extract_scenarios

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

No annotations are provided, so the description must carry the full burden. It discloses that scenarios are classified via keyword heuristics and split into Given/When/Then where possible, and it details the output fields. However, it does not cover side effects, error behavior, or prerequisites beyond the input format. This partial 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 and well-structured: it opens with the purpose, then explains the method, output format, and a pairing suggestion. Every sentence adds value without redundancy or excessive length.

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 the tool's moderate complexity and lack of output schema, the description provides a complete picture of inputs, outputs, and workflow position. It defines the scenario fields and suggests a next step. Minor missing details (e.g., handling of unscoped input) are acceptable for a processing tool.

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 has 0% description coverage, so the description compensates by explaining that the parameter is the acceptance_criteria array from parse_spec. It does not detail the array's structure beyond mentioning required text field, but it provides contextual linkage to another tool. This adds moderate value.

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 converts parsed acceptance criteria into testable scenarios, specifying the input source (from parse_spec) and output structure (Given/When/Then with classification). This distinguishes it from siblings like parse_spec (which likely produces the input) and generate_test_plan (which produces a markdown handoff).

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 instructs to pass the acceptance_criteria array from parse_spec, providing a clear before/after context. It also suggests pairing with generate_test_plan, reinforcing a workflow. Although it does not list exclusions or alternatives, the guidance is sufficient for correct usage.

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