully complete for an AI agent to select and invoke the tool correctly, even without reading the schema or annotations.

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 a baseline of 3 applies. The description adds a usage example (category=AI limit=10) and explicitly warns about the correct parameter name, adding practical meaning beyond the schema. However, most parameter details are already in the schema, so the extra value is modest.

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 returns curated data center industry news from 40+ trade sources with specified fields (title, summary, source, published_at, entities). It distinguishes from siblings by explicitly naming execute_plan, list_transactions, and get_pipeline as alternatives for other use cases.

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?

Provides explicit when-to-use and when-not-to-use guidance: use execute_plan if news is only one input to a larger question, use get_news directly for headline requests, and avoid this tool for structured M&A deal data (use list_transactions) or construction pipeline (use get_pipeline). Also includes a concrete example invocation.

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