opfor-setup
Set up an agent or chatbot target for Opfor red-teaming.
Skills
Find an Agent Skill for your task. Read the guide and copy the install command.
Updated 11-05 00:16
Agents & models
25,653 results
create-agent
Create a Claude Code Agent. Activated when requested to create an agent, write AGENT.md, or create a new agent.
prompt-improver
Analyze and improve prompts using evidence-based techniques. Enhance prompt quality by applying proven techniques such as Few-shot, CoT, XML structuring, and Context Engineering. Use when requested for prompt improvement, prompt review, prompt optimization, or prompting improvement.
skill-creator
Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Claude's…
pi-prompt-authoring
Author SYSTEM.md or APPEND_SYSTEM.md for pi coding agent. Use when extending the default system prompt with custom principles, guidelines, or project rules.
context-slim
Compresses potential LLM context sources - project and global CLAUDE.md, rules, agent descriptions, hook text, memory - by cross-layer dedup, default-knowledge…
agent-teams
Pre-composed agent team library. Use when the user asks which teams are available, what a team does, when to pick one team over another, or to browse…
acpx
Use acpx as a headless ACP CLI for agent-to-agent communication, including prompt/exec/sessions workflows, session scoping, queueing, permissions, and output…
human-in-loop-agents
Build agents that pause for human approval, review, and intervention. Use this skill when implementing approval workflows, human oversight, agent interrupts,…
llm-fallback-chains
Use this skill when implementing fallback strategies for LLM applications. Activate when the user needs graceful degradation for AI services, multi-provider…
model-routing-strategy
Use this skill when implementing model selection for LLM applications. Activate when the user needs to choose between different AI models, implement…
prompt-caching-patterns
Use this skill when implementing caching for LLM applications. Activate when the user wants to reduce API costs through caching, implement semantic caching,…
langchain-development
Expert guidance for LangChain and LangGraph development with Python, covering chain composition, agents, memory, and RAG implementations.
mandatory-verification
Mandatory external verification workflow for ALL non-trivial factual claims before presenting them as true. This skill MUST be used whenever Claude is asked to…
panel-review-rationalisation
Panel health assessment, firm exit management, coverage gap analysis, and panel refresh brief for in-house legal ops teams. Produce an annual Panel Health…
privilege-sentinel
Pre-flight privilege and work-product check for legal AI prompts. Use when the user is about to send legal content to a third-party AI surface (ChatGPT,…
skill-injection-defense
Audits legal AI skills, prompts, workflows, MCP/tool instructions, and agent packages for prompt injection, malicious instructions, unsafe scripts, suspicious…
lazyweb-explain-flow
EXPLAIN how something works with a hosted, tappable flow diagram — a walkthrough, a failure trace, an answer to "how does X work?", a hypothetical. Saves…
dspy-chain-of-thought
Use when the task benefits from intermediate reasoning before producing an answer — multi-step logic, analysis, math, or complex classification where direct…
find-skills
Helps users discover and install agent skills when they ask questions like "how do I do X", "find a skill for X", "is there a skill that can...", or express…
ln-005-multi-agent-context-review
Multi-agent context review: delegates plans, decisions, documents, architecture proposals to external agents (Codex + Gemini) for independent review with…
ln-014-agent-instructions-auditor
Audits CLAUDE.md, AGENTS.md, GEMINI.md for token budget, prompt cache safety, compact instructions, and cross-agent consistency. Use after editing instruction…
effective-harnesses
Long-running agent project harness for Codex, OpenClaw, Claude Code, and other coding agents. Use to initialize or maintain projects that need feature…
lark-workflow-multi-agent-dev
Multi-programming-agent collaboration: supports three working modes—competition mode, division-of-labor mode, and pipeline mode; task management and result tracking are done via Feishu Bitable and messages. Use when the user needs 'parallel development', 'multi-agent', 'competition mode', 'division-of-labor mode', 'pipeline collaboration', or 'code comparison'.