RigorGraph

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Turn AI research into auditable claim-evidence graphs.

RigorGraph is a local-first CLI, offline report, GitHub Action, and skill pack for recording what a research claim says, what evidence supports it, who independently checked it, and what remains open. It preserves the difference between proof, literature support, numerical evidence, benchmark evidence, and uncertainty.

RigorGraph checks workflow integrity and traceability. VERIFIED means accepted by the recorded workflow; it does not mean absolute truth, formal certification, peer review, or expert consensus.

1.0 release candidate: RigorGraph 1.0 keeps its public interfaces additive and ships only when deterministic quality gates pass. External use is evidence, not permission to weaken or block those gates. Do not include private research data in public feedback.

Quick start

RigorGraph requires Python 3.11 or newer and no API key. After the approved PyPI RC publish, install the release candidate with:

python -m pip install --pre "rigorgraph==1.0.0rc2"
rigorgraph demo --scenario math --open

The demo creates a project, runs a deterministic audit, and opens a self-contained report. Try the intentionally invalid promotion:

rigorgraph demo invalid-demo --scenario invalid
rigorgraph audit invalid-demo

The audit rejects the attempt to treat a finite numerical scan as a formal proof.

Start your own project

rigorgraph --lang en quickstart my-research --name "My research project" --author "Your name" --type formal --statement "Every bounded sequence has property P." --open

This creates one real DRAFT claim in the language you supplied and opens its offline report. The claim appears under Open gaps; RigorGraph does not invent evidence or promote it to VERIFIED. The project stores human-readable, version-controlled records:

my-research/
├── rigorgraph.yaml
└── .rigorgraph/
    ├── claims.jsonl
    ├── evidence.jsonl
    └── verifications.jsonl

Commands

Use --lang en, --lang zh-TW, --lang zh-CN, or --lang ja before a command. Without it, RigorGraph uses project configuration, then the operating-system locale, then English.

What the audit enforces

• IDs are unique and links resolve.
• Claim dependencies are acyclic.
• Revoked or rejected claims cannot silently support downstream claims.
• A claim author cannot be its independent verifier.
• VERIFIED requires an independent ACCEPT record.
• Formal claims need proof evidence; literature claims need an exact source locator; empirical and benchmark claims need reproducibility artifacts.
• Local evidence paths cannot escape the project and their required SHA-256 digests must match.
• An ACCEPT record is bound to the exact claim-and-evidence snapshot it reviewed.
• A verified synthesis depends only on currently verified claims.

User-authored claims, formulas, quotations, and evidence remain in their original language. The interface translates labels only.

Evidence bundles

RigorGraph 1.0 defines an additive, versioned evidence-bundle contract. An HonestCI run can emit a bundle containing result summaries, allowlisted GitHub provenance, and SHA-256 digests for the configuration and observed artifacts. Importing it copies the exact JSON into .rigorgraph/artifacts/; it never promotes or verifies a claim.

rigorgraph evidence import honest-ci-evidence.json --claim CLM-CI --path my-research

Only DRAFT and PROPOSED claims can be linked. See Evidence bundles for the schema, compatibility policy, privacy boundary, and HonestCI profile.

Agent skills and Codex plugin

The repository includes four focused Agent Skills:

• research-intake
• capture-claim
• adversarial-verify
• release-audit

It also ships a native .codex-plugin/plugin.json. The GitHub Release includes rigorgraph-codex-plugin-1.0.0-rc.2.zip; extract it, then install its isolated marketplace:

codex plugin marketplace add PATH_TO_EXTRACTED_BUNDLE
codex plugin add rigorgraph@rigorgraph-release

Start a new Codex task after installation so the four skills are discovered. See Codex plugin installation. The ZIP does not edit your personal marketplace file.

GitHub Action

steps:
  - uses: actions/checkout@v7
  - uses: actions/setup-python@v7
    with:
      python-version: "3.12"
  - uses: f0909172434/rigorgraph@v1.0.0-rc.2
    with:
      path: .
      fail-on: error

The action writes a GitHub Job Summary and uploads the offline report. It does not post PR comments by default. The moving @v1 tag is created only after the stable release passes the RC gates.

Develop from source

git clone https://github.com/f0909172434/rigorgraph.git
cd rigorgraph
python -m venv .venv
python -m pip install -e ".[dev]"
cd frontend
npm install
npm run build
cd ..
pytest
python scripts/release_check.py

See CONTRIBUTING.md for translation and verification rules, and Release policy for the solo-maintainer release criteria.

Privacy and boundaries

• Local by default; no account, telemetry, remote database, or built-in paid model API.
• The HTML report is self-contained and makes no runtime network requests.
• Deterministic gates can catch incomplete records and invalid promotion, but cannot guarantee that a human or AI proof is mathematically correct.
• Core results still need appropriate expert review.

MIT License.