AI导哈

数据与研究

ai-research-reproduction

lllllllama/rigo…t-skills

Rigor Reproduce compatible skill slug for README-first deep learning repository reproduction. Use when the user wants an end-to-end, minimal-trustworthy flow that reads the repository first, selects the smallest documented inference or evaluation target, coordinates intake, setup, trusted execution, optional trusted training, optional repository analysis, and optional paper-gap resolution, enforces conservative patch rules, records evidence assumptions deviations and human decision points, and writes the standardized `repro_outputs/` bundle. Do not use for paper summary, generic environment setup, isolated repo scanning, standalone command execution, silent protocol changes, score chasing, or broad research assistance outside repository-grounded reproduction.

  • 34.1万 次安装
  • 486 星标
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安装命令

npx skills add https://github.com/lllllllama/rigorpilot-skills --skill ai-research-reproduction

SKILL.md

ai-research-reproduction

Purpose

Guide README-first deep learning reproduction toward the smallest trustworthy run with auditable evidence. Preserve documented meaning; record assumptions, deviations and blockers instead of changing semantics to manufacture success. Load specialized references only for a concrete uncertainty.

Fast Path

For a routine bounded run, keep the control path short:

  1. Read the target README and only the target test/config/source needed to understand the documented command.
  2. Run scripts/orchestrate_repro.py --repo <repo> --plan-only --agent-output with any explicit user timeout bound (--timeout or --train-timeout) already supplied; review command_candidates, the selected cmd-XX, side-effect contract, selection fingerprint, and returned reviewed_run_args. With no --output-dir, later evidence goes to <repo>/repro_outputs regardless of caller cwd.
  3. Run the selected candidate, or another reviewed candidate, with --run-selected --command-id <cmd-XX> --plan-fingerprint <fingerprint> --agent-output plus requested timeout/metric/source-adjacent options. Preserve an explicit user command-timeout bound instead of silently making it stricter on a routine trusted run. --timeout limits the target command; do not wrap the whole orchestrator in an equal or shorter external timeout, because it still needs time to terminate children and write terminal evidence. A changed command set fails closed; setup/download commands are never target candidates.
  4. Run --verify-output --agent-output; inspect detailed evidence files only when verification fails or the result is partial/blocked.
  5. Deliver the bounded result and stop.

相关 Skills

paper-context-resolverlllllllama/rigo…t-skillsRigor Paper Context helper for README-first deep learning repo reproduction. Use only when the README and repository files leave a narrow reproduction-critical gap and the task is to resolve a specific paper detail such as dataset split, preprocessing, evaluation protocol, checkpoint mapping, or runtime assumption from primary paper sources while recording conflicts. Do not use for general paper summary, repo scanning, environment setup, command execution, title-only paper lookup, or replacing README guidance by default.其他48.1万repo-intake-and-planlllllllama/rigo…t-skillsRigor Intake helper for README-first deep learning repo reproduction. Use when the task is specifically to scan a repository, read the README and common project files, extract documented commands, classify inference, evaluation, and training candidates, and return the smallest trustworthy reproduction plan to the main orchestrator. Do not use for environment setup, asset download, command execution, final reporting, paper lookup, or end-to-end orchestration.智能体工作流48.1万env-and-assets-bootstraplllllllama/rigo…t-skillsRigor Setup skill for README-first deep learning repo reproduction. Use when the task is specifically to prepare a conservative conda-first environment, checkpoint and dataset path assumptions, cache location hints, and setup notes before any run on a README-documented repository. Do not use for repo scanning, full orchestration, paper interpretation, final run reporting, or generic environment setup that is not tied to a specific reproduction target.智能体工作流48万minimal-run-and-auditlllllllama/rigo…t-skillsRigor Run skill for README-first deep learning repo reproduction. Use when the task is specifically to capture or normalize evidence from the selected smoke test or documented inference or evaluation command and write standardized `repro_outputs/` files, including patch notes when repository files changed. Do not use for training execution, initial repo intake, generic environment setup, paper lookup, target selection, hidden scientific-meaning changes, or end-to-end orchestration by itself.测试与安全48万ai-research-explorelllllllama/rigo…t-skillsRigor Explore compatible skill slug for meaningful and potentially novel deep learning research candidates. Use when the researcher has chosen the task family, dataset, benchmark, evaluation method, provided SOTA references, and wants candidate-only exploration on top of `current_research` with auditable repo understanding, idea gating, fair comparison, and governed experiments written to `explore_outputs/`. Do not use for README-first trusted reproduction, open-ended direction finding, narrow code-only or run-only exploration, passive repo analysis, verified novelty claims, or implicit experimentation.数据与研究34.2万analyze-projectlllllllama/rigo…t-skillsRigor Analyze / Rigor Audit read-only skill for deep learning research repositories. Use when the user wants to read and understand a repository, inspect model structure and training or inference entrypoints, review configs and insertion points, or flag suspicious implementation patterns without modifying code or running heavy jobs. Do not use for active command execution, broad refactoring, speculative code adaptation, or automatic bug fixing.测试与安全34.2万