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

Annotations already provide readOnlyHint, openWorldHint, idempotentHint, destructiveHint. The description adds technical details about embeddings (BGE-base-en), cosine similarity, window size (500-char overlapping), and truncation behavior (200K chars, truncated and flagged). This goes beyond annotations and adds significant value.

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 paragraph of about 6 sentences, concise and front-loaded with purpose. It packs key information without wasted words, though the structure could be slightly improved with bullet points or clearer separation of technical details.

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 no output schema, the description still explains return format (passages, character offsets, similarity scores), input constraints, and technical behavior. It covers the use case, pairing, and truncation handling, making the tool fully understandable 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 well. The description repeats this information and adds example queries, but does not provide additional semantics beyond what the schema offers.

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 does semantic search inside a fetched record, using a natural-language query to return relevant passages. It distinguishes itself from siblings by mentioning pairing with ask_pipeworx_grounded and emphasizing that it works on already-fetched text.

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 'Use when the record is too big to cram into the prompt' and describes benefits over alternatives. Also mentions pairing with ask_pipeworx_grounded for grounded reasoning, giving clear when-to-use and when-not-to-use guidance.

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