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does-it-run

Does it actually run?

does-it-run executes AI agents against standard test cases and emits reproducible evidence — runs, durations, costs, diffs — the fact layer behind every compatibility page on agentrundb.com.

Website content is not written. It is run.

What it does

  1. Prepares an isolated fixture repo with a failing unit test
  2. Invokes a coding agent (headless CLI) with a standard task
  3. Verifies the outcome by running the test suite
  4. Emits the AgentRunDB standard run JSON:
{
  "sourceRunId": "claude-code-deepseek-read-repo-edit-run-test-1765432100123",
  "compatibility": {
    "agentSlug": "claude-code",
    "targetType": "model",
    "targetSlug": "deepseek"
  },
  "testCase": "read-repo-edit-run-test",
  "status": "passed",
  "duration": 72.4,
  "toolCall": true,
  "fileEdit": true,
  "tokens": 12450,
  "cost": 0.18,
  "errors": [],
  "evidence": ["log.txt"]
}

Quick start (local)

# 1. Requires: node >= 22, git, and the agent CLI installed (e.g. claude)
claude --version

# 2. Dry run — no model calls, prints the plan
npm run verify:dry -- --agent claude-code

# 3. Real run against DeepSeek
DEEPSEEK_API_KEY=sk-... npm run verify -- --agent claude-code --model deepseek

# 4. Import into a local AgentRunDB site
#    (inside the site repo: pnpm agentrundb:import <output json>)

Reports are written to data/<agent-slug>/<date>/<sourceRunId>/ with the raw agent log (log.txt), the report (report.json) and the fixture diff.

CI (GitHub Actions)

.github/workflows/verify.yml runs the matrix on schedule. Required repo secrets:

Secret Purpose
DEEPSEEK_API_KEY / KIMI_API_KEY / GLM_API_KEY / QWEN_API_KEY Model API key — resolved as <MODEL>_API_KEY (or generic API_KEY)
IMPORT_URL (optional) Site ingestion endpoint, e.g. https://agentrundb.com/api/runs/import
IMPORT_TOKEN (optional) Bearer token for the ingestion endpoint

Without IMPORT_URL the workflow only uploads the run JSON as an artifact.

Adding an agent adapter

Create agents/<slug>.js exporting:

export default {
  slug: 'my-agent',
  async checkInstalled() { /* throw if the CLI is missing */ },
  buildEnv({ model, apiKey }) { /* return env overrides */ },
  async invoke({ workdir, task, timeoutMs }) { /* run the agent headless */ },
};

Then run npm run verify -- --agent my-agent.

Test cases

Cases live in cases/ as JSON. Each case defines the task prompt, the expected outcome and the fixture it uses. Cases map 1:1 to test_cases rows on the site — keep slugs in sync.

License

MIT

About

Run AI agents against standard test cases and publish reproducible evidence. Does it actually run? — agentrundb.com

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