Build an HTTP extraction

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

Beyond the annotations, the description discloses the draft-versus-write behavior of apply, the generated artifact as universal api_call.config.flow, and the operational requirement to run and prove engine=http with writ_diagnose_http_workflow before exposing the workflow. It also adds safety constraints such as never putting fetch in evaluate_js and never sending Writ-only controls to the site. These details materially help an agent avoid destructive or invalid actions.

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 and front-loads purpose, usage conditions, workflow steps, and safety constraints. Although long for a tool definition, each sentence carries routing, behavioral, or validation guidance rather than filler. Minor density in the middle section keeps it from a perfect score.

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 complex mutation tool with rich annotations but no output schema, the description covers the full lifecycle: preconditions, draft review, apply behavior, post-apply workflow execution, and diagnostic proof. It does not need to explain return values because no output schema exists, and the annotations already cover open-world and destructive traits. Nothing critical for correct invocation is missing.

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 89%, so the input schema already carries most parameter meaning, including apply, goal, workflow, step_index, request_samples, and desired_inputs. The description adds sequencing for apply but does not meaningfully extend the semantics of the remaining parameters beyond what the schema provides. Thus baseline 3 is appropriate.

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 a specific verb and resource: create or revise an advanced browserless HTTP extraction from plain language and browser-network evidence. It clearly distinguishes this from siblings such as writ_browser_compose for ordinary login/bootstrap chains and writ_diagnose_http_workflow for post-apply validation. An agent can identify the tool's scope without opening the schema.

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 gives explicit when-to-use guidance: use AFTER a browser experiment/capture_network when simple requests or Auphan-style auth/function graphs are insufficient, and lists concrete triggers like request loops, GraphQL discovery, recursive JSON, dedupe, sorting, and cursor pagination. It also routes ordinary chains to writ_browser_compose and prescribes apply=false first, then apply=true, followed by workflow proof.

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