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

The description adds significant behavioral context beyond the annotations, such as the embedding model (BGE-base-en), similarity metric (cosine), window size (500-char overlapping), character cap (200K chars) with truncation and flagging, and the fact that each passage includes a character offset for verification. No contradictions 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?

The description is concise (three sentences) and front-loaded: the first sentence states the primary action, the second explains when to use and the pairing, and the third provides technical specifics. Every sentence adds unique value with no redundancy.

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 lacking an output schema, the description fully explains what is returned: top-N passages with character offsets and similarity scores. It also covers limits (200K chars, truncation flagging), the embedding model, and pairing with a sibling tool. This is complete for the tool's complexity.

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%, so the baseline is 3. The description adds value by explaining the purpose of each parameter: 'text' is the document to search (max 200K chars), 'query' is a natural-language query with examples, and 'limit' controls the number of passages. This enhances understanding beyond the schema 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 performs semantic search inside a fetched record, specifying the verb 'search within', the resource 'a fetched record', and the use case when the record is too big for the prompt. It also distinguishes from sibling tools like 'ask_pipeworx_grounded' by explaining how they pair.

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?

The description explicitly says when to use: 'Use when the record is too big to cram into the prompt' and explains that it saves context by returning only relevant passages. It also provides a pairing guideline with 'ask_pipeworx_grounded' for grounding over the results instead of the whole document.

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