github-workflows
claudePR management, multi-repo PR finalization, and issue shaping with Shape Up methodology
18 skills
Specific to the maintainer's own setup and not intended for general use
Plugin jpe-ai-delegation from marketplace jacobpevans-cc-plugins in dryvist/claude-code-plugins. Commands read from the repo's manifest — 3 days ago.
delegation-ladderApply the executor ladder for the maintainer's own setup, including eligibility and verification rules.
PR management, multi-repo PR finalization, and issue shaping with Shape Up methodology
18 skills
High-level operational runbooks for homelab management: DR-node power management, DNS ingress convergence, and secrets-engine identity bring-up
9 skills
Harness-agnostic session continuity: goal statements, status snapshots, cold resume, replanning, and wrap-up. No git or GitHub required.
7 skills
Delegate tasks to AI models, orchestrate premium-model work, and run autonomous maintenance loops
7 skills
Agent and skill builders, authoring standards, workspace management, and skills/tools registry lookup
7 skills
Systematic CodeQL alert analysis and resolution for GitHub Actions workflows
2 skills · 1 command · 3 agents
AI-powered codebase understanding — analyze, visualize, and explain any project
9 skills · 10 agents · hooks
Open-source AI job search that runs locally in your AI coding CLI: scan job portals, evaluate listings into a structured A-H report with a 1-5 score, tailor your CV, track applications
5 skills · hooks
Rewrite AI-sounding text so it reads like the writer without changing what it says.
1 skill
AI memory system — mine projects and conversations into a searchable palace. 47 MCP tools, auto-save hooks, guided setup.
3 skills · 6 commands · 1 MCP server · hooks
Perform AI code review on Git diffs — supports workspace changes, branch ranges, and single commits with concurrent per-file analysis, codebase search, and deep context-aware review.
2 commands
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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