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

No annotations are provided, so the description must disclose behavioral traits. It does so comprehensively: returns up to 12 candidates, explains the signals (role, protocols, etc.), and warns that fit.status='unknown' means fields were not extracted, and results are untrusted data.

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 efficient: three sentences covering deprecation, scope, behavior, and warnings. Front-loaded with the critical deprecation notice, 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?

Given the simple one-parameter tool with no output schema, the description is remarkably complete, covering the corpus, result count, signals, edge cases, and trustworthiness. No gaps for the agent.

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 single parameter 'query' has 100% schema coverage, but the description adds valuable beyond-schema context by specifying the expected format ('Short keyword phrase') and prohibitions (no project names, paths, or secrets).

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 it is a deprecated free-text keyword search over a specific corpus (GitHub repos with >=2000 stars), explicitly distinguishing it from the sibling tool find_fit_candidates by noting it lacks constraint checking and pass/fail verdicts.

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 explicitly advises to use find_fit_candidates for new integrations, and clarifies this tool is for compatibility-only searches. It sets clear expectations about what the tool does and does not do.

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