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BearQ: Run Tests in Functional Areas

bearq_run_tests_in_functional_areas
Read-onlyIdempotent

Run regression tests for specified functional areas by ID or name. Target test cases tagged with chosen areas to validate changes in those modules.

Instructions

Runs every regression test case tagged with one or more functional areas. Functional areas can be given by ID or name.

Toolset: Tasks

Parameters:

  • functionalAreas (array) required: Functional areas to target, by ID or name.

  • environment (string): Target environment name to run tests against. Omit to use the workspace default.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
environmentNoTarget environment name to run tests against. Omit to use the workspace default.
functionalAreasYesFunctional areas to target, by ID or name.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.40.0
  2. Removedv0.34.0
  3. Changed1 schema field changedv0.30.0
    • addedInput schema / properties / environment
      Added value: +{
+  "description": "Target environment name to run tests against. Omit to use the workspace default.",
+  "minLength": 1,
+  "type": "string"
+}
  4. First observedv0.27.1

TDQS

B3/5.0
Behavior2/5

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

Annotations already cover read-only/idempotent/destructive safety, so the description's burden is mainly behavior beyond that. It does not mention that this appears to create or run a task, return a task identifier, or require polling with sibling task tools. 'Runs every regression test case' communicates the core action but adds no execution-lifecycle context.

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

Conciseness3/5

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

The opening sentence is efficient and front-loaded. However, the parameter list duplicates the schema descriptions and the 'Toolset: Tasks' line contributes little functional value, so not every line earns its place.

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

Completeness2/5

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

No output schema and no return-value description, and no mention of the task lifecycle despite sibling get_task_status/wait_for_task/stop_task tools. An agent can invoke it with functionalAreas, but cannot know what to do with the result or how to monitor completion. With no output schema, the description should bridge that gap.

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

Parameters3/5

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

Schema coverage is 100%: both functionalAreas and environment already have descriptions in the schema. The description repeats them verbatim, adding no new meaning beyond saying that functional areas may be IDs or names, which the schema's anyOf already implies. Baseline 3 is appropriate.

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 first sentence states a specific action and scope: it 'Runs every regression test case tagged with one or more functional areas.' This clearly identifies the resource and distinguishes it from broader runners like bearq_run_regression_tests, though it does not explicitly name siblings or say what it is not.

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?

Usage context is implied by scope: choose this tool when regression tests need to be filtered by functional areas. There is no explicit when-to-use/when-not-to-use guidance or comparison with bearq_run_regression_tests and bearq_run_test_cases, leaving some routing to inference.

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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