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

Beyond the read-only/idempotent annotations, the description reveals concrete behavior: every passage carries a character offset for verification, embeddings use BGE-base-en with cosine over 500-char overlapping windows, and inputs over 200K chars are truncated and flagged. These are valuable operational details that an agent cannot infer from annotations alone.

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 information-dense but not verbose. Each sentence contributes: core purpose, usage trigger, pairing guidance, and technical internals. It is slightly long but well organized, making it easy to scan. It could be tightened by removing the embedding model details, but they are relevant for understanding truncation and scoring behavior.

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 there is no output schema, the description adequately explains what the agent receives: 'top-N passages with character offsets and similarity scores.' It also covers edge behavior (truncation flag) and integration with a sibling tool. For a search-within-record tool with 3 parameters and no output schema, this is a complete picture.

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%, so the baseline is 3. The description adds value by giving concrete examples for the 'query' parameter (e.g., 'supply-chain risk', 'fiscal year 2024 revenue') and explaining the relationship between 'text' and 'query' (pass the already-pulled text and ask a natural-language query). It also clarifies the output concept of top-N passages, though it doesn't describe the 'limit' parameter beyond the schema's explicit documentation.

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 begins with a clear, specific action: 'Semantic search INSIDE a fetched record.' It distinguishes this tool from broader search/retrieval tools by scoping it to already-fetched text, and the 'pairs with ask_pipeworx_grounded' note further differentiates its role. The verb+resource combination is 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 when-to-use guidance is provided: 'Use when the record is too big to cram into the prompt — search_within saves context, returns only the passages that matter.' It also names an alternative/complementary tool (ask_pipeworx_grounded) and explains how to combine them. This clearly directs the agent to the right context for selecting this tool.

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