Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add lllllllama/RigorPilot-Skills --skill ai-research-reproductiongit clone --depth 1 https://github.com/lllllllama/RigorPilot-SkillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/lllllllama/rigorpilot-skills/ai-research-reproduction)<a href="https://agentmods.dev/skills/lllllllama/rigorpilot-skills/ai-research-reproduction"><img src="https://agentmods.dev/badge/skills/lllllllama/rigorpilot-skills/ai-research-reproduction/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/lllllllama/rigorpilot-skills/ai-research-reproduction"><img src="https://agentmods.dev/badge/skills/lllllllama/rigorpilot-skills/ai-research-reproduction.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Rogue Agent · line 71 Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00136 | $0.01554 |
| Opus 5 | $0.00068 | $0.00777 |
| Sonnet 5 | $0.00027 | $0.00311 |
| Haiku 4.5 | $0.00014 | $0.00155 |
Grade A, and why
ai-research-reproduction scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
1 near-identical copy found in the catalogue:
- ai-research-reproduction — 97% identical, 2 lines differ
How it starts
The opening of the file, as written. The whole thing — 131 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ai-research-reproduction
Purpose
Guide README-first deep learning reproduction toward a minimal trustworthy run
with auditable evidence. Reproduction is not "make it run by changing
anything"; faithfully read the README, environment, weights, datasets, and
documented commands, then record results and deviations. Start with
references/agent-operating-principles.md; load
references/research-rigor-principles.md and
references/deep-learning-experiment-principles.md when scientific meaning or
experiment details are at stake.
The deterministic entrypoint is scripts/orchestrate_repro.py. It includes a
self-contained _bundled/ runtime, so this skill works when installed alone;
separately installed companion skills remain optional reusable entrypoints.
Executed commands persist lifecycle state, append-only events, and full streamed
stdout/stderr under repro_outputs/_runtime/<run_id>/. A CANCEL file in the
active run directory requests process-tree cancellation.
For recovery, queues or model gates, read references/runtime-and-model-adapter.md; for the optional model/tool loop, read references/agent-runner.md and use scripts/run_agent.py.
Fit
Use this skill when all are true:
- The target is an AI code repository with a README, scripts, configs, or documented commands.
- The request spans multiple trusted phases such as intake, setup, execution, training verification, analysis, paper-gap resolution, and reporting.
- The desired result is a small reproducible target, not broad experimentation.
Do not use this skill for paper summaries, generic environment setup, isolated repo scanning, standalone command execution, open-ended research design, or explicit candidate-only exploration.
Trusted Target Selection
Choose the smallest target that can honestly demonstrate repository-grounded reproduction:
- documented inference
- documented evaluation
- documented training startup or partial verification
- full training only after explicit user confirmation
What ships with it
44 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- _bundled/MANIFEST.json 5.3 KB
- _bundled/shared/scripts/agent_provider.py 4.4 KB runs code
- _bundled/shared/scripts/command_utils.py 3.0 KB runs code
- _bundled/shared/scripts/lessons_store.py 8.4 KB runs code
- _bundled/shared/scripts/model_adapter.py 6.3 KB runs code
- _bundled/shared/scripts/resource_monitor.py 8.0 KB runs code
- _bundled/shared/scripts/runtime_runner.py 27 KB runs code
- _bundled/shared/scripts/task_queue.py 30 KB runs code
- _bundled/shared/scripts/write_explore_bundle.py 33 KB runs code
- _bundled/shared/scripts/write_run_bundle.py 30 KB runs code
- _bundled/skills/analyze-project/scripts/analyze_project.py 25 KB runs code
- _bundled/skills/env-and-assets-bootstrap/scripts/plan_setup.py 4.7 KB runs code
- _bundled/skills/env-and-assets-bootstrap/scripts/prepare_assets.py 4.2 KB runs code
- _bundled/skills/minimal-run-and-audit/scripts/write_outputs.py 1.1 KB runs code
- _bundled/skills/repo-intake-and-plan/scripts/extract_commands.py 13 KB runs code
- _bundled/skills/repo-intake-and-plan/scripts/scan_repo.py 2.9 KB runs code
- _bundled/skills/run-train/scripts/run_training.py 19 KB runs code
- _bundled/skills/run-train/scripts/write_outputs.py 1.1 KB runs code
- agents/openai.yaml 389 B
- assets/COMMANDS.template.md 348 B
- assets/LOG.template.md 669 B
- assets/model_profile.template.json 183 B
- assets/PATCHES.template.md 525 B
- assets/readme_annotations.template.json 1.1 KB
- assets/status.template.json 1.1 KB
- assets/SUMMARY.template.md 621 B
- references/agent-operating-principles.md 2.7 KB
- references/agent-runner.md 10 KB
- references/architecture.md 1.3 KB
- references/continuous-learning-policy.md 3.7 KB
- references/deep-learning-experiment-principles.md 2.0 KB
- references/explore-variant-spec.md 4.1 KB
- references/language-policy.md 794 B
- references/output-spec.md 7.2 KB
- references/patch-policy.md 1.6 KB
- references/readme-annotation-policy.md 4.3 KB
- references/research-pitfall-checklist.md 1.6 KB
- references/research-rigor-principles.md 3.7 KB
- references/research-safety-principles.md 1.9 KB
- references/research-thinking-loop.md 4.1 KB
- references/runtime-and-model-adapter.md 5.3 KB
- scripts/annotate_readme.py 36 KB runs code
- scripts/orchestrate_repro.py 63 KB runs code
- scripts/run_agent.py 38 KB runs code
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 5d ago Changed c45e2f58572e
- 6d ago Changed 7cc128f04cc0
- 7d ago Changed e7e737bb9713
- 13d ago First seen · 131 lines · 136 tokens per session scan A 2dd32f685ef0
ai-research-reproduction is a skill published in the GitHub repository lllllllama/RigorPilot-Skills (487 stars, last pushed 5d ago), licensed MIT. It adds 136 tokens to every session and 1,554 once invoked, about $0.0007 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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