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

Given annotations already declare readOnlyHint=true and destructiveHint=false, the description adds valuable behavioral context: it returns character offsets and similarity scores, uses BGE-base-en embeddings with cosine similarity over 500-char windows, and has a 200K char cap with truncation flagging. These details go beyond the annotations to describe the tool's internal mechanics and edge-case behavior.

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 packed with information in just three sentences: purpose, usage guidance, and technical specifics. It is front-loaded with the core function, avoids fluff, and every sentence earns its place. The structure flows logically from what to when to how.

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?

With no output schema, the description adequately hints at the return format ('top-N passages with character offsets and similarity scores'). It covers the input parameter constraints (200K cap), edge cases (truncation flag), and differentiates from siblings. For a tool of this complexity, the description is complete and self-contained.

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. The description reinforces the text cap and provides example queries, but it does not add significant new meaning beyond what the schema already states for each parameter. The added context about 'text you already pulled' and 'natural-language query' is present in the schema too, so no extra compensation needed.

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,' clearly distinguishing this from sibling tools like ask_pipeworx which search external sources. It also specifies the output (top-N passages, character offsets, similarity scores) and usage context (large records too big for the prompt), leaving no ambiguity about what this 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 explicitly states when to use it: 'Use when the record is too big to cram into the prompt,' and pairs it with ask_pipeworx_grounded, explaining the intended workflow: 'fetch with the gateway, ground over the relevant passages instead of the whole document.' This gives clear guidance on when it is appropriate and how it relates to an alternative.

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