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Found 771 Skills
Orchestrate teams of parallel Claude Code sessions working on the same codebase. Handles task decomposition, agent coordination, context isolation, and merge strategies. Builds on worktree-manager for infrastructure.
Run all security scanners against the project and produce a unified, severity-bucketed report. Orchestrates gitleaks (secrets), osv-scanner/trivy (dependency vulns), semgrep (static analysis), context-file injection scanner (built-in), and repo hygiene checks (built-in). Missing scanners are skipped with install hints — the scan always completes. Triggers on: 'security check', 'security scan', 'run security', 'scan for secrets', 'check for vulnerabilities', 'security audit', 'audit dependencies', 'check secrets', 'find vulnerabilities', 'scan codebase'.
Use this skill when managing multi-repository systems using the `meta` tool (github.com/mateodelnorte/meta). Triggers on meta git clone, meta exec, meta project create/import/migrate, coordinating commands across many repos, running npm/yarn installs across all projects, migrating a monorepo to a multi-repo architecture, or any workflow that requires running git or shell commands against multiple child repositories at once.
A comprehensive development team tailored for beginners, consisting of product managers, architects, designers, developers, and testers, guiding you through the entire process from concept to launch.
Create or update the skill registry for the current project. Scans user skills and project conventions, writes .atl/skill-registry.md, and saves to engram if available. Trigger: When user says "update skills", "skill registry", "actualizar skills", "update registry", or after installing/removing skills.
2-stage pipeline: trace (causal investigation) -> deep-interview (requirements crystallization) with 3-point injection
Multi-agent pipeline orchestrator that plans and dispatches parallel development tasks to worktree agents. Reads project context, configures task directories with PRDs and jsonl context files, and launches isolated coding agents. Use when multiple independent features need parallel development, orchestrating worktree agents, or managing multi-agent coding pipelines.
Use when orchestrating multi-agent teams for parallel work — feature dev, quality audits, research sprints, bug hunts, or any task needing 2+ agents working concurrently
Classify user requests and route to the correct agent + skill combination. Use for any user request that needs delegation: code changes, debugging, reviews, content creation, research, or multi-step workflows. Invoked as the primary entry point via "/do [request]". Do NOT handle code changes directly - always route to a domain agent. Do NOT skip routing for anything beyond pure fact lookups or single read commands.
Multi-step voice content generation with deterministic validation. Orchestrates a 7-phase pipeline: LOAD, GROUND, GENERATE, VALIDATE, REFINE, OUTPUT, CLEANUP. Use when generating content in a specific voice, writing as a persona, or validating existing content against a voice profile. Use for "voice write", "write as", "generate in voice", or "voice content". Do NOT use for creating new voice profiles (use voice-calibrator), analyzing writing samples (use voice_analyzer.py), or general content without a voice target.
Fresh-subagent-per-task execution with two-stage review (ADR compliance + code quality). Use when an implementation plan exists with mostly independent tasks and you want quality gates between each. Use for "execute plan", "subagent", "dispatch tasks", or multi-task implementation runs. Do NOT use for single simple tasks, tightly coupled work needing shared context, or when the user wants manual review after each task.
Optimize BigQuery compute costs by assigning data models (Dataform, dbt, Airflow) to slot reservations or on-demand compute based on Masthead recommendations.