Rigorously

Automated research quality assurance.

Rigorously catches the mistakes that slip past manual review — fabricated citations, overclaimed results, irreproducible numbers, and statistical misinterpretations. One command. Eight checks.

Tested on: Python CLI, Claude Code, pre-commit hooks · Compatible with: 16+ AI coding platforms via the Agent Skills standard and MCP

The Problem

Citation errors appear in 25% of published papers. "Statistically significant" gets misused in half of biomedical literature. Overclaimed results are the #1 reason reviewers reject computational papers. Manual review catches some of these. Rigorously catches the rest.

pip install rigorously
rigorously check paper.tex

Run It Before You Submit

Journals like PLOS, Nature, and Science desk-reject up to 40% of submissions for preventable issues: citation errors, missing sections, inconsistent numbers. Each round-trip costs weeks. Rigorously catches these in 3 seconds before a reviewer sees your paper. No account. No cloud. No data leaves your machine.

What It Catches

Check	What It Does
Citation Verification	Verifies every bib entry against CrossRef — DOIs, titles, authors, journals
Overclaim Detection	Flags "proven," "validated," "novel," "impossible" — suggests precise alternatives
Number Consistency	Cross-checks every number across abstract, body, tables, and captions
Parameter Auditing	Verifies code parameters match paper claims and docstrings
Statistical Auditing	Checks p-values, sample sizes, test appropriateness, power analysis
Evidence Mapping	Traces every claim to supporting code, data, or citation
Reproducibility	Runs referenced scripts, compares output to paper numbers
Adversarial Review	Compiles findings into a simulated hostile peer review

Sample Output

$ rigorously check paper.tex

  Overclaim Detection: 4 findings
  ┌──────────┬────────┬───────────────────────┬─────────────────────────────┐
  │ CRITICAL │ L.56   │ validated             │ Use "consistent with" unless│
  │          │        │                       │ quantitatively compared     │
  │ CRITICAL │ L.216  │ proof_language         │ Models provide evidence,    │
  │          │        │                       │ not proof                   │
  │ WARNING  │ L.502  │ confirms_demonstrates │ Models predict or suggest;  │
  │          │        │                       │ they do not confirm         │
  │ INFO     │ L.89   │ significant_ambiguous  │ Specify p < X or use       │
  │          │        │                       │ "substantial"               │
  └──────────┴────────┴───────────────────────┴─────────────────────────────┘

  Citation Verification: 12 entries checked
    ✓ Best2010 — DOI resolves, metadata matches
    ✓ Karin2020 — DOI resolves, metadata matches
    ✗ LePoul2000 — Author mismatch: bib has "Bhatt" x4, PubMed has "Hanoun"

  VERDICT: 4 critical issues. Fix before submission.

Platform Support

Platform	Command
CLI	pip install rigorously
Claude Code	claude plugin install rigorously
Cursor	cursor plugin install rigorously
Codex CLI	codex plugin install rigorously
Kiro	Add power → rigorously
Windsurf	Add skill → rigorously
Continue.dev	Add MCP → rigorously
Aider	aider --read rigorously
Any MCP client	"command": "rigorously", "args": ["serve"]
Pre-commit	rigorously install-hook
CI/CD	rigorously check paper.tex

How It Works

paper.tex + refs.bib
       │
       ▼
  ┌─────────┐    ┌──────────┐    ┌──────────┐
  │  Parse   │───▶│ Extract  │───▶│ Verify   │
  │ LaTeX/MD │    │ claims,  │    │ against  │
  │          │    │ numbers, │    │ CrossRef,│
  │          │    │ citations│    │ code,    │
  │          │    │          │    │ PubMed   │
  └─────────┘    └──────────┘    └──────────┘
                                       │
                                       ▼
                                ┌──────────┐
                                │  Report  │
                                │ GO/NO-GO │
                                └──────────┘

MCP Server

For AI agent integration:

pip install "rigorously[mcp]"
python -m rigorous.mcp_server

Tools: check_paper, verify_citation, check_overclaims, audit_parameters, generate_report

Pre-commit Hook

rigorously install-hook
# Blocks commits with critical integrity issues in paper files

vs. Alternatives

Feature	Rigorously	RefChecker	ACL pubcheck
Citation verification	✓	✓	✗
Overclaim detection	✓	✗	✗
Number consistency	✓	✗	✗
Parameter auditing	✓	✗	✗
Statistical auditing	✓	✗	✗
Evidence mapping	✓	✗	✗
Reproducibility	✓	✗	✗
Adversarial review	✓	✗	✗
AI agent integration	✓ (16+ platforms)	✗	✗
Pre-commit hook	✓	✗	✗
Format checking	✗	✗	✓

Origin

Built to catch real mistakes in real research. During development of a computational neuroscience paper, Rigorously caught 5 fabricated bibliography entries, 4 overclaimed results, and a parameter bug that was disguised as a scientific discovery — all before submission. It now runs on every commit.

Contributing

See CONTRIBUTING.md.

Citation

If you use Rigorously in your research workflow:

@software{rigorously,
  author = {Miraj, Mansib},
  title = {Rigorously: Automated Research Quality Assurance},
  url = {https://github.com/XenResearch/rigorously},
  year = {2026}
}

License

MIT