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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world), so the description is free to add genuinely new context: which fields are matched, that results are ordered best-match-first, and the important provenance caveat that entries are "documentation-checked only, not installed or audited." That caveat is real behavioral information an agent needs before recommending a tool.

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?

Four short sentences, front-loaded with purpose, then matching behavior, then the output instruction and caveat. Every sentence carries information; there is no filler, though the sentence about showing access notes to the human is more of a policy reminder than tool description.

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?

With an output schema present, the description need not explain return shapes, and it correctly focuses on matching semantics, ranking, and the trust caveat. The remaining gap is sibling differentiation — nothing tells the agent when to prefer get_gear or recommend_stack over a free-text search.

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 100%, so the baseline is 3, but the description adds meaning the schema does not: the specific fields searched (name, category, description, audience, access notes), which tells the agent how to phrase a query. The ranking rule and empty-string-plus-category pattern are duplicated from the schema rather than extended.

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 names a specific verb and resource ("Search the Gearlist catalog of source-checked AI agent tools, MCP servers and skills") and describes the matching scope. It is clear what the tool does, but it never distinguishes itself from siblings like get_gear, list_skills or recommend_stack, so an agent must infer the boundary.

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?

Usage is implied by the keyword-search framing, and the description adds an output-handling instruction ("show the human" the access notes). However, it gives no explicit when-to-use versus get_gear or recommend_stack, and the useful routing hint for listing a whole category lives in the schema, not the description.

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