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

Annotations declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, destructiveHint=false. The description adds critical behavioral details: 'BGE-base-en embeddings + cosine over 500-char overlapping windows; cap is 200K chars (longer inputs are truncated and flagged).' This goes well beyond annotations and provides full transparency.

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 short paragraph with three sentences. It front-loads the purpose, provides usage guidance, and details behavior without any wasted words. Every sentence earns its place.

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 no output schema, the description explains the output: 'top-N passages with character offsets and similarity scores.' It also covers embedding model, windowing, and character limits. For a tool with three parameters, this is very complete.

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% with good descriptions for each parameter. The description reinforces these by explaining output format (passages with offsets and similarity scores) and providing query examples. This adds substantial meaning 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?

Clearly states 'Semantic search INSIDE a fetched record' and distinguishes from sibling ask_pipeworx_grounded by noting that search_within is for searching within a record, while the other grounds over passages. The verb 'search' and resource 'inside a fetched record' are specific and 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?

Explicitly says 'Use when the record is too big to cram into the prompt' and provides a pairing strategy with ask_pipeworx_grounded: 'fetch with the gateway, ground over the relevant passages instead of the whole document.' This gives clear context and alternatives.

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