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SkillsMP는 DojoGenesis/gateway에서 89개의 skill을 수집했습니다. skill을 열어 소스와 세부 정보를 확인하세요.
수집된 skill 89개 중 40개를 표시합니다.
Produces a dispatch plan — isolation model, agent count, sequencing, and model assignments — for multi-agent parallel work. Use when: "dispatch agents in parallel", "run multiple tracks simultaneously", "plan parallel agent strategy", "should this be…
원문 언어: 영어
Produces a structured background-dispatch handoff — task description, output contract, success criteria, and timeout — so long-running work completes without blocking the user. Use when: "run this in the background", "dispatch agent for long task", "I need…
원문 언어: 영어
Routes health-audit findings to the correct execution path — main thread, foreground fix, or parallel agent waves. Use when health-audit findings need to be sorted by effort and dispatched as agent waves.
원문 언어: 영어
Produces a granular todo list where each item maps to one discrete deliverable or decision point, maintained at real-time accuracy throughout execution. Use when: 'what is the status', 'too many items in the list', 'simplify the progress tracking', 'long todo…
원문 언어: 영어
Conductor agent pattern that decomposes complex tasks, dispatches specialist sub-agents, manages dependencies, and synthesizes results into a unified deliverable. Use when: 'coordinate multiple specialist agents', 'orchestrate a complex multi-phase task',…
원문 언어: 영어
Selects the correct multi-agent orchestration pattern for a task using an 11-signal selection matrix. Use when choosing which orchestration pattern fits a multi-agent task.
원문 언어: 영어
Produces a verified multi-track execution by dispatching parallel agents with file manifests, independent verification, and status tracking. Use when: "dispatch agents", "parallel tracks", "multi-track work", "fan out", "divide and conquer".
원문 언어: 영어
Produces a structured codebase map — directory roles, entry points, dependency graph, architectural patterns, and dragon locations — for any unfamiliar repository. Use when: 'map this codebase for me', 'I need to understand this repo before I start', 'give me…
원문 언어: 영어
Produces a scored comparison of available DESIGN.md design systems against a project's requirements and delivers a recommended selection with adaptation notes. Use when: 'which design system fits this project', 'pick a design reference for me', 'match a…
원문 언어: 영어
Extracts design tokens, component structure, and layout from a Figma file and produces framework-specific code (HTML, Svelte, React, or Vue) that preserves design intent rather than pixel-copying. Use when: 'implement this Figma design', 'convert this Figma…
원문 언어: 영어
5-layer code analysis (AST, Call Graph, CFG, DFG, PDG) that yields 95% token savings over raw file reads. Use when: 'systematically understand an unfamiliar codebase', 'analyze code structure with minimal tokens', 'map call graphs and data flow', 'find dead…
원문 언어: 영어
Produces a typeset PDF artifact from any source file — code, Markdown, HTML, chat JSON, or structured Dojo files (specs, ADRs, skills). Use when: "export this to PDF", "generate a PDF of this file", "make a PDF from this".
원문 언어: 영어
Configure Pretext typography settings for PDF export — font stacks, sizing, line height, page geometry, and disposition-driven typography mapping. Use when defaults need tuning for specific content types or audiences.
원문 언어: 영어
Produces a signed distribution manifest and CAS-packaged skill set by orchestrating the full community-to-Dojo pipeline: shallow-clone repos, scan for compatibility, normalize frontmatter in parallel batches of 10, package via dojo CLI, and emit manifest.json…
원문 언어: 영어
Produces an enriched SKILL.md with all six Dojo SkillRegistry.IsValid() fields populated — name, description, tier, agents, tool_dependencies, and trigger phrases — inferred from the existing body without rewriting it. Use when: "normalize this skill", "make…
원문 언어: 영어
Produces a compatibility catalog — skill-scan-report.md and skill-scan-catalog.json — classifying every SKILL.md in one or more GitHub repos or local paths as ready, normalizable, or incompatible, so you know exactly what normalization work lies ahead before…
원문 언어: 영어
Produces a quantified current-state report (test count, aria markers, error boundaries, storage usage, dependencies) used to anchor specifications in measured reality rather than assumptions. Use when: 'audit the codebase before speccing', 'ground this spec…
원문 언어: 영어
Spec-to-fix pipeline: audit a codebase against its specification, classify gaps by severity, fix in parallel, track in GAPS.md registry. Use when a spec exists but implementation completeness is unknown.
