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

The description goes well beyond annotations by disclosing return format (passages with offsets and similarity scores), the embedding model and algorithm (BGE-base-en + cosine over 500-char windows), and input limits (200K chars with truncation flagged). This adds substantial behavioral context not available from annotations alone.

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?

Three sentences with front-loaded purpose, followed by usage guidance and technical specifics. No redundancy or filler; every sentence contributes meaningful information.

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 explains the return values (passages, offsets, similarity scores), input constraints, and embedding details. For a tool with moderate complexity, this is thorough and self-sufficient.

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%, so baseline is 3. The description adds meaning by clarifying the 'text' parameter should be content already fetched (e.g., SEC filing, article) and explains that 'query' is a natural-language request. It also indirectly describes the output's relationship to 'limit' (top-N passages). This extra context elevates the score above baseline.

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 the tool performs semantic search inside a provided text ('Semantic search INSIDE a fetched record'), with a specific verb, resource, and scope. It distinguishes from siblings by emphasizing it operates on already-fetched content rather than fetching or grounding, and references ask_pipeworx_grounded as a complement.

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?

Explicit when-to-use guidance is given: 'Use when the record is too big to cram into the prompt.' It also names a specific sibling tool (ask_pipeworx_grounded) and explains how the two pair, providing clear context and an alternative.

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