network_extract

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

No annotations are provided, so the description carries full burden. It describes the output structure (fields, scores, etc.) but does not detail error handling, performance, or side effects. The behavioral disclosure is adequate but not comprehensive.

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 concise with two sentences. The first sentence front-loads the main purpose, and the second provides usage guidance. No extra words or redundancy.

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 5 parameters, no output schema, and many sibling tools, the description covers the main purpose and usage context well. It includes specifics like the types parameter examples. Minor missing: handling of empty captures or invalid inputs.

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%, with each parameter having a description. The tool description adds context about when to use parameters (e.g., 'query' for ranking) but does not provide significant additional meaning beyond the schema.

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 clearly states the tool's purpose: 'Parse captured JSON/API/network responses into semantic objects with fields, scores, matched query terms, and capture/path provenance.' It uses specific verbs and resource, and distinguishes from siblings like network_stores and body by providing usage context.

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 says when to use: 'Use after navigate or activate when network_stores shows JSON/GraphQL/NDJSON captures and raw body_preview is too noisy.' This provides clear context, though it doesn't explicitly state when not to use or list alternative tools beyond body_preview.

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