Run research repositories from their README, with bounded execution and auditable evidence. RigorPilot adds section-level results without rewriting the original README. Trusted reproduction is the default; candidate exploration requires explicit authorization.
$ npx -y skills add lllllllama/rigorpilot-skills --agent claude-code
Repo: lllllllama/ai-paper-reproduction-skill
What's inside
Run research repositories from their README, with bounded execution and auditable evidence. RigorPilot adds section-level results without rewriting the original README. Trusted reproduction is the default; candidate exploration requires explicit authorization.
Original commands, prose, badges, images, videos and HTML stay in the source file. RigorPilot splits that file into sections and inserts one evidence-linked card per section. Removing its insertion blocks restores the retained original README byte for byte.
Each card below opens a full annotated README beside the original README in a retained repository checkout. Supporting repository files are kept so relative links and media retain their original context.
🟢 selected checks passed · 🔵 not executed · ⚪ read only · 🟡 partial · 🔴 blocked · 🟣 decision needed. Green does not automatically mean paper-result reproduction; blue is not an execution failure.
All four cases and upstream links · Recorded suite · Case definitions · Methodology
These are historical, commit-pinned deterministic runs: 4/4 case protocols
passed in 251.0 s, with a peak workspace of 98.67 MiB and 0 model API calls.
The zero-API count applies only to that suite. Selection-only and partial cases
are not completed evaluations, converged training or reproduced paper scores.
New: installed-skill micrograd trial, with before/after command reports, a retained failed attempt and independent checks—not a model-quality comparison.
Current acceptance: explicit named-skill and fresh-client natural-language AUTO both pass end to end; earlier failures remain retained and A/B/model uplift remain unrun. Compact status · real-client evidence
The installer needs Node.js/npm. Tested with skills@1.5.26 and Node 22.20.0;
that installer requires Node ≥22.20.0. If you see EBADENGINE, check the requested version.
Install the self-contained reproduction skill:
npx skills add lllllllama/RigorPilot-Skills --skill ai-research-reproduction
Install all skills for the companion research entrypoints:
npx skills add lllllllama/RigorPilot-Skills --all
These commands use the current GitHub repository name.
Open the target repository in a Skills-capable agent, then ask:
Use ai-research-reproduction: run the smallest README-documented evaluation, preserve the source and write evidence to repro_outputs/, plus an annotated copy beside the original README. Ask before large downloads or long training.
The main skill works alone; choose all skills for companion and leaf entrypoints. Your existing agent loads the skill. The standalone model runner is optional. Client compatibility
Recommended first run:
| Step | What it does | What it does not do |
|---|---|---|
| Plan | Lists README-backed cmd-XX candidates, selects the smallest trusted target, and returns a selection fingerprint | No target execution, installs, downloads, source edits or evidence writes |
| Run | Executes a reviewed command-id bound to that plan fingerprint and writes evidence under the target repo by default | Setup/download commands cannot be selected; a changed plan fails before target execution |
| Verify | Rechecks the retained evidence, README round trip, runtime state and current source snapshot | Does not rerun the target command |
Start with the RIGORPILOT_README.md reported in source_adjacent_readme.path,
then follow its command and log links. If a conflicting file blocks the extra
copy, that file stays intact; inspect repro_outputs/SUMMARY.md for the outcome
and next action.
README → documented target → reviewed setup → bounded execution → verification → evidence.
This is local execution, not an OS sandbox. Approved commands can access the host and network; use trusted repositories. Resource admission and between-action budget checks are not hard OS quotas or subscription-balance monitoring.
The optional model loop currently supports Anthropic Messages and reviewed command IDs, not unrestricted source repair. This standalone runner has no successful live-model acceptance recorded yet: three provider attempts returned HTTP 502. Other model profiles are metadata, not proof of working transports or equivalent model performance. Runner and recovery contract · Implementation evidence and limits
| Task | Skill |
|---|---|
| Reproduce from README commands | ai-research-reproduction |
| Read-only repository analysis | analyze-project |
| Prepare environment, data and weights | env-and-assets-bootstrap |
| Run documented inference or evaluation | minimal-run-and-audit |
| Start or verify training conservatively | run-train |
| Diagnose before proposing a patch | safe-debug |
| Coordinate authorized candidate exploration | ai-research-explore |
| Implement a candidate change on an isolated branch | explore-code |
| Execute a bounded candidate experiment | explore-run |
Two helpers support orchestration: repo-intake-and-plan and paper-context-resolver.
Exploration requires a durable current_research anchor and a frozen comparison
contract. Candidate results never become trusted baseline results by declaration.
Routing · Research loop ·
Campaign inputs
| Artifact | What to inspect |
|---|---|
repro_outputs/ANNOTATED_README.md | Original README with inserted section verdicts |
SUMMARY.md, COMMANDS.md, LOG.md, status.json | Outcome, exact commands, reviewed selection provenance, stable error.code, observations and machine-readable status |
invocation.json, evidence_manifest.json | Invocation/source-integrity summary plus retained file sizes and SHA-256 hashes for local consistency checks |
PATCHES.md, SCIENTIFIC_CHANGELOG.md, COMPARABILITY_REPORT.md | Changes, scientific meaning and comparison boundaries |
_runtime/<run_id>/ | Process state, events, resource samples and stdout/stderr |
.repro_job/ | Optional short-call supervisor: frozen request, reusable receipt, phase logs and completion-time verification |
Showing a partial view of a very large repo.
View @lllllllama’s profileRun research repositories from their README, with bounded execution and auditable evidence. RigorPilot adds section-level results without rewriting the original README. Trusted reproduction is the default; candidate exploration requires explicit authorization.
@lllllllamaFAQ
lllllllama-ai-paper-reproduction-skill is a Claude Code plugin with 11 hand-picked skills for research work, indexed on Flowy. Install it with the command on its page. It includes ai-research-explore, ai-research-reproduction, analyze-project. Its skills do not fire on their own yet. Request auto-invocation to have Flowy route them as you prompt. Free and open source.
Is this plugin yours?
Claim it with GitHubSubmit a pluginPromote it