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

The description discloses rich behavioral details beyond the annotations: returns passages with character offsets and similarity scores, uses BGE-base-en embeddings with 500-char windows, enforces a 200K char cap with truncation flagging. These are valuable operational insights not present in 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 a single dense paragraph that front-loads purpose, then usage, then technical details. Every sentence contributes value, with no filler or repetition.

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?

For a tool with no output schema, the description adequately explains the return format (passages with offsets and scores), algorithmic details, and input limits. It also mentions pairing with a sibling tool, making it fully self-contained for an agent.

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 context by explaining that 'text' is the already-pulled record, 'query' is natural language, and 'limit' controls the number of passages. It also ties parameters to the output (offsets and scores), enhancing understanding 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?

The description opens with 'Semantic search INSIDE a fetched record,' which clearly states the verb (search) and resource (a fetched record). It distinguishes from sibling tools by emphasizing 'INSIDE' and 'fetched,' and explicitly pairs with ask_pipeworx_grounded, clarifying its niche.

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?

It provides explicit guidance: 'Use when the record is too big to cram into the prompt' and pairs with ask_pipeworx_grounded for a specific workflow. This clarifies when to use this tool versus alternatives.

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