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

Annotations already declare readOnly, openWorld, idempotent, and non-destructive hints, and the description adds significant behavioral detail beyond that: it discloses the embedding model (BGE-base-en), cosine similarity, 500-char overlapping windows, and the 200K character cap with truncation flagging. It also explains output traits like character offsets and similarity scores.

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 front-loaded with the core purpose ('Search INSIDE a fetched record') and every subsequent sentence provides useful, non-redundant information: use case, benefits, pairing with an alternative, technical mechanism, and size limits. It is dense but not bloated, with no filler or repeating schema details.

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 there is no output schema, the description fully explains what the agent gets back: top-N passages with character offsets and similarity scores. It also covers the input cap (200K chars), truncation behavior, parameter defaults, and how to verify verbatim quotes, making it complete for an agent to use correctly.

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 description coverage is 100%, so the baseline is 3, but the description adds meaningful context beyond the schema: it clarifies that `text` should be 'the text you already pulled' with real-world examples, and it gives concrete query examples like 'supply-chain risk' and 'fiscal year 2024 revenue.' This enriches the parameter meaning without being redundant.

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 and resource: 'Semantic search INSIDE a fetched record.' It clearly distinguishes this from sibling tools by emphasizing it operates on already-fetched text (e.g., a SEC 10-K body) rather than performing broad retrieval, and it explicitly pairs with ask_pipeworx_grounded to clarify its niche.

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 provides explicit when-to-use guidance: 'Use when the record is too big to cram into the prompt.' It also explains the benefit (saves context, returns only relevant passages) and contrasts with the alternative ask_pipeworx_grounded, telling the agent to fetch with the gateway and ground over relevant passages instead of the whole document.

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