ralph-loop
claudeInteractive self-referential AI loops for iterative development. Claude works on the same task repeatedly, seeing its previous work, until completion.
3 commands · hooks
Delegation and completion discipline for substantial autonomous agent work: a unit-count gate with a DELEGATION.md ledger and one fresh subagent per unit, plus acceptance gates with an approval-bound checker, Depth Tree decomposition, and an optional Stop hook so no leaf lands half-done.
Not in a marketplace yet, so it loads for one session with --plugin-dir.
Plugin emasoft-agents-discipline in Emasoft/emasoft-agents-discipline. Commands read from the repo's manifest — 1 month ago.
agents-disciplineDelegation and completion discipline for substantial autonomous work. Use when a task splits into independent units, when an agent faces a long or multi-part task, work that returned half-done, an exhaustive audit or build, parallel leaves or pipelines, or explicit triggers such as /agents-disciplin
Interactive self-referential AI loops for iterative development. Claude works on the same task repeatedly, seeing its previous work, until completion.
3 commands · hooks
tasteskill 2.5.1: professional company websites at the figma.com and x.ai level, with one section per screen, real photographs, real product UI, effects kept for tech and gaming pages, and a real-browser checker and finish gate.
1 skill
SPARC methodology — Specification, Pseudocode, Architecture, Refinement, Completion phases with quality gates
3 skills · 1 command · 1 agent
5 skills + 35 modes + Material Passport pipeline. Includes v3.6.7 cross-model audit gate and v3.6.8 generator-evaluator contract.
5 skills · 16 commands · 4 agents · hooks
Build, deploy, and operate applications on AWS. Skills to author infrastructure-as-code, use core services, and complete common tasks.
27 skills · 1 MCP server
Eval-gated LLM fine-tuning lifecycle (LoRA/QLoRA, DPO, GRPO/RLVR, vision SFT, quantized export). Use when fine-tuning an open-weights model end-to-end: building the eval harness first, selecting method and model, preparing data, training with Unsloth or TRL, gating checkpoints, and exporting GGUF/FP8.
10 skills · 2 commands · 3 agents
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