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

Annotations only say readOnly/idempotent/openWorld, but the description adds concrete mechanics: 'BGE-base-en embeddings + cosine over 500-char overlapping windows; cap is 200K chars (longer inputs are truncated and flagged).' It also discloses that every passage carries an offset and similarity score, which is more than the annotations reveal. No contradiction.

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?

Three sentences, each earning its place: first the core action, second the usage scenario and pairing, third the technical details. Highly efficient and well-structured.

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?

For a tool with no output schema, the description fully prepares the agent: tells what to expect (passages, offsets, scores), how to use it with examples, technical limits (truncation), and integration with ask_pipeworx_grounded. No significant gaps.

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?

The schema describes all three params, but the description enriches them with real-world examples ('a SEC 10-K body, an article, a long tool result') and clarifies the query style ('natural-language query'). It also clarifies the limit as 'top-N passages' and ties the text param into the usage context.

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 specific action: 'Semantic search INSIDE a fetched record,' which clearly names a verb (search) and resource (record). It distinguishes itself from siblings like ask_pipeworx_grounded by explaining this tool is for searching within already-fetched text, not for a broader Q&A flow.

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?

It gives an explicit when-to-use: 'Use when the record is too big to cram into the prompt.' It also pairs directly with ask_pipeworx_grounded, telling the agent exactly how to combine it with a sibling tool: '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.