io.github.CloudCorpRecords/flakyguard

Registre officiel Autres

Flaky-test evidence tracker: per-test pass/fail history, flakiness rates, and a quarantine list.

Que pouvez-vous faire avec io.github.CloudCorpRecords/flakyguard ?

  • analyze_test_flakiness — Analyze test flakiness

Installation

Ajoutez ceci à la configuration MCP de votre client (Claude Desktop : claude_desktop_config.json ; Cursor : .cursor/mcp.json ; VS Code et les autres utilisent la même forme « mcpServers »).

NPM package @reneturcios/flakyguard
Claude Code
claude mcp add flakyguard -- npx -y @reneturcios/flakyguard@0.1.0 mcp
Configuration JSON (Claude Desktop, Cursor, VS Code)
{
    "mcpServers": {
        "flakyguard": {
            "command": "npx",
            "args": [
                "-y",
                "@reneturcios/flakyguard@0.1.0",
                "mcp"
            ]
        }
    }
}
OCI package ghcr.io/cloudcorprecords/flakyguard:0.1.0
Claude Code
claude mcp add flakyguard -- docker run -i --rm ghcr.io/cloudcorprecords/flakyguard:0.1.0 mcp
Configuration JSON (Claude Desktop, Cursor, VS Code)
{
    "mcpServers": {
        "flakyguard": {
            "command": "docker",
            "args": [
                "run",
                "-i",
                "--rm",
                "ghcr.io/cloudcorprecords/flakyguard:0.1.0",
                "mcp"
            ]
        }
    }
}

Documentation

Tirée du README du projet sur GitHub, actualisée chaque semaine. Les liens ouvrent GitHub.

Sommaire
  1. flakyguard
  2. CLI
  3. MCP server
  4. Docker
  5. Development
  6. License

flakyguard

"That test is flaky" is usually a feeling. flakyguard turns it into evidence. Feed it the per-test outcomes from a set of CI runs and it builds the record for every test:

  • Per-test history — how many runs contained the test, and how many times it passed, failed, or was skipped
  • Evidence runs — passes plus failures; a skip is recorded but never counts as evidence, because a test that did not run proves nothing either way
  • Classification — a test needs a minimum amount of evidence (two evidence runs by default) before it earns a verdict: stable_pass if it never failed, stable_fail if it never passed, flaky if it did both, and insufficient_data until then
  • Flakiness rate — the minority outcome's share of the evidence runs, so a test that splits its results evenly rates 0.5 and a mostly reliable one rates close to 0
  • Quarantine list — the flaky tests whose rate meets the quarantine threshold (0.5 by default), worst first, each entry carrying the pass/fail counts behind its rate
  • Verdict — quarantine_recommended when the list is non-empty, otherwise clean

Rates are rounded to four decimal places. Everything is computed locally from the runs you supply: no network, no configuration, no history kept between calls. Bad input — a run with no results, a status outside passed / failed / skipped, the same test twice in one run — is rejected with an error naming the offending path, and no partial analysis is produced.

CLI

npx @reneturcios/flakyguard analyze --input args.json
npx @reneturcios/flakyguard --version

args.json contains the full arguments object:

{
  "runs": [
    {
      "run_id": "run-101",
      "results": [
        { "test": "checkout totals", "status": "passed" },
        { "test": "search ranking", "status": "failed" }
      ]
    },
    {
      "run_id": "run-102",
      "results": [
        { "test": "checkout totals", "status": "failed" },
        { "test": "search ranking", "status": "failed" }
      ]
    }
  ],
  "min_runs": 2,
  "quarantine_threshold": 0.5
}

min_runs and quarantine_threshold are optional. The analysis is printed as JSON.

Exit codes: 0 on success, 1 on a runtime error (including an unreadable or invalid input file, or invalid input), 2 on a usage error.

MCP server

npx -y @reneturcios/flakyguard mcp

MCP client config:

{
  "mcpServers": {
    "flakyguard": {
      "command": "npx",
      "args": ["-y", "@reneturcios/flakyguard", "mcp"]
    }
  }
}
Tools
  • analyze_test_flakiness — Analyze test flakiness across CI runs.

    • runs (array, required, at least one) — runs as {run_id, results} objects, where each result is {test, status} and status is one of passed, failed, skipped; a test may not appear twice in one run
    • min_runs (integer, optional, >= 1, default 2) — minimum evidence runs before a test is classified as stable or flaky
    • quarantine_threshold (number, optional, 0 to 1, default 0.5) — flakiness-rate threshold for the quarantine list

    Returns {run_count, test_count, tests, quarantine, summary, verdict}.

Docker

docker run -i ghcr.io/cloudcorprecords/flakyguard
docker run --rm -v "$PWD:/w" ghcr.io/cloudcorprecords/flakyguard analyze --input /w/args.json

Development

npm install
npm run build   # tsc -> dist/
npm test        # tsx --test test/*.test.ts (pure local, no network)
npm run dev     # run the CLI from source

License

MIT — Copyright (c) 2026 Rene Turcios

Questions fréquentes

Qu'est-ce que io.github.CloudCorpRecords/flakyguard ?

Flaky-test evidence tracker: per-test pass/fail history, flakiness rates, and a quarantine list.

Comment installer io.github.CloudCorpRecords/flakyguard ?

Il s'exécute sur votre machine. Dans Claude Code : claude mcp add flakyguard -- npx -y @reneturcios/flakyguard@0.1.0 mcp. Pour les autres clients, collez la configuration JSON de cette page dans leurs réglages MCP.

Faut-il une clé API pour io.github.CloudCorpRecords/flakyguard ?

Son entrée au registre n'indique aucune clé ni secret obligatoire. Certaines fonctions peuvent tout de même demander un compte auprès du service auquel il se connecte.

io.github.CloudCorpRecords/flakyguard est-il open source ?

Oui. Son code est sur GitHub sous licence MIT.

Qui maintient io.github.CloudCorpRecords/flakyguard ?

Il est publié par CloudCorpRecords. AI.tn le référence sans le maintenir ni le recommander.

Issu du registre MCP officiel. Être listé n'est pas une recommandation : vérifiez le code et les permissions d'un serveur avant de lui donner accès à vos données.