env-and-assets-bootstrap

Habilidade de configuração rigorosa para reprodução de repositório de deep learning com foco em README. Use quando a tarefa for especificamente preparar um ambiente conservador baseado em conda, suposições de caminhos de checkpoint e dataset, dicas de localização de cache e notas de configuração antes de qualquer execução em um repositório documentado por README. Não use para varredura de repositório, orquestração completa, interpretação de artigo, relatório final de execução ou configuração genérica de ambiente que não esteja vinculada a um alvo de reprodução específico.

npx skills add https://github.com/lllllllama/rigorpilot-skills --skill env-and-assets-bootstrap

env-and-assets-bootstrap

Use this as the Rigor Setup skill. The installed slug remains env-and-assets-bootstrap for compatibility.

Use the shared operating principles in ../../references/agent-operating-principles.md; this skill should keep setup planning conservative while leaving environment-specific judgment to the model.

When to apply

  • After repo intake identifies a credible reproduction target.
  • When environment creation or asset path preparation is needed before running commands.
  • When the repo depends on checkpoints, datasets, or cache directories.
  • When the user explicitly wants setup help before any run attempt.

When not to apply

  • When the repository already ships a ready-to-run environment that does not need translation.
  • When the task is only to scan and plan.
  • When the task is only to report results from commands that already ran.
  • When the request is a generic conda or package-management question outside repo reproduction.

Clear boundaries

  • This skill prepares environment and asset assumptions.
  • It does not own target selection.
  • It does not own final reporting.
  • It does not perform paper lookup except by forwarding gaps to the optional paper resolver.

Input expectations

  • target repo path
  • selected reproduction goal
  • relevant README setup steps
  • any known OS or package constraints

Output expectations

  • conservative environment setup notes
  • candidate conda commands
  • asset path plan
  • checkpoint and dataset source hints
  • unresolved dependency or asset risks

Notes

Use references/env-policy.md, references/assets-policy.md, scripts/bootstrap_env.py, scripts/plan_setup.py, and scripts/prepare_assets.py. Use scripts/bootstrap_env.sh only as a POSIX wrapper around the Python bootstrapper when a shell entrypoint is more convenient.

Mais skills de lllllllama

ai-research-explore
lllllllama
Rigor 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,...
researchdata-analysisapi
analyze-project
lllllllama
Habilidade somente leitura do Rigor Analyze / Rigor Audit para repositórios de pesquisa em deep learning. Use quando o usuário quiser ler e entender um repositório, inspecionar a estrutura do modelo e pontos de entrada de treinamento ou inferência, revisar configurações e pontos de inserção, ou sinalizar padrões de implementação suspeitos sem modificar código ou executar tarefas pesadas. Não use para execução ativa de comandos, refatoração ampla, adaptação especulativa de código ou correção automática de bugs.
developmentcode-reviewresearch
ai-research-reproduction
lllllllama
Orquestrador do modo de reprodução do RigorPilot para reprodução de repositórios de aprendizado profundo com foco em README. Use quando o usuário desejar um fluxo completo e de confiança mínima que primeiro leia o repositório, selecione o menor alvo de inferência ou avaliação documentado, coordene a ingestão, configuração, execução confiável, treinamento confiável opcional, análise opcional do repositório e resolução opcional de lacunas do artigo, aplique regras conservadoras de correção, registre evidências, suposições, desvios e pontos de decisão humana,...
researchdevelopmentdocument
explore-code
lllllllama
Rigor Improve implementation leaf skill for auditable candidate implementation in deep learning research repositories. Use when the researcher explicitly authorizes exploratory work on an isolated branch or worktree to transplant modules, adapt a backbone, add LoRA or adapter layers, replace a head, or stitch together meaningful low-risk migration ideas with rollback-aware records in `explore_outputs/`. Do not use for end-to-end exploration orchestration on top of `current_research`, trusted...
developmentresearchcode-review
minimal-run-and-audit
lllllllama
Rigor 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.
developmenttestingcode-review
explore-run
lllllllama
Rigor Improve / Rigor Explore run leaf skill for bounded exploratory evidence in deep learning research repositories. Use when the researcher explicitly authorizes exploratory runs such as small-subset validation, short-cycle guess-and-check, batch sweeps, idle-GPU search, or quick transfer-learning trials, with fair-comparison caveats and no-overclaim summaries in `explore_outputs/`. Do not use for end-to-end exploration orchestration on top of `current_research`, trusted baseline...
researchdevelopmentdata-analysis
safe-debug
lllllllama
Habilidade de Debug Rigoroso / Auditoria Rigorosa para trabalhos de pesquisa em aprendizado profundo. Use quando o usuário colar um traceback, erro de terminal, CUDA OOM, falha ao carregar checkpoint, incompatibilidade de forma, sintoma de perda NaN ou falha de treinamento e quiser um diagnóstico conservador antes de qualquer correção, com correções de debug claramente separadas das contribuições de pesquisa. Não use para refatoração ampla, adaptação especulativa, correção exploratória automática ou familiarização geral com o repositório.
developmenttestingcode-review
paper-context-resolver
lllllllama
Rigor 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...
researchdocumentdata-analysis