lllllllama
11 Skills with substantive, source-verified documentation. Open a card to read the original instructions and review package and installation details.
lllllllamapaper-context-resolver
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 replacing R
- Total installs
- 483.8K
- GitHub stars
- 486
- Updated
- Sep 23
lllllllamarepo-intake-and-plan
Rigor 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.
- Total installs
- 483K
- GitHub stars
- 486
- Updated
- Sep 23
lllllllamaminimal-run-and-audit
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 reprooutputs/ 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.
- Total installs
- 482.9K
- GitHub stars
- 486
- Updated
- Sep 23
lllllllamaenv-and-assets-bootstrap
Rigor 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.
- Total installs
- 482.8K
- GitHub stars
- 486
- Updated
- Sep 23
lllllllamaai-research-explore
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 currentresearch with auditable repo understanding, idea gating, fair comparison, and governed experiments written to exploreoutputs/. Do not use for README-first trusted reproduction, open-ended direction finding, narrow code-on
- Total installs
- 344.2K
- GitHub stars
- 486
- Updated
- Sep 23
lllllllamaanalyze-project
Rigor 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.
- Total installs
- 344K
- GitHub stars
- 486
- Updated
- Sep 23
lllllllamaai-research-reproduction
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 w
- Total installs
- 343.8K
- GitHub stars
- 486
- Updated
- Sep 23
lllllllamasafe-debug
Rigor Debug / Rigor Audit skill for deep learning research work. Use when the user pastes a traceback, terminal error, CUDA OOM, checkpoint load failure, shape mismatch, NaN loss symptom, or training failure and wants conservative diagnosis before any patching, with debug fixes clearly separated from research contributions. Do not use for broad refactoring, speculative adaptation, automatic exploratory patching, or general repository familiarization.
- Total installs
- 343.5K
- GitHub stars
- 486
- Updated
- Sep 23
lllllllamaexplore-code
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 exploreoutputs/. Do not use for end-to-end exploration orchestration on top of currentresearch, trusted baseline
- Total installs
- 343.4K
- GitHub stars
- 486
- Updated
- Sep 23
lllllllamarun-train
Rigor Train skill for deep learning research repositories. Use when a documented or selected training command should be run conservatively for startup verification, short-run verification, full kickoff, or resume, with command, config, seed, log, checkpoint, status, and metric evidence written to standardized trainoutputs/. Do not use for environment setup, exploratory sweeps, speculative idea implementation, or end-to-end orchestration.
- Total installs
- 343.2K
- GitHub stars
- 486
- Updated
- Sep 23
lllllllamaexplore-run
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 exploreoutputs/. Do not use for end-to-end exploration orchestration on top of currentresearch, trusted baseline execution, conserva
- Total installs
- 343.2K
- GitHub stars
- 486
- Updated
- Sep 23