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

Annotations already mark the tool as read-only, idempotent, and non-destructive. The description goes beyond by detailing truncation at 200K chars, embedding model (BGE-base-en), overlapping windows (500 chars), and that truncated inputs are flagged. No contradictions 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?

Front-loaded with main purpose, each sentence adds value (purpose, when-to-use, technical details). Slightly verbose with model and window details, but overall 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?

No output schema, but description explains that return includes passages with character offsets and similarity scores, which is sufficient. Covers input constraints (200K char limit, truncation), enabling correct agent usage.

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% and description adds meaning: explains truncation behavior for 'text', provides example queries for 'query', and notes default for 'limit' (5). While schema already documents basics, the description enriches understanding with practical usage details.

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 verb ('semantic search'), resource ('inside a fetched record'), and distinguishes from siblings by specifying that it searches within already-pulled text. The description explicitly contrasts with other tools like 'ask_pipeworx_grounded', making the use case 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?

Provides explicit guidance: use when a record is too large for the prompt, saves context, returns relevant passages with offsets for verification. Also describes how it pairs with 'ask_pipeworx_grounded', giving clear when-to and when-not-to context.

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