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

Beyond the annotations (readOnlyHint, idempotentHint, destructiveHint), the description discloses concrete behavioral details: BGE-base-en embeddings, cosine similarity over 500-char overlapping windows, a 200K character cap with truncation-plus-flag, and offsets for verifying verbatim quotes. This adds substantial operational context the agent needs to use the tool correctly.

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 efficiently front-loaded with the purpose, then gives a usage scenario, a sibling pairing, and technical parameters—all in a single dense paragraph. Every sentence adds value: no filler, no repetition of schema or annotations, and it stays easily scannable.

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 tool with no output schema, the description adequately covers what the agent will receive (top-N passages, offsets, similarity scores) and important input constraints (200K truncation). It also explains the algorithmic approach and how the tool fits into a broader workflow (fetch → search within → ground), making it complete for the given 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?

The input schema already covers all params at 100%, and the description adds meaning by explaining that 'text' is content already pulled from elsewhere (e.g., a 10-K body) and that 'query' is a natural-language request. It reinforces the limit default without needing to restate the schema, so it provides extra context rather than redundancy.

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,' a specific verb+resource+scope that clearly differentiates this from siblings like ask_pipeworx or ask_pipeworx_grounded. It also specifies the return format (top-N passages with offsets and similarity scores), removing any ambiguity about what the tool does.

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?

Explicitly states when to use it ('Use when the record is too big to cram into the prompt') and names a direct alternative/companion ('Pairs with ask_pipeworx_grounded'), telling the agent to fetch with the gateway and ground over relevant passages. This gives clear decision-making context for choosing this tool over siblings.

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