match_queries

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

No annotations are provided, so the description carries full burden. It explains the scoring process and output verdicts but does not explicitly state side effects or whether the tool is read-only. The instruction to write a file from another tool's response adds some clarity.

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 concise, covering key aspects in a few sentences. No redundant information, though it could be slightly more structured for easier parsing.

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 no output schema and lack of annotations, the description covers input format, preprocessing, and output logic. However, it omits details on the scoring algorithm, behavior of site and saveToFile parameters, and any prerequisites.

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 50%. The description adds context for queries and queriesFile (e.g., field names, source), but ignores site and saveToFile parameters entirely. It partially compensates for the gap.

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 matches search queries with site articles to produce boost or new recommendations. It distinguishes itself from sibling tools like audit_content or list_articles by focusing on query-article matching.

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?

Provides explicit preprocessing instructions (filter positions 8-30, format queries from another tool). However, it does not mention when not to use this tool or offer comparisons to sibling tools.

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