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

Annotations already mark it as read-only, open-world, idempotent, and non-destructive. The description adds significant behavioral detail beyond annotations: 'BGE-base-en embeddings + cosine over 500-char overlapping windows; cap is 200K chars (longer inputs are truncated and flagged).' It also discloses the return format (passages with offsets and 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 compact but information-dense. It front-loads the core purpose, then efficiently covers use case, pairing, algorithm, limits, and output characteristics—every sentence earns its place with no filler.

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?

Despite lacking an output schema, the description clearly states what the results contain: 'top-N passages with character offsets and similarity scores.' It also covers the truncation behavior, the maximum input size, and how to use it with a companion tool, making the tool's behavior 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 coverage is 100% with detailed descriptions for all three parameters. The description adds contextual examples like 'a SEC 10-K body, an article, a long tool result' and query examples, but these are already mirrored in the schema. It does not add significant new meaning beyond what parameter descriptions provide, so the baseline of 3 is appropriate.

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', giving a specific verb and resource that clearly distinguish it from the sibling tools like ask_pipeworx (which likely queries external data). It also explains the value proposition—saving context, returning only relevant passages—making its purpose unambiguous.

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?

Explicit guidance is provided: 'Use when the record is too big to cram into the prompt' and it directly names a companion alternative: 'Pairs with ask_pipeworx_grounded: fetch with the gateway, ground over the relevant passages instead of the whole document.' This gives clear when-to-use and alternative context.

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