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

Goes well beyond the readOnly/idempotent annotations by revealing the embedding model (BGE-base-en), similarity metric (cosine), text window size (500-char overlapping), input cap (200K chars, truncation flagged), and return payload (character offsets, similarity scores). 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?

The description is long but every sentence contributes value: purpose, use case, pairing, technical details, and limitations. It is front-loaded with the core action and structured logically. No fluff or 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?

With no output schema, the description adequately explains return values (top-N passages with character offsets and similarity scores). It also covers operational constraints (200K character cap, truncation flag) and provides enough context for an agent to invoke it correctly in a retrieval pipeline.

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% and the schema already provides detailed descriptions for each parameter with examples. The tool description adds minimal parameter-specific meaning beyond reinforcing that text is 'already pulled' and query is natural language. It does not systematically elaborate on limit or further parameter semantics.

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 precise verb+resource+scope: 'Semantic search INSIDE a fetched record.' It explicitly differentiates from sibling tools like ask_pipeworx_grounded by emphasizing it operates on already-fetched text, not the whole document or external data.

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?

Clearly states when to use: 'Use when the record is too big to cram into the prompt.' It also provides an explicit alternative/complement: 'Pairs with ask_pipeworx_grounded: fetch with the gateway, ground over the relevant passages instead of the whole document.'

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