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

Beyond annotations (readOnly, idempotent, non-destructive), the description reveals the embedding model (BGE-base-en), windowing strategy (500-char overlapping windows), similarity metric (cosine), and the 200K-character cap with truncation behavior flagged. It also notes offsets for verification, adding rich behavioral context.

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 and well-structured: it front-loads the core purpose, then usage guidance, then technical details. Every sentence adds value—purpose, use case, workflow, and implementation specifics—without redundancy or padding.

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 clearly states the return format: top-N passages with character offsets and similarity scores. It covers input constraints, algorithm details, and how to integrate with a related tool, making it complete for an agent to invoke correctly without missing information.

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% with detailed descriptions for text, query, and limit. The description adds only contextual framing (e.g., 'text you already pulled', 'top-N passages') but no substantial new semantics beyond the schema. The baseline of 3 applies since the schema already carries the explanatory weight.

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 states a specific verb ('Semantic search') and a specific resource ('inside a fetched record'), with clear examples of input and output. It distinguishes itself from siblings by emphasizing it works on text the agent has already pulled, unlike tools that fetch documents. The pairing note with ask_pipeworx_grounded further clarifies its unique role.

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 says 'Use when the record is too big to cram into the prompt' and contrasts with ask_pipeworx_grounded by explaining the intended workflow: fetch with gateway, then ground over relevant passages. This gives clear when-to-use and alternative guidance.

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