195 skills · sorted by relevance
Synchronizes README.md Command Center with current project state. Triggers on gate changes, EPIC status changes, or explicit `/ghm-status-sync` invocation. Outputs updated README.md dashboard with current lifecycle stage, blockers, and metrics.
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Creates new Source of Truth (SoT) files when existing templates don't fit your needs. Triggers on requests to create a new SoT file, add a new artifact type, or when user says "I need to track [X] but there's no SoT for it", "create SoT", "new source of truth". Outputs a properly structured SoT.*.md file with ID prefix, frontmatter, and update protocol.
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Designs cross-session agent memory: point-in-time facts, consolidation, tenant isolation. Use when auditing user memory or Mem0/Zep. Not for repo context (dev-context-engineering).
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Creates reusable vector-brain implementations: repo, docs, compliance. Use when building pgvector SQL, manifests, ingest scripts. Not for context design (dev-context-engineering).
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Context-driven AI development with AGENTS.md, repo knowledge bases, Claude Code, Codex, and Copilot. Use when adopting repo-native AI workflows or multi-repo setups.
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Optimizes agent context setup. Use when starting a new session, when agent output quality degrades, when switching between tasks, or when you need to configure rules files and context for a project.
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Context window management. Auto-triggered when context is filling up. Triggers smart compaction and preserves critical information across compaction boundaries. Called by L1 orchestrators at context thresholds.
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Use when a long session has accumulated stale or conflicting context or the user asks to refresh it. Not for remote, credential, publish, deploy, or irreversible changes.
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Master context engineering for AI agent systems. Use when designing agent architectures, debugging context failures, optimizing token usage, implementing memory systems, building multi-agent coordination, evaluating agent performance, or developing LLM-powered pipelines. Covers context fundamentals, degradation patterns, optimization techniques (compaction, masking, caching), compression strategies, memory architectures, multi-agent patterns, LLM-as-Judge evaluation, tool design, and project development.
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Engineer the full context a model sees — system prompts, retrieved knowledge, tool definitions, state, and history as one designed artifact. Use when moving beyond prompt tweaks to systematic context design.
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Audit a repo's agent context — CLAUDE.md files, codebase docs, skills, and tool/MCP designs — against Anthropic's Claude 5 context-engineering guidance ("unhobbling": Anthropic cut ~80% of Claude Code's system prompt with no eval loss). Finds overconstraint, conflicting instructions, redundancy, stale facts, and missing "unknown knowns"; produces a scored findings report with concrete rewrites, then applies approved fixes. Use when someone says "audit my CLAUDE.md", "context audit", "unhobble this repo", "review our agent docs/skills/tools", or after upgrading to Claude 5-generation models.
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Optimizes agent context setup. Use when starting a new session, when agent output quality degrades, when switching between tasks, or when you need to configure rules files and context for a project.
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Read-only audit of the project's agent-tree structural overhead vs the context window. NOT for cost tracking (budget skill); NOT for read/compact decisions (mk:context-engineering).
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Runtime router for context decisions: read-more/stop/ask/assume/delegate, minimal read-set, compaction timing. Model: Write/Select/Compress/Isolate. NOT for agent-tree overhead audit (context-audit).
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Creates new skills with proper structure, compliance checks, and registration. Enforces mk: prefix, sub-agents.md structure, and context-engineering principles. Use to scaffold a new skill.
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Runtime router for context decisions: read-more/stop/ask/assume/delegate, minimal read-set, compaction timing. Model: Write/Select/Compress/Isolate. NOT for .codex/ overhead audit (mk:context-audit).
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Read-only audit of .codex/ structural overhead: 'remove X save Y tokens' vs the context window. NOT for cost tracking (budget skill); NOT for runtime read/compact decisions (mk:context-engineering).
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Use when refining a draft user prompt before sending it to a coding agent. Decomposes goal/context/constraints/acceptance/output-format, detects ambiguity and model-coupled framing, then emits a model-agnostic rewrite. Supports --analyze, --score, and --deep. NOT for prompts from scratch (mk:brainstorming), plans/reviews (mk:elicit), implementation plans (mk:plan-creator), or general codebase scouting (mk:scout).
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Read-only audit of `.claude/` structural overhead. Reports prioritized "remove X save Y tokens" recommendations against the model context window. NOT for monetary cost tracking — that's /mk:budget. NOT for transcript size monitoring — long-session continuity defers to Claude Code native compaction. NOT for runtime context decisions (what to read, when to compact) — see mk:context-engineering. Use when planning to add context capacity, diagnosing perceived slowdowns, or auditing health.
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Semantic search, grep, and Q&A across codebases and documentation indexed in CodeAlive. Use when the user mentions "CodeAlive", asks to list or get data sources, list indexed repositories, search code or docs across remote repos, fetch artifact content, or trace call graphs across repositories.
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Optimizes agent context setup. Use when starting a new session, when agent output quality degrades, when switching between tasks, or when you need to configure rules files and context for a project.
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This skill should be used when the user asks.
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Use when starting a coding session, setting up a project for AI-assisted development, switching between parts of a codebase, or when agent output quality degrades — hallucinated APIs, wrong patterns, ignored project conventions. Structures what the agent loads and when.
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Loads and manages company context for all C-suite advisor skills. Reads ~/.claude/company-context.md, detects stale context (>90 days), enriches context during conversations, and enforces privacy/anonymization rules before external API calls. Use when starting any C-suite advisor session, when context looks stale or missing, or before sending company data to an external service.
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