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

Annotations already cover read-only, idempotent, non-open-world. The description adds substantive context: result cap of 10, curation/verification ('verified, dated'), the fields returned (symptoms, cause, fix, code example, last-checked date), and the existence of staleness handling. It does not say what happens when the provider is unknown or no traps match, which is the main remaining gap.

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?

Three tight sentences, front-loaded with the trigger, then the return contract, then the sibling disambiguation. No filler or repetition of the title.

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?

No output schema exists, and the description compensates by describing the returned fields and the 10-item cap, which is what an agent needs to consume results. Minor omission: no guidance on empty results or unknown provider slugs.

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% and the four parameters are documented with examples and ranking behavior, so the schema does the heavy lifting. The description adds nothing parameter-specific (no mention of slug format, ranking, or include_stale), so baseline 3 applies.

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?

States a specific verb and resource ('look up traps for a provider') and immediately distinguishes itself from the sibling search_traps by input type (provider vs. error message). An agent can route between them without opening either schema.

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?

Gives an explicit trigger ('Call before writing code against a third-party API, platform, or AI tool') and names the alternative with its selecting condition ('Use search_traps instead when you already have an error message'). Both when-to-use and when-not-to-use are present.

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