Catalog
All AI skills
30 skills. Every one is readable here; downloads and live use need a subscription.
codex-fable5
Apply Fable-inspired discipline to Codex work: inspect first, track goals and findings, ground conclusions in evidence, verify before completion, and adapt Claude/Fable prompt guidance without identity or provider claims.
cv-generator
Generate professional, ATS-optimized CVs for FlowCV, Canva, Google Docs, or Word. Handles multi-source merging, JD targeting, seniority adaptation, and humanized rewriting. Outputs paste-ready text with an ATS flaw report and improvement suggestions.
enhance-prompt
Transforms vague UI ideas into polished, Stitch-optimized prompts. Enhances specificity, adds UI/UX keywords, injects design system context, and structures output for better generation results.
fable-safe-prompt
Rewrite allowed prompts to reduce false-positive safety triggers without bypassing policy or changing intent.
llm-application-dev-prompt-optimize
You are an expert prompt engineer specializing in crafting effective prompts for LLMs through advanced techniques including constitutional AI, chain-of-thought reasoning, and model-specific optimizati
llm-prompt-optimizer
Use when improving prompts for any LLM. Applies proven prompt engineering techniques to boost output quality, reduce hallucinations, and cut token usage.
prompt-caching
Caching strategies for LLM prompts including Anthropic prompt caching, response caching, and CAG (Cache Augmented Generation)
prompt-engineer
Transforms user prompts into optimized prompts using frameworks (RTF, RISEN, Chain of Thought, RODES, Chain of Density, RACE, RISE, STAR, SOAP, CLEAR, GROW)
prompt-engineering
Expert guide on prompt engineering patterns, best practices, and optimization techniques. Use when user wants to improve prompts, learn prompting strategies, or debug agent behavior.
prompt-engineering-patterns
Master advanced prompt engineering techniques to maximize LLM performance, reliability, and controllability.
prompt-library
A comprehensