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

The description discloses specific behavioral details beyond the readOnly/openWorld annotations: it mentions returning 'character offsets and similarity scores', the embedding model 'BGE-base-en embeddings + cosine over 500-char overlapping windows', and the 'cap is 200K chars (longer inputs are truncated and flagged)'. These details inform the agent about output structure and limitations.

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 compact yet information-dense, covering purpose, usage example, when-to-use, integration, and technical specs in five sentences. Each sentence contributes unique information, with no filler or redundant claims.

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 the tool's moderate complexity (3 params, no output schema), the description covers all essential aspects: purpose, input examples, output format (top-N passages with offsets and scores), use case, integration with a sibling, and a critical constraint (200K char cap with truncation flag). It is sufficient for an agent to correctly invoke the tool and interpret results.

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 provides comprehensive descriptions for all 3 parameters (100% coverage). The description's prose ('Pass the text you already pulled... plus a natural-language query') largely restates the schema. While it adds example contexts (SEC 10-K, article, tool result), these are illustrative rather than essential for parameter understanding. Thus baseline 3 is appropriate.

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', specifying a clear verb ('search') and resource ('fetched record'). It distinguishes itself from siblings by emphasizing that it operates on already-pulled text, unlike broader tools like ask_pipeworx. The phrase 'get back the top-N passages' clarifies the deliverable.

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 'Use when the record is too big to cram into the prompt' and suggests pairing with 'ask_pipeworx_grounded', explaining the workflow: 'fetch with the gateway, ground over the relevant passages instead of the whole document.' This provides clear when-to-use and alternative usage guidance.

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