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이 저장소의 skills
SkillsMP는 richfrem/agent-plugins-skills에서 138개의 skill을 수집했습니다. skill을 열어 소스와 세부 정보를 확인하세요.
richfrem/agent-plugins-skills수집된 skill 138개 중 40개를 표시합니다.
Codifies the plan-and-delegate workflow for evolving plugins, skills, and agents. Given a target (plugin/skill/agent name) and an evolution goal, this skill first brainstorms 2-3 approach options using the cheapest available model, presents them for…
원문 언어: 영어
Trigger with "explain agentic os", "how do I set up a persistent agent environment", "what is the CLAUDE.md hierarchy", "explain the context folder structure", "how does session memory work", "what is soul.md or user.md", "explain auto-memory or MEMORY.md",…
원문 언어: 영어
Pattern 5: Concurrent Event-Driven Multi-Agent Loop. Coordinates multiple Claude sessions as OS threads sharing a common event bus and memory address space. Every loop cycle is a full improvement cycle: execute, eval against benchmark (KEEP/DISCARD), emit…
원문 언어: 영어
Trigger: "set up agentic OS", "initialize agent harness", "init my project for AI agents", "where do I put CLAUDE.md", "create my agent environment", "set up persistent memory". Guides users through an interview to understand their use case, then scaffolds…
원문 언어: 영어
Trigger with "remember this", "update memory", "what should we record from this session", "capture learnings", "write a session log", or when closing a session. Guides agents on managing memory hygiene across sessions, deciding what to write to dated memory…
원문 언어: 영어
Continuously improves an existing agent skill based on eval results using the RED-GREEN-REFACTOR cycle. Apply when a skill's routing accuracy is low, trigger descriptions need sharpening, or os-eval-runner scores are below target. (1) run a RED baseline to…
원문 언어: 영어
Self-healing and self-evolving pattern for agents operating against repo capabilities, scripts, skills, sub-agents, selectors, workflows, and external systems. Classifies evolution events into four tiers — Friction/Workaround, Gap, Failure, Regression —…
원문 언어: 영어
(Industry standard: Parallel Agent) Primary Use Case: Work that can be partitioned into independent sub-tasks running concurrently across multiple agents. Parallel multi-agent execution pattern. Use when: work can be partitioned into independent tasks that N…
원문 언어: 영어
(Industry standard: Sequential Agent / Agent as a Tool) Primary Use Case: Delegating a well-defined task to a worker agent, verifying its execution, and repeating if necessary. Inner/outer agent delegation pattern. Use when: work needs to be delegated from a…
원문 언어: 영어
(Industry standard: Loop Agent / Single Agent) Primary Use Case: Self-contained research, content generation, and exploration where no inner delegation is required. Self-directed research and knowledge capture loop. Use when: starting a session (Orientation),…
원문 언어: 영어
(Industry standard: Routing Agent / Orchestrator Pattern) Primary Use Case: Analyzing an ambiguous trigger and routing it to one of the specific specialized implementations. Routes triggers to the appropriate agent-loop pattern. Use when: assessing a task,…
원문 언어: 영어
(Industry standard: Review and Critique Pattern) Primary Use Case: Iterative generation paired with adversarial review, continuing until an 'Approved' verdict is reached. Orchestrated adversarial review loop. Use when: research, designs, architectures, or…
원문 언어: 영어
Tiered memory system for cognitive continuity across agent sessions. Manages hot cache (session context loaded at boot) and deep storage (loaded on demand). Use when: (1) starting a session and loading context, (2) deciding what to remember vs forget, (3)…
원문 언어: 영어
Removes stale and orphaned entries from the RLM Summary Ledger. Use after files are deleted, renamed, or moved to keep the ledger in sync with the filesystem. <example> user: "Clean up the RLM cache after I renamed some files" assistant: "I'll use…
원문 언어: 영어
Knowledge Curator agent skill for the RLM Factory. Auto-invoked when tasks involve distilling code summaries, querying the semantic ledger, auditing cache coverage, or maintaining RLM hygiene. Supports both Ollama-based batch distillation and agent-powered…
원문 언어: 영어
Distills uncached files into the Recursive Language Model(RLM) Summary cache Ledger. You (the agent) ARE the distillation engine. Read each file deeply, write a high-quality 1-sentence summary, inject it via inject_summary.py. The purpose is if you read the…
원문 언어: 영어
Interactive RLM cache initialization. Use when: setting up a new project's semantic cache for the first time, or adding a new cache profile. Walks the user through folder selection, extension config, manifest creation, and first distillation pass.
원문 언어: 영어
3-Phase Knowledge Search strategy for the RLM Factory ecosystem. Auto-invoked when tasks involve finding code, documentation, or architecture context in the repository. Enforces the optimal search order: RLM Summary Scan (O(1)) -> Vector DB Semantic Search ->…
원문 언어: 영어
Interactively initializes the Vector DB plugin. Guided discovery asks which folders to index, confirms the manifest, then scaffolds vector_profiles.json for high-performance In-Process or Native Server connections. Mandatory first step before ingestion or…
원문 언어: 영어
Semantic search skill for retrieving code and documentation from the ChromaDB vector store. Use when you need concept-based search across the repository (Phase 2 of the 3-phase search protocol). V2 includes L4/L5 retrieval constraints.