원문 언어: 영어
Produces a gap inventory and Track 0 remediation commit that closes mismatches between implementation prompts and actual codebase state, ensuring parallel tracks start from a clean, type-safe foundation. Use when: 'commission these tracks', 'run Track 0…
원문 언어: 영어
Adversarial code review that breaks the self-review monoculture. Use when you want a genuinely critical review of recent changes, before merging a PR, or when you suspect Claude is being too agreeable about code quality. Forces perspective shifts through…
원문 언어: 영어
Produces an aggregated markdown performance report from stored trace data — tool call metrics, token usage, cost, bottlenecks, and numbered recommendations. Use when: "session cost report", "what ran this week", "why did this spike", "end-of-sprint…
원문 언어: 영어
Produces a structured APPROVE / WARN / BLOCK decision by checking remaining token budget across query, session, and monthly tiers before an expensive operation runs. Use when: "is this operation within budget", "pre-flight check before web search", "budget…
원문 언어: 영어
Produces a verified build/test status report and auto-fixed modules by sweeping all Go modules in a workspace. Use when: "run a sweep", "check all builds", "nightly sweep", "fix all failing modules", "workspace health check".
원문 언어: 영어
Produces a CLAUDE.md health report listing conflicts, redundancies, and stale rules across the global, project, and subdirectory hierarchy — and optionally installs a PreToolUse hook to block unauthorized modifications. Use when: "agent behavior is…
원문 언어: 영어
Runs a structured 7-phase convergence session to arrest strategic drift after 3-4 Sonnet feature sessions. Use when the drift-detector fires YELLOW or RED, or when you notice accumulating uncommitted state, deferred validations, and growing open-items lists.
원문 언어: 영어
Produces a hook script scaffold and settings.json registration block by looking up the correct lifecycle event, exit code pattern, and configuration for a Claude Code hook. Use when: "write a new hook", "hook is not firing", "block a tool call mechanically",…
원문 언어: 영어
Scaffolds new MCP servers with tool definitions, transport wiring, handler structure, and test harness for Python (FastMCP) or TypeScript (MCP SDK). Use when: 'build a new MCP server', 'scaffold an MCP integration', 'create tools for an external API', 'set up…
원문 언어: 영어
Produces a running multi-agent observability dashboard by deploying the hook capture pipeline, SQLite WAL store, and WebSocket-streaming Vue client — then validates it with a live test session. Use when: "set up monitoring for multi-agent workflows", "debug…
원문 언어: 영어
Produces an architectural specification document mapping Gateway SSE events and OTEL spans to named dashboard widgets, a data flow diagram, and an MCP App config — ready to hand to an implementation agent. Use when: "design the observability dashboard", "spec…
원문 언어: 영어
Produces a provenance determination — pointer or gap — for empty or apparently incomplete directories, with a documented rationale and recommended action. Use when: "this directory is empty", "missing SKILL.md", "coverage metric shows a gap", "why is this…
원문 언어: 영어
Produces a Supply Chain Refresh Report and updated manifest.json by pulling the latest from all watched repos, scanning for new or changed skills, normalizing, and packaging them into CAS. Use when: "refresh the supply chain", "update community skills",…
원문 언어: 영어
Produces structured OTEL-compatible log entries and a session summary (call counts, success rate, cost, top tools by cost and frequency) for all tool executions within a session. Use when: "log tool calls for this session", "debug unexpected tool selection",…
원문 언어: 영어
Map an external AI tool's behavioral patterns to Dojo ADA disposition fields by analyzing its ingested system prompt. Produces a disposition YAML approximation and similarity score against Dojo defaults. Use when understanding how other agents think or when…
원문 언어: 영어
Produces a cross-tool disposition matrix, behavioral cluster analysis, and a set of named YAML disposition presets by synthesizing analyses from 3+ ingested AI system prompts. Use when: "build an intelligence map", "compare all agent behaviors", "generate…
원문 언어: 영어
Maintains a running decision log and context state across agent sessions, preventing context loss between clears and session boundaries. Use when: 'starting a new session on an ongoing project', 'context is getting heavy', 'preserve state before clearing',…
원문 언어: 영어
Produces a stored MemoryEntry (structured sections + ADA disposition indicators) and one or more MemorySeeds by parsing a system prompt from an external AI tool into Dojo memory. Use when: "ingest this system prompt", "store this prompt in memory", "parse…
원문 언어: 영어
Captures user corrections from a session, validates them semantically, and writes approved learnings to the most specific persistence target (skill file, project CLAUDE.md, or global CLAUDE.md). Use when: "remember this for next time", "don't do that again",…
원문 언어: 영어
Produces updated memory artifacts by compressing a session's key decisions, changes, and context into the structured memory garden. Use when: "compress this session", "save context", "end of session", "update memory", "wrap up".
원문 언어: 영어
Designs and configures all three loops of solo-operator session automation — session bookends, background maintenance agents, and a delegation flywheel. Use when setting up a new workspace, recovering from the 44% zero-artifact session leak, or preparing to…
원문 언어: 영어
Produces a named ADA disposition preset (YAML) and a layered behavioral analysis (structural decomposition + evidence-cited classifications) from a system prompt. Use when: "analyze this system prompt", "extract disposition from prompt", "reverse-engineer…
원문 언어: 영어