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

The description discloses several behavioral details beyond what annotations provide: it uses BGE-base-en embeddings with cosine similarity over 500-char overlapping windows, has a 200K character limit with truncation and flagging for longer inputs, and returns character offsets and similarity scores. The read-only, idempotent nature is implied by the search operation and aligns with the annotations. There is no contradiction.

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 three sentences, each earning its place: the first states the core function, the second provides usage guidance, and the third gives technical implementation details. It is front-loaded with the most important information, uses intentional formatting (CAPS for 'INSIDE') to emphasize key constraints, and contains no filler or redundant content.

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?

Despite lacking an output schema, the description covers the essential return information (passages with offsets and similarity scores), the operational constraints (character cap, truncation), and the integration with a sibling tool. The tool is a straightforward search operation, and the description fully equips an agent to invoke it correctly and understand its output.

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?

The input schema already provides 100% coverage for all three parameters (text, limit, query) with clear descriptions, including examples for query. The description adds minor context (e.g., 'Pass the text you already pulled' for text, 'top-N passages' for limit) but does not substantially enhance parameter understanding beyond the schema. Per the rubric, a baseline of 3 is appropriate when schema coverage is high and the description adds marginal value.

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 opens with a specific verb and resource: 'Semantic search INSIDE a fetched record.' It clearly distinguishes this from sibling tools by emphasizing that it operates on already-fetched text, provides concrete examples (SEC 10-K, article, long tool result), and explicitly describes the return value (top-N passages with character offsets and similarity scores). This goes far beyond the tool name and title, fully clarifying what the tool does.

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 gives explicit when-to-use guidance: 'Use when the record is too big to cram into the prompt' and explains the benefit (saves context, returns only relevant passages, provides offsets for verifying quotes). It also names a complementary tool (ask_pipeworx_grounded) and describes the workflow (fetch with the gateway, ground over relevant passages). This is clear, actionable guidance on when to use this tool versus alternatives.

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