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

Beyond the annotations (readOnly, idempotent, etc.), the description discloses meaningful behavioral details: the embedding model (BGE-base-en), similarity metric (cosine), chunking strategy (500-char overlapping windows), and a 200K char cap with truncation flagging. It also mentions output characteristics (offsets for verbatim quote verification). This adds substantial value beyond structured fields.

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 four sentences, each earning its place: core action, usage condition, paired workflow, and technical caveats. It is front-loaded with the most important information and contains no fluff. Despite being longer than the minimal example, it remains efficient and well-structured for the tool's complexity.

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?

The description is complete despite no output schema: it explains what the tool returns (top-N passages with offsets and similarity scores), the use case, the truncation behavior, and how it fits in the broader tool ecosystem. Given the 3-parameter schema and rich annotations, the description covers all necessary context for correct invocation and interpretation.

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 baseline is 3. The description reinforces parameter meaning with examples ('SEC 10-K body, an article, a long tool result') and explains the purpose of the text parameter, but it does not add new semantic detail beyond what the schema already provides. No extra insight about 'limit' is given.

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 previously fetched record, using specific verb and resource ('Semantic search INSIDE a fetched record'). It distinguishes from siblings by emphasizing 'inside' already-pulled text and explicitly pairs with ask_pipeworx_grounded for the grounded answering step, making its unique role evident.

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 says when to use: 'Use when the record is too big to cram into the prompt.' It also provides a paired alternative workflow with ask_pipeworx_grounded: 'fetch with the gateway, ground over the relevant passages instead of the whole document.' This constitutes both a positive usage condition and an alternative, fulfilling the when/when-not/alternatives criterion.

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