ac-autonomous-orchestrator
Main orchestrator for autonomous coding operations. Use when running autonomous sessions, coordinating components, managing the full lifecycle, or orchestrating implementations.
ac-checkpoint-manager
Manage checkpoints for rollback capability. Use when creating save points, rolling back changes, managing recovery points, or restoring previous states.
ac-code-validator
Validate code quality and standards. Use when running linting, checking types, validating code style, or performing static analysis.
ac-commit-manager
Manage git commits for autonomous coding. Use when committing feature implementations, creating descriptive commits, managing git workflow, or handling version control.
ac-complexity-assessor
Assess feature and project complexity. Use when estimating effort, determining spec pipeline type, calculating cost estimates, or planning resource allocation.
ac-config-manager
Configuration management for autonomous coding. Use when loading settings, managing environment variables, configuring providers, or setting up autonomous mode options.
ac-context-compactor
Manage and compact context for long sessions. Use when context is filling up, creating handoff summaries, optimizing context usage, or preparing for session continuation.
ac-context-optimizer
Optimize context usage for autonomous coding. Use when managing context window, prioritizing information, reducing token usage, or improving efficiency.
ac-criteria-validator
Validate acceptance criteria and feature completion. Use when checking if features pass, validating test results, verifying acceptance criteria, or determining feature completion status.
ac-feature-analyzer
Analyze features and their dependencies. Use when mapping feature relationships, detecting blockers, optimizing build order, or identifying critical paths.
ac-handoff-creator
Create handoff packages for session transitions. Use when ending sessions, preparing for continuation, saving session state, or creating resumable context.
ac-hooks-manager
Hook installation and management for autonomous coding. Use when setting up Stop hooks, managing pre/post tool hooks, or configuring autonomous continuation.
ac-insight-extractor
Extract insights from autonomous coding sessions. Use when learning from completions, extracting patterns, analyzing decisions, or improving future performance.
ac-knowledge-graph
Manage knowledge graph for autonomous coding. Use when storing relationships, querying connected knowledge, building project understanding, or maintaining semantic memory.
ac-master-controller
Master controller for complete autonomous operation. Use when starting full autonomous projects, managing end-to-end workflow, controlling autonomous lifecycle, or running complete implementations.
ac-memory-manager
Manage persistent memory for autonomous coding. Use when storing/retrieving knowledge, managing Graphiti integration, persisting learnings, or accessing episodic memory.
ac-parallel-coordinator
Coordinate parallel autonomous operations. Use when running parallel features, managing concurrent work, coordinating multiple agents, or optimizing throughput.
ac-qa-reviewer
Quality assurance review for implementations. Use when reviewing code quality, checking implementation standards, performing QA cycles, or validating feature quality.
ac-security-sandbox
Security sandbox for autonomous coding. Use when validating commands, configuring permissions, managing allowlists, or ensuring safe execution.
ac-session-manager
Session lifecycle management for autonomous coding. Use when starting sessions, resuming work, detecting session type (init vs continue), or managing auto-continuation between sessions.
ac-spec-generator
Generate feature lists from specifications. Use when creating feature_list.json, converting requirements to features, generating 50-100+ testable features, or initializing autonomous projects.
ac-spec-parser
Parse and validate project specifications. Use when loading YAML/JSON specs, validating spec structure, extracting requirements, or converting between spec formats.
ac-state-tracker
State persistence for autonomous coding. Use when saving progress, loading state, tracking features, managing checkpoints, or persisting data across sessions.
ac-stop-hook-analyzer
Analyze context and decide on continuation via Stop hook. Use when determining if work should continue, analyzing completion status, making continuation decisions, or implementing the Two-Claude pattern.
ac-task-executor
Execute implementation tasks in autonomous coding. Use when running feature implementations, executing build tasks, processing feature queue, or orchestrating task completion.
ac-tdd-runner
Run TDD cycle for feature implementation. Use when implementing features with RED-GREEN-REFACTOR, running test-driven development, automating TDD workflow, or ensuring test-first development.
ac-test-generator
Generate tests for features using TDD approach. Use when creating test files, generating test cases, implementing RED phase of TDD, or scaffolding test infrastructure.
ac-workspace-manager
Manage git worktrees for isolated development. Use when creating isolated workspaces, managing parallel development, handling worktree lifecycle, or merging completed work.
accessibility-testing
Accessibility testing with axe-core and Playwright. Use when checking WCAG compliance, finding a11y issues, ensuring keyboard navigation, or testing screen reader compatibility.
