collect_article_evidence

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

With no annotations, the description must carry behavioral disclosure. It does add some behavioral expectations: it reads public bodies, keeps failures explicit, and separates demo bodies. However, it omits network side effects, what 'demo bodies' means, and how failures are represented.

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 one concise sentence with the primary action front-loadedcars and no wasted words. The second clause is cryptic but still contributes behavioral caveats.

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?

An output schema exists, but the description still leaves key invocation details ambiguous: what shape 'news' must take, how max_articles applies, and why demo bodies must be kept separate. An agent would likely need to inspect sibling tool outputs to call this correctly.

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 0%, so the description must compensate. It does not explain the required 'news' object shape or that max_articles limits how many article bodies are processed. The description adds little beyond what the parameter names already imply.

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 states a concrete operation ('Read public article bodies into source-linked paragraph evidence') and distinguishes this from sibling tools that fetch, summarize, or analyze crypto news. It is somewhat jargon-heavy, but the core purpose is identifiable.

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?

There is no explicit guidance on when to use this tool versus fetch_today_crypto_news, summarize_crypto_news, or analyze_crypto_insights. The phrase about failures and demo bodies reads like behavior notes, not usage direction.

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