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

Beyond annotations (which all indicate safe, non-destructive, idempotent behavior), the description reveals technical details: embedding model (BGE-base-en), similarity measure (cosine), windowing (500-char overlapping windows), and a hard cap (200K chars with truncation and flagging). Also mentions character offsets for quote verification. This adds significant behavioral context that annotations alone don't cover.

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?

Every sentence serves a purpose: first sentence states functionality, second provides usage context and benefit, third gives pairing advice, fourth details technical implementation and limits. Front-loaded with purpose, then usage, then technical details. No filler or redundancy.

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 no output schema, the description explains return values (top-N passages with character offsets and similarity scores). It addresses the main use case (large documents), technical constraints (200K char cap, truncation), and integration with sibling tools (ask_pipeworx_grounded). Annotations provide safety guarantees. The description is complete enough for an agent to understand when and how to use this tool.

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% (all three parameters described with basic purpose). The description adds value by clarifying that 'text' is the document to search, 'query' is a natural-language query with examples, and 'limit' controls max passages. It also explains the max char limit and truncation behavior, which is not in the schema. However, the schema already provides adequate descriptions, so the incremental value is somewhat limited.

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 uses a specific verb ('Semantic search INSIDE a fetched record') and resource (a fetched record) and immediately distinguishes from siblings by mentioning pairing with ask_pipeworx_grounded. It gives concrete examples (e.g., SEC 10-K, article, long tool result). This leaves no ambiguity about what the tool does and how it differs from other search tools.

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 states when to use ('when the record is too big to cram into the prompt') and suggests an alternative workflow ('Pairs with ask_pipeworx_grounded'). Also explains the benefit ('saves context, returns only the passages that matter'). Provides clear context for selecting this tool over alternatives.

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