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testit-mcp-server

testit-mcp-server

by iampopovich

rerun_test_run_results

Re-run selected autotest results in a test run to create new pending attempts and set the run back to InProgress; submit new results afterward.

Instructions

Re-run autotest results of a run: each selected result gets a new pending attempt and the run goes back to InProgress. Submit new results via submit_test_run_results; attempts are listed by get_test_result_reruns.

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": {
      "id": "<id>",
      "testResultIds": "<testResultIds>"
    },
    "name": "rerun_test_run_results"
  }
}

Input Schema

NameRequiredDescriptionDefault
idYesTest run UUID.
testResultIdsYesNon-empty.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A4.2/5.0
Behavior4/5

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

Annotations only declare the generic profile (writable, open-world, non-idempotent, non-destructive); the description adds the meaningful side effects an agent must know: new pending attempts are created and the run's state flips back to InProgress. It doesn't spell out whether existing attempts are superseded, whether prior results are invalidated, or any permission requirements.

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

Conciseness5/5

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

Two sentences, effect stated first, sibling routing second, with no filler. Every clause carries actionable information and the most decision-relevant fact (state change to InProgress) is front-loaded.

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

Completeness4/5

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

For a two-parameter mutation tool with no output schema, the definition covers the state transition, the follow-up path (submit_test_run_results) and the inspection path (get_test_result_reruns), which is sufficient to call it correctly. It leaves the return payload and any constraints on which runs are eligible unstated.

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 description coverage is 100%, with both id and testResultIds documented, so the baseline is 3. The description only echoes the schema's intent by saying 'each selected result', adding no format, ordering, or batch-size detail beyond it.

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

Purpose5/5

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

States a specific verb and resource ('Re-run autotest results of a run') plus the exact effect: each selected result gets a new pending attempt and the run transitions to InProgress. This is clearly separable from submit_test_run_results, which the description explicitly names as the way to supply new results.

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

Usage Guidelines4/5

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

Gives clear context for use (re-running selected results to generate fresh attempts) and routes the agent to two relevant siblings: submit_test_run_results for new results and get_test_result_reruns for inspecting attempts. It does not state exclusions, e.g. whether results from completed or closed runs can be re-run, so it stops short of a full when/when-not guide.

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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