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

The description reveals behavioral details beyond the annotations: BGE-base-en embeddings, cosine similarity, 500-char overlapping windows, a 200K character cap with truncation flagging, and that each passage includes character offsets for verification. These details help the agent anticipate output and edge cases, which the annotations (readOnlyHint, idempotentHint) do not cover.

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 in the first sentence, then expands with usage context and technical details. Every sentence provides useful information without redundancy, achieving a strong balance between thoroughness and conciseness.

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?

Since there is no output schema, the description compensates by clearly stating the return format (top-N passages with character offsets and similarity scores). It also covers limit scenarios (truncation with flagging), integration with a sibling tool, and the rationale for using it, making it complete for agent decision-making.

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%, so the baseline is 3. The description adds value by providing concrete examples for 'text' (SEC 10-K body, article, tool result) and for 'query' (natural-language examples like 'supply-chain risk'), which helps the agent craft effective inputs. It does not add much for 'limit' beyond 'top-N', but the schema already explains that.

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 states the tool's function with a specific verb and resource: 'Semantic search INSIDE a fetched record.' It clearly explains the input (text + query) and output (passages with offsets and similarity), and distinguishes itself from sibling tools like ask_pipeworx_grounded by operating on already-retrieved text.

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.' It also positions the tool as a complement to ask_pipeworx_grounded, providing clear context for its role in a workflow. This is direct guidance for agent selection.

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