ack-resources
AWS Controllers for Kubernetes (ACK) for Kubernetes-native AWS resource management. Use when managing AWS resources via kubectl, implementing GitOps for infrastructure, creating self-service developer platforms, integrating AWS services with EKS workloads, or adopting existing AWS resources into Kubernetes.
agent-cost-optimizer
Real-time cost tracking, budget enforcement, and ROI measurement for AI agent operations. Track token usage, predict costs, enforce budget caps ($50-70/month typical), optimize model selection, cache results, measure cost-to-value. Use when tracking AI costs, preventing budget overruns, optimizing spend, measuring ROI, or ensuring cost-effective AI operations.
agent-memory-system
Persistent memory architecture for AI agents across sessions. Episodic memory (past events), procedural memory (learned skills), semantic memory (knowledge graph), short-term memory (active context). Use when implementing cross-session persistence, skill learning, context preservation, personalization, or building truly adaptive AI systems with long-term memory.
alphavantage-api
Alpha Vantage financial API for stocks, forex, crypto, and 50+ technical indicators. Use when fetching time series data, technical analysis, fundamentals, economic indicators, or news sentiment.
analysis
Comprehensive analysis operations for code, skills, processes, data, and patterns. Task-based operations with pattern recognition, metrics calculation, trend identification, and actionable insights generation. Use when analyzing code quality, reviewing skill effectiveness, identifying process improvements, extracting patterns, or generating insights from data.
anthropic-docs-updater
Automated documentation update mechanism for anthropic-expert skill. Five-step workflow from update detection through documentation fetching and processing to skill integration and validation. Use when updating Anthropic documentation, checking for new releases, fetching latest docs, keeping anthropic-expert current, or synchronizing with Anthropic product changes.
anthropic-expert
Comprehensive Anthropic product expertise covering Claude models, Claude API, Python SDK, Agent SDK, Claude Code, and Model Context Protocol. Six integrated capabilities with complete documentation, searchable references, code examples, and cross-product integration patterns. Use when working with Claude API, building agents, using SDKs, developing with Claude Code, integrating MCP servers, learning Anthropic products, optimizing costs, implementing Anthropic features, managing context, using Opus 4.5, or implementing advanced tool patterns.
api-testing
REST and GraphQL API testing with Playwright. Use when testing APIs, mocking endpoints, validating responses, or integrating API tests with E2E flows.
auto-claude-build
Auto-Claude autonomous build system. Use when running builds, understanding agent workflow, managing parallel execution, or troubleshooting build issues.
auto-claude-cli
Auto-Claude CLI command reference and usage patterns. Use when running specs, managing builds, checking status, or using CLI commands for autonomous coding tasks.
auto-claude-memory
Auto-Claude Graphiti memory system configuration and usage. Use when setting up memory persistence, configuring LLM/embedding providers, querying knowledge graph, or optimizing memory performance.
auto-claude-optimization
Auto-Claude performance optimization and cost management. Use when optimizing token usage, reducing API costs, improving build speed, or tuning agent performance.
auto-claude-setup
Complete Auto-Claude installation and setup guide for all platforms. Use when installing Auto-Claude on WSL, Windows, Linux, or macOS, setting up development environment, or troubleshooting installation issues.
auto-claude-spec
Auto-Claude spec creation and management. Use when creating feature specs, understanding spec pipeline phases, modifying requirements, or managing spec lifecycle.
auto-claude-troubleshooting
Auto-Claude debugging and troubleshooting guide. Use when fixing installation issues, debugging build failures, resolving agent errors, or diagnosing performance problems.
auto-claude-updater
Auto-update system for Auto-Claude skills and documentation. Use when checking for updates, synchronizing with upstream, updating skills automatically, or managing version compatibility.
auto-claude-workspace
Auto-Claude workspace and git worktree management. Use when reviewing changes, merging builds, managing branches, or understanding isolation strategy.
auto-updater
Automatically apply improvements to skills and the ecosystem based on system-reviewer findings and best-practices-learner insights. Workflow for automated improvement identification, priority assessment, safe application, validation, and rollback capability. Use when applying systematic improvements, automating enhancement cycles, bulk updating multiple skills, or implementing ecosystem-wide improvements.
autonomous-cost-optimizer
Token and cost optimization for autonomous coding. Use when tracking token usage, optimizing API costs, managing budgets, or improving efficiency.
autonomous-loop
Main orchestration loop for autonomous coding. Use when running autonomous sessions, orchestrating feature completion, managing continuous loops, or coordinating agent lifecycle.
autonomous-master
Master orchestrator for autonomous coding projects. Use when starting autonomous projects, continuing sessions, checking status, or running complete autonomous workflows.
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