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

While annotations already indicate a safe read-only operation, the description adds valuable behavioral context: BGE-base-en embeddings, 500-char overlapping windows, a 200K character cap with truncation flagging, and the return format (passages with offsets and similarity scores). This goes well beyond the 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 information-dense but well-organized: it front-loads the core purpose, then provides usage context, and concludes with technical details. Every sentence contributes value without redundancy or fluff.

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 prepares the agent by explaining return values, edge cases (truncation), and how it integrates with other tools. It covers enough context for correct invocation and interpretation of 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?

Schema coverage is 100% with descriptions for all three parameters. The description reinforces the 'text' parameter with a concrete example and provides example queries for 'query', but it does not add significant new meaning beyond what the schema already offers. The baseline of 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', clearly stating the verb, resource, and scope. It distinguishes the tool from siblings by emphasizing that it operates on already-fetched text, and even contrasts with ask_pipeworx_grounded for the grounding workflow.

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', providing a clear when-to-use criterion. It also names an alternative workflow (ask_pipeworx_grounded) and explains how they pair, offering actionable guidance on tool selection.

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