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

Beyond the annotations (readOnly, openWorld, idempotent), the description discloses concrete behavior: returns top-N passages with character offsets and similarity scores, uses BGE-base-en embeddings with cosine over 500-char overlapping windows, and truncates inputs above 200K chars with a flag. This gives the agent an accurate mental model of how the tool behaves.

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 every sentence earns its place: purpose, return format, use case, sibling pairing, and algorithm details. It is front-loaded with the core function, and the length is justified given the complexity of the tool. No redundancy or filler.

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?

Without an output schema, the description explains the return shape (top-N passages, offsets, scores) and the truncation behavior. It covers enough for an agent to select and invoke the tool confidently, including a realistic example of query phrasing. No critical gaps remain.

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%, with each parameter already described clearly. The description adds no new parameter-specific semantics; it only mentions the 200K cap for text (already in schema) and doesn't elaborate on limit beyond the schema's 'Max passages to return.' Baseline 3 is appropriate because the schema carries the full burden.

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 itself from siblings by explaining that it searches within already-fetched text rather than over the whole document, and it explicitly names a sibling (ask_pipeworx_grounded) to show how they differ.

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 an explicit use case: 'Use when the record is too big to cram into the prompt.' It also provides a pairing strategy with ask_pipeworx_grounded, telling the agent when and how to combine tools. This is direct, actionable guidance with no ambiguity.

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