원문 언어: 영어
Scaffolds a new slash command in an existing plugin. NOT for creating event-driven hooks (use `create-hook`) and NOT for standard skills (use `create-skill`).
원문 언어: 영어
Adds an MCP server integration configuration to an existing plugin. NOT for scaffolding a brand-new plugin (use `create-plugin`) and NOT for Azure hosted agents (use `create-azure-agent`).
원문 언어: 영어
Provides information about how to create, structure, install, and audit Agent Skills, Plugins, Antigravity Workflows, and Sub-agents. Trigger this when specifications, rules, or best practices for the ecosystem are required.
원문 언어: 영어
Provides active execution protocols to rigorously audit how code, directory structures, and agent actions comply with the authoritative ecosystem specs. Trigger when validating new skills, plugins, or workflows.
원문 언어: 영어
Trigger with "evaluate autoresearch fit", "score this skill for karpathy loop", "is this a good autoresearch candidate", "assess autoresearch viability for", "which skills are best for autonomous loop optimization", "score skills for 3-file architecture", or…
원문 언어: 영어
Fixes broken path references in plugin skill and agent files to ensure portability across installed environments. Use when you see "plugins/" paths in SKILL.md or agent files, need to standardize path references after installing a skill, want to audit and fix…
원문 언어: 영어
Audit file path references in plugins and skills. Trigger with "audit path references", "check file references", "find broken references", "path reference audit", "verify paths", or when you need to validate that all ./references in code actually exist in the…
원문 언어: 영어
Convert raw plugin analysis results into actionable improvement recommendations for agent-scaffolders and agent-scaffolders. Trigger with "synthesize learnings", "generate improvement recommendations", "what should we improve in our scaffolders", "update our…
원문 언어: 영어
Interactive skill to scaffold and optimize the .agents/ directory for any project mapping up Antigravity configuration. Sets up .gemini/GEMINI.md, skills/, prompts/, and config.json using best practices. Produces a lean, modular configuration extending the…
원문 언어: 영어
Interactive skill to scaffold and optimize the .claude/ directory for any project. Sets up CLAUDE.md, .claude/rules/, .claude/settings.json with best practices, and optional hooks. Produces a lean, modular configuration that avoids monolithic context bloat.…
원문 언어: 영어
Local Gemma 4 12B sub-agent. Routes bounded tasks directly to the optimized llama-server at localhost:8089 — no routing proxy, no cloud API, 2–5s typical response. Use for fast, private, cost-free subtask delegation from any cloud primary agent. Part of the…
원문 언어: 영어
Cross-platform setup wizard for the local Gemma 4 12B inference stack. Automates llama-server installation (binary download or Metal/CUDA/Vulkan/ROCm compile), model download, routing proxy daemon install (launchd/systemd/NSSM), and Mode A/B validation.…
원문 언어: 영어
Interactive skill to scaffold and optimize configuration files for both Claude Code (.claude/) and Google ADK/Gemini (.agents/) directories. Trigger with "set up project", "scaffold agent config", "setup cli agent settings", or "configure agents for this…
원문 언어: 영어
Python dependency and environment management for multi-service or monorepo python backends. Use when: (1) adding, upgrading, or removing a Python package, (2) responding to Dependabot or security vulnerability alerts (GHSA/CVE), (3) creating a new service…
원문 언어: 영어
Reduces AI agent context bloat across three dimensions: (1) duplicate skill deduplication — clears stale agent directory copies since the IDE already reads from plugins/ directly; (2) instruction file optimization — rewrites CLAUDE.md, GEMINI.md, or…
원문 언어: 영어
Guides a Subject Matter Expert through a structured discovery session to create and approve a Discovery Plan before any building begins. This is the HARD-GATE brainstorming skill — no prototype can be built until the SME explicitly approves the plan. Trigger…
원문 언어: 영어
SME-facing orchestrator for the Business Exploration Loop. Supports 4 session types (greenfield, brownfield, discovery-only, spike) with adaptive phase selection. Manages state via exploration-dashboard.md, enforces phase gates, and routes to child skills in…
원문 언어: 영어
Builds a prototype component by component, self-reviewing each component against the Discovery Plan before moving to the next. Invoked by prototype-builder after the layout direction is confirmed. Trigger phrases: "build the prototype", "let's build it",…
원문 언어: 영어
Top-level orchestration skill coordinating the entire 7-step surgical vibe-to-enterprise reengineering pipeline with automated safety and economic optimization controls.
원문 언어: 영어
Presents layout options to the SME in plain language before any prototype construction begins. Invoked after the Discovery Plan is approved to confirm visual structure and direction. Trigger phrases: "what should it look like", "show me some layout options",…
원문 언어: 영어