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

Discloses embedding model (BGE-base-en), windowing (500-char overlapping), and character cap (200K chars with truncation flag). These details are beyond annotations (readOnlyHint, idempotentHint), which already indicate safety. No contradiction with 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?

Single paragraph front-loads core purpose and then adds details efficiently. Every sentence adds value; could benefit from slight structural separation but remains clear and non-redundant.

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 three parameters, full schema coverage, and no output schema, the description provides sufficient context: embedding details, truncation behavior, and workflow integration. Missing return format or offset description, but functionality is well-specified.

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?

All three parameters are described in the schema (100% coverage). Description adds examples for query and clarifies limits (max ~200K chars, 1-20 limit), but does not significantly extend beyond schema descriptions.

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?

Clearly states 'Semantic search INSIDE a fetched record' and gives concrete examples (SEC 10-K, article) of input types. Explicitly distinguishes from sibling tools like ask_pipeworx_grounded by explaining their relationship.

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 describes ideal scenarios. Mentions pairing with ask_pipeworx_grounded as an alternative workflow, but does not explicitly list when not to use.

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