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

Description goes beyond annotations (readOnlyHint, etc.) by detailing the embedding model (BGE-base-en), windowing (500-char overlapping), similarity metric (cosine), and truncation behavior (200K char cap, flagged). Also explains that every passage carries an offset for verification.

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?

Description is a single well-structured paragraph: purpose first, then usage guidance, then technical details. Every sentence adds critical information without redundancy. Front-loaded with key point.

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 explains that results are passages with character offsets and similarity scores, and covers constraints (200K char limit, truncation warning). Sufficient for the tool's complexity and parameter count.

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 baseline is 3. The description adds value by providing natural-language query examples and clarifying the truncation behavior for the 'text' parameter. Exceeds baseline but not max due to schema already being sufficient.

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 clearly states 'Semantic search INSIDE a fetched record' with examples like SEC 10-K and long tool results. It differentiates from siblings by mentioning 'Pairs with ask_pipeworx_grounded', but could be more explicit about when not to use this over siblings.

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: 'Use when the record is too big to cram into the prompt'. Mentions pairing with ask_pipeworx_grounded as an alternative workflow, and describes the benefit (saves context, returns relevant passages). No exclusions needed.

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