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

Beyond the readOnly/idempotent annotations, the description discloses specific mechanics: 'BGE-base-en embeddings + cosine over 500-char overlapping windows; cap is 200K chars (longer inputs are truncated and flagged).' It also promises output structure (offsets and similarity scores), giving the agent accurate expectations for behavior and result format.

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 dense but well-organized: it states the core function first, then the output, use case, complementary tool, and technical constraints in sequence. No sentence is filler; each adds actionable information for an agent deciding whether and how to call the tool.

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?

For a tool with no output schema, the description fully specifies the return contract: 'get back the top-N passages with character offsets and similarity scores.' It also covers the input cap, truncation flag, and the recommended workflow with ask_pipeworx_grounded, so the agent has all necessary context to select and invoke the tool 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?

The input schema already covers 100% of parameter descriptions, so the baseline is 3. The description adds operational context—'the text you already pulled' and 'top-N passages'—which reinforces how text, query, and limit are used together. It also mentions the 200K truncation flag, which is behavior that reflects on the text parameter.

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 'Semantic search INSIDE a fetched record,' which names the exact verb, resource, and scope. It differentiates from siblings like ask_pipeworx_grounded by explicitly framing search_within as operating on already-fetched text, and it lists concrete outputs (passages, offsets, similarity scores).

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 includes an explicit 'Use when' clause: 'when the record is too big to cram into the prompt.' It also names a companion tool and explains how to combine them: 'Pairs with ask_pipeworx_grounded: fetch with the gateway, ground over the relevant passages instead of the whole document.' This provides clear when-to-use and how-it-fits guidance.

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