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

Annotations already indicate readOnlyHint, idempotentHint, etc. The description adds valuable details: the algorithm (BGE-base-en embeddings + cosine overlap), windowing (500-char overlapping windows), character cap (200K chars with truncation/flagging), and verification mechanism (character offsets). 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 concise (three sentences) and front-loaded with the core purpose, then usage, then technical details. Every sentence adds essential information 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?

Given the tool has no output schema, the description adequately explains the return values (top-N passages with character offsets and similarity scores) and mentions truncation flag. It covers usage context, behavioral traits, and parameter constraints, leaving little ambiguity 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 description coverage is 100%, so the schema already documents all parameters adequately. The description adds some context (e.g., the cap of 200K chars for 'text' and examples for 'query') but does not significantly extend 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 the tool performs semantic search inside a provided text, with specific verb 'search inside' and resource 'fetched record'. It distinguishes itself from siblings by focusing on searching within a pre-fetched text rather than external sources.

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 explicitly states when to use this tool ('when the record is too big to cram into the prompt') and mentions a complementary sibling tool (ask_pipeworx_grounded). It does not provide explicit when-not scenarios, but the guidance is clear.

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