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reqtrace-mcp

reqtrace-mcp

by b4ked
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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get_requirement

Read-only

Retrieve a requirement's implementing code, linked tests, latest results, coverage, review state, and open issue count by req_id for traceability and impact analysis.

Instructions

One requirement with its implementing code, linked tests, latest results, coverage, review state and number of open issues.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "req_id": "<req_id>"
    },
    "name": "get_requirement"
  }
}

Input Schema

NameRequiredDescriptionDefault
req_idYes

Output Schema

NameRequiredDescriptionDefault
reviewNoLatest review decision, if current
statusYes
coverageNo
open_issuesNo
requirementYes
verified_byYes
test_resultsYesnodeid -> outcome, latest run
implemented_byYes
unexercised_codeNoImplementing items no passing linked test executes (when others are)
tests_exercising_codeNoLinked tests that executed implementing code

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.2/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds what the response aggregates (code links, tests, coverage, review state, open issue count), which is useful context, but says nothing about behavior on a missing or invalid req_id.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

One tight sentence with the resource front-loaded and no filler. It is a noun phrase rather than a sentence, which costs a little clarity but wastes nothing.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists, so the returned fields need not be re-explained, and the annotations carry the safety profile. The remaining gap is the undocumented required parameter and no note on failure behavior, which leaves a minimum-viable but incomplete definition.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% for the single required req_id parameter, and the description never mentions it, leaving its expected format or identifier source unexplained. With a real parameter at zero coverage, the description fails to compensate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The fragment 'One requirement with its implementing code, linked tests, latest results, coverage, review state and number of open issues' clearly identifies the resource (a single requirement) and the depth of detail returned. It is distinguishable from the plural sibling list_requirements, though no explicit verb is used and no sibling is named.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The singular 'One requirement' implicitly signals a per-requirement detail fetch versus list_requirements, but there is no explicit when-to-use, when-not-to-use, or named alternative. Usage must be inferred from the name and the payload list.

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

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