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

Beyond the readOnlyHint/idempotentHint annotations, the description discloses the exact output format (passages with offsets and similarity scores), the embedding model (BGE-base-en), window size (500-char overlapping), and the 200K char truncation behavior with flagging. This is substantial behavioral detail that aids the agent in interpreting results.

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?

Every sentence earns its place: definition, use case, tool pairing, and technical constraints. It's front-loaded with the core action and never wastes words.

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 a rich 3-param schema and no output schema, this description fully explains the return format, technical approach, and constraints (truncation). It even situates the tool in a workflow with ask_pipeworx_grounded, making it self-contained for a capable agent.

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 schema already has 100% parameter coverage, so the baseline is 3. The description adds value by giving concrete examples for text (SEC 10-K body, article) and query ('supply-chain risk'), and it reinforces the 200K cap, which helps the agent form better inputs. This elevates it to 4.

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,' naming the verb, resource, and scope. It distinguishes itself from sibling tools like ask_pipeworx by emphasizing the fetched-record context and the 'top-N passages with character offsets' return.

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?

It explicitly states when to use: 'Use when the record is too big to cram into the prompt.' It also names a paired tool, ask_pipeworx_grounded, and explains the workflow of fetching with the gateway and grounding over relevant passages. This provides clear context and an alternative path.

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