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

No annotations are supplied, so the description carries the full burden and does a good job: it discloses the retrieval method (TF-IDF + cosine similarity over catalogue metadata), the shape of the result (top-N with a relevance score), and the auth requirement ('FREE, no key required'). It does not discuss ordering guarantees, tie-breaking, or whether an empty result is possible, which keeps it below a 5.

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 the core distinction and ending with the practical auth note. The phrase 'TF-IDF + cosine similarity' is implementation detail that does little for tool selection and slightly dilutes an otherwise tight 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?

For a two-parameter search tool with no output schema, the description covers purpose, method, result shape, the alternative to prefer, and cost/auth. Nothing an agent needs in order to call this correctly is missing.

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 both parameters are already documented by the schema, which sets the baseline at 3. The description adds modest value by establishing that the query is matched semantically rather than by keyword, but it adds nothing about the 'count' parameter beyond what the schema states.

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 ('Find patterns') and immediately defines the retrieval mode ('by meaning, not by keyword'), which separates it from list_patterns, get_pattern, and recommend_patterns. The description of what fields are searched (title, tags, style, industry_fit, role, tech) further pins down what kind of result to expect.

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?

Names the sibling alternative and the exact condition that selects this tool: use it 'when recommend_patterns misses because the brief uses different vocabulary than the tags.' That is an explicit when-to-use with a named fallback trigger rather than implied guidance.

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