Parse Gherkin feature text and return each scenario with its requirement IDs, pulled from @REQ tags or scenario titles, to map features to requirements.
Parse Gherkin feature text and return each scenario with the requirement IDs it is linked to (via @REQ-001 tags or IDs in the scenario title).
| Name | Required | Description | Default |
|---|---|---|---|
| features | Yes | One or more .feature documents |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It does disclose the core extraction logic (requirement IDs found via @REQ-001 tags OR scenario title IDs), which is the key behavior. However, it does not disclose edge cases (malformed Gherkin, unmatched scenarios), the file-vs-text input distinction present in the schema, or error behavior.
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?
A single, front-loaded sentence with zero wasted words. It states the action, the input, the output, and the extraction mechanisms compactly. Every element earns its place.
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 one parameter and full schema coverage, input handling is well covered. The main gap is the unspecified output format - there is no output schema, and the description only says it 'returns each scenario' conceptually without describing the returned structure. Since no annotations exist either, an agent would not know the exact shape of the returned scenarios.
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 100% - the single 'features' parameter and its nested 'path'/'text' properties are all documented in the schema. The description adds no parameter-specific semantics beyond what the schema provides, so the baseline of 3 for high-coverage schemas applies.
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 (Parse), a specific resource (Gherkin feature text), and a clear output (scenarios with linked requirement IDs via @REQ-001 tags or title IDs). This clearly distinguishes it from siblings like parse_requirements (which parses requirement documents, not feature files) and diff_requirements/traceability_matrix (which operate on parsed artifacts, not raw Gherkin).
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 usage context is implied by the purpose: an agent can infer this tool is for extracting scenarios from Gherkin feature documents. However, there is no explicit guidance about when to use this tool versus parse_requirements (e.g., when you only need requirement specs, not scenarios) or when NOT to use it. No alternatives or exclusions are named.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.