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

The description adds substantial behavioral context beyond annotations: embedding model (BGE-base-en), similarity metric (cosine), window size (500-char overlapping), character cap (200K) with truncation flag. No contradiction with annotations (readOnly, idempotent, etc.).

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 packed with information, no wasted words. Front-loaded with the core purpose, then provides usage context and technical details. Excellent structure.

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 fully explains what is returned (passages with offsets, scores, truncation flag). Covers input constraints, embedding details, and pairing advice. Complete for a tool of this complexity.

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 covers all 3 parameters with descriptions (100% coverage). The description adds value by explaining what the tool returns (passages with character offsets and similarity scores), which compensates for the lack of an output schema. However, it doesn't add per-parameter details beyond the schema.

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 it performs semantic search inside a fetched record with a specific verb and resource. It distinguishes from sibling tools by contrasting with ask_pipeworx_grounded, and emphasizes the use case when a record is too large for the prompt.

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 when to use ('too big to cram into the prompt') and provides a pairing suggestion with ask_pipeworx_grounded. While it doesn't list explicit alternatives or when-not-to-use, the context is clear enough for an agent to decide.

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