Agent skills
Skills you can use with AI coding agents, indexed from public GitHub repositories.
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kaizen
持续改进 — V 阶段, 交付后自动复盘经验沉淀
WenJunDuan/Rlues 166
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plan-first
强制先规划后执行 — 基于 design.md 生成计划
WenJunDuan/Rlues 166
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brainstorm
需求头脑风暴 — R₀b 阶段, 探索方案空间
WenJunDuan/Rlues 166
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quickstart
新手引导 — 首次使用 VibeCoding 的引导流程
WenJunDuan/Rlues 166
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agent-teams
Agent Teams orchestration for Claude Code. Coordinates multiple Claude
instances working in parallel on shared codebase. Requires experimental
flag CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS=1.
New in v8.0, replaces multi-ai skill for Claude Code platform.
WenJunDuan/Rlues 166
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smart-archive
Intelligent context archiving for the 1M token era.
Replaces strategic-compact. Works with server-side Compaction API.
Archives completed RIPER phases to .ai_state/ instead of emergency compression.
WenJunDuan/Rlues 166
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iterative-retrieval
Large context iterative retrieval. For tasks requiring
information from many files, retrieves in batches to avoid
overwhelming the context window.
WenJunDuan/Rlues 166
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phase-router
P.A.C.E. v2.0 complexity routing engine. Analyzes task complexity
and routes to optimal path (A/B/C/D) with effort level mapping.
v8.0: Added Path D for Agent Teams, effort parameter integration.
WenJunDuan/Rlues 166
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continuous-learning
v1 basic learning. Extracts patterns from sessions and stores
them in the experience skill.
WenJunDuan/Rlues 166
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continuous-learning-v2
v2 Instinct-based learning system. Builds confidence through
repeated observations and evolves high-confidence patterns into skills.
WenJunDuan/Rlues 166
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verification-loop
Verify-fix-retry loop with cross-model validation support.
v8.0: Added --cross mode for dual-model verification.
WenJunDuan/Rlues 166
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context7
Library documentation fetcher using Context7 CLI (npx ctx7).
Provides up-to-date, version-specific docs for external libraries.
CLI version replaces Context7 MCP for lower context overhead.
WenJunDuan/Rlues 166
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service-analysis
Service boundary analysis. Identifies service boundaries,
dependencies, and integration points in the codebase.
WenJunDuan/Rlues 166
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eval-harness
Evaluation framework for measuring code agent effectiveness.
v8.0: Added Agent Teams collaboration quality metrics.
WenJunDuan/Rlues 166
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code-quality
Linus-style code quality enforcement. Checks taste, simplicity,
and engineering rigor.
WenJunDuan/Rlues 166
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model-router
Intelligent task-to-model routing based on benchmark data.
Routes tasks to Claude Code or Codex CLI based on task type
and model strengths. New in v8.0.
WenJunDuan/Rlues 166
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knowledge-base
Project knowledge management. Stores and retrieves project-specific
documentation, standards, and technical references.
WenJunDuan/Rlues 166
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experience
Experience management. Stores learned patterns, mistakes, and
best practices from past development sessions.
WenJunDuan/Rlues 166
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riper
RIPER execution cycle: Research → Innovate → Plan → Execute → Review.
Core workflow engine for all P.A.C.E. paths.
WenJunDuan/Rlues 166
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cunzhi
寸止确认机制。通过 cunzhi MCP 工具强制暂停等待用户确认。
真正的暂停，不是输出文字假装等待。
WenJunDuan/Rlues 166
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iterative-retrieval
Progressive context refinement for subagents and complex tasks. Retrieves
context incrementally based on actual needs rather than loading everything
upfront. Reduces context waste and improves relevance.
WenJunDuan/Rlues 166
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phase-router
Intent recognition and workflow routing. Analyzes user input to determine
task type and routes to appropriate agent. Core decision layer.
WenJunDuan/Rlues 166
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continuous-learning
Auto-extract reusable patterns from coding sessions. Activates on session end
or when /learn command is invoked. Identifies successful patterns, debugging
solutions, and architectural decisions worth preserving for future sessions.
WenJunDuan/Rlues 166
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continuous-learning-v2
Instinct-based learning system with confidence scoring. Automatically learns
patterns from sessions and evolves them into skills. Supports import/export
for team sharing.
WenJunDuan/Rlues 166