Loading...
Loading...
Found 11,972 Skills
JavaScript reverse engineering and browser debugging MCP server with anti-detection and agent-first tooling
Security hardening guide for high-privilege autonomous AI agents (OpenClaw) with zero-trust architecture, behavior controls, and automated auditing
Produce a token-bounded context pack from the Obsidian wiki — a compact, structured slice of the most relevant pages for a topic or recent activity, designed for downstream consumption by another agent or skill. Use when the user says "/wiki-context-pack", "make a context pack", "give me a context slice for X", "pack the wiki for my agent", or "bounded context for Y". Different from wiki-query (which answers a question) — this produces reusable input material for a downstream task.
Run multiple AI coding agent sessions in parallel using git worktrees — each agent isolated in its own worktree, working on a separate branch. Use this skill whenever the user wants to: run two or more AI agents simultaneously on different features or bugs, set up isolated agent workspaces in the same repo, push parallel branches to GitHub and open/update PRs, coordinate between concurrent agent sessions, or clean up after merging. Triggers on: "parallel agents", "multiple agent sessions", "git worktree", "run agents in parallel", "work on two things at once", "isolated agent workspace", "spin up another agent", or any request involving simultaneous AI-assisted development streams.
Run adversarial review on a PM artifact via the pm-critic sub-agent. Dispatches natively on Claude Code with the pm-skills plugin (invokes @agent-pm-critic); on non-Claude clients (Codex CLI, Cursor, Windsurf, Copilot, Gemini CLI) reads subagents/pm-critic.md and executes the system prompt inline. Returns findings graded P0/P1/P2/P3 with concrete fix suggestions per finding, plus a layered Status Summary section and machine-readable Status YAML block per master plan D26.
Manus-style context engineering for Agent Teams. Coordinate multiple Claude Code instances with shared planning files. Use when complex tasks need parallel work (code review, debugging, feature development). Requires CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS=1.
Provision a zero-config, no-signup Upstash Redis database for an AI agent via a single POST to `https://upstash.com/start-redis`. Use when an agent needs scratch Redis for short-term memory, conversation history, sub-agent work queues, or ranked recall and the user has not provided credentials. The database lives 3 days unless the user claims it.
AI-powered OSINT agent with interactive REPL, MCP server, and CLI for email/username/domain/IP/phone investigation using 11 integrated tools
Every PostHog resource in one CLI — with offline search, agent-native output, and cross-resource analytics no... Trigger phrases: `check my PostHog feature flags`, `query PostHog events`, `show experiment results in PostHog`, `what errors are spiking in PostHog`, `LLM costs in PostHog`, `is it safe to ramp this flag`, `use posthog`.
For use when students **have completed WG-12 to WG-21** (single-file consolidation blueprint) and are working on **WG-22 Code Splitting** (`agent_core.py` + `main.py`). **First message in a new session**: Display PEAS brand screen and confirm readiness first; after confirmation, **lay out the context** before proceeding to requirement clarification. If **`prompts/` or `templates/`** are missing, copy them from `references/project_assets/` to the project root. Process: Spec Alignment (2d′) → Six-column Contract → **In-session Handoff Implementation** → Acceptance. Starting point: starter_main_wg21.py; Standard reference: reference_agent_core.py + reference_main.py. Triggers: peas-workshop-advanced-coach, PEAS workshop advanced coach, WG-22, code splitting coach, Agent.chat.
Build and maintain project-specific review policy for `agentic-review` by combining repository docs (`AGENTS.md`, `ENGINEERING.md`, `CONTEXT.md`/`CONTEXT-MAP.md`, ADRs), repository-mined conventions, and structured user input, then writing machine-usable policy files under `<docs-dir>/review/policies/`, including audit-governance metadata consumed by `agentic-review`. Use when the user wants architecture integrity checks (onion/clean/hexagonal), module-specific review rules, dependency-direction policy, naming/inheritance convention enforcement, stricter project/domain review standards, or explicit auditability requirements for specialist review coverage.
Apply when context is filling up: large outputs, long files, repeated reads, fan-out planning. Route bulk to subagents; keep summaries in the main thread, not raw payloads.