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

Annotations provide read-only, open-world, idempotent, non-destructive hints. The description adds behavioral details beyond annotations: uses BGE-base-en embeddings + cosine over 500-char overlapping windows, cap of 200K chars with truncation flagged. No contradiction with annotations.

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?

Description is concise and well-structured. First sentence states core action, second sentence describes inputs/outputs, third gives usage context, fourth pairs with sibling, fifth details technical implementation. No redundant sentences.

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?

Despite no output schema, the description explains return values: top-N passages with character offsets and similarity scores. It also covers limits (200K chars, truncation flag), parameters, and pairing. Complete for a search tool.

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%, and the description adds meaningful context: for 'text' it explains max ~200K chars, for 'limit' default 5, and for 'query' provides examples and clarifies it's a natural-language query. This enriches the schema's minimal descriptions.

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 the tool's purpose: 'Semantic search INSIDE a fetched record'. It specifies the verb 'search', the resource 'inside a fetched record', and explains inputs (text, query) and outputs (passages with offsets, scores). It distinguishes from siblings like ask_pipeworx_grounded by mentioning pairing.

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?

Explicit usage guidance: 'Use when the record is too big to cram into the prompt' and provides an alternative workflow: 'Pairs with ask_pipeworx_grounded: fetch with the gateway, ground over the relevant passages'. This clearly differentiates when to use this tool versus others.

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