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

Beyond the annotations (readOnly, openWorld, idempotent, non-destructive), the description discloses several important behavioral traits: BGE-base-en embeddings, cosine similarity over 500-char overlapping windows, a 200K character cap with truncation flagged, and output details including character offsets and similarity scores. This gives the agent a clear model of what the tool does internally and what to expect in results.

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 a single compact paragraph that front-loads the core purpose first. Each sentence earns its place: purpose, use case, pairing with a sibling, technical details, and limitations. There is no filler or repetition, and the structure flows logically from what to how to when.

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 no output schema, the description fully covers what the agent will receive (top-N passages with offsets and scores). It also covers input constraints (cap, truncation), the intended workflow (pairing with ask_pipeworx_grounded), and the problem it solves (context savings). This is complete for a relatively simple tool with well-covered parameters.

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 how the text is processed (embeddings, windows, truncation) and that the output includes offsets and scores, which enriches the meaning of 'limit' and 'text' beyond the simple schema descriptions. It also reinforces the purpose of the query parameter with natural-language examples.

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 opens with 'Semantic search INSIDE a fetched record,' which clearly identifies the verb (search), the resource (a fetched record), and the scope (inside that record). It further distinguishes itself from the sibling ask_pipeworx_grounded by positioning search_within as the tool for digging into an already-fetched document while the sibling grounds over the relevant passages.

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 states when to use the tool: 'Use when the record is too big to cram into the prompt.' It also gives a concrete alternative and integration path: 'Pairs with ask_pipeworx_grounded: fetch with the gateway, ground over the relevant passages instead of the whole document,' which clarifies the intended workflow and exclusion.

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