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

Annotations already indicate read-only, open-world, idempotent, non-destructive. The description adds valuable behavioral details: truncation at 200K chars with a flag, use of BGE-base-en embeddings and cosine similarity over 500-char overlapping windows, and that returns include character offsets and 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 well-structured and front-loaded with the core action, then usage guidance, then technical details. Every sentence earns its place: it covers what, when, how, and edge cases (truncation) without fluff. It is dense but appropriately sized for the information conveyed.

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?

No output schema exists, so the description must explain return values, and it does: 'top-N passages with character offsets and similarity scores'. It also addresses limits (max 200K chars, truncation flag) which is critical for an agent to set expectations. For a search tool with no output schema, this is 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 coverage is 100%, so baseline is 3. The description adds meaningful context beyond the schema: concrete examples of valid text inputs (SEC 10-K body, article, long tool result) and query examples (e.g., 'supply-chain risk', 'drug interactions'), plus clarifies that limit controls top-N passages. This enhances understanding of how the parameters should be used.

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 a specific verb and resource: 'Semantic search INSIDE a fetched record' with text and query inputs producing top-N passages with offsets and scores. It distinguishes itself from siblings like ask_pipeworx_grounded by focusing on searching within already-fetched text rather than grounding over the whole document.

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 when to use: 'Use when the record is too big to cram into the prompt' and explains the benefit of saving context. It also names a companion tool (ask_pipeworx_grounded) and suggests a workflow, providing clear guidance on when this tool fits vs. alternatives.

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