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

Annotations already declare readOnlyHint=true and idempotentHint=true, but the description adds valuable behavioral details: returns character offsets and similarity scores, uses BGE-base-en embeddings with 500-char overlapping windows, and has a 200K char cap with truncation flagged. No contradictions 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?

The description is dense but every sentence earns its place. It front-loads the primary purpose, then covers benefits, pairing, technical mechanism, and limits. At roughly 100 words, it is appropriately sized for the tool's complexity without redundancy.

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 3-parameter tool with no output schema, the description covers everything needed: purpose, usage scenario, return format (top-N passages with offsets and scores), algorithmic details, and input limits. It is complete enough for an agent to select and invoke the tool correctly.

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 the baseline is 3. The description reinforces parameter meaning ('Pass the text you already pulled... plus a natural-language query') but does not add significant information beyond the schema's existing descriptions for text, query, and limit. The truncation/flagging behavior is useful context but is more behavioral than parameter-specific.

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 a specific verb and resource: 'Semantic search INSIDE a fetched record.' It clearly distinguishes itself from siblings by emphasizing the input is user-supplied text, not a PipeWorx query, and it explicitly differentiates from ask_pipeworx_grounded by noting it operates on a passage level.

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?

The description gives an explicit use case: 'Use when the record is too big to cram into the prompt.' It also names a complementary sibling (ask_pipeworx_grounded) and explains the workflow: fetch with the gateway, then ground over passages. This provides clear when-to-use guidance and alternatives.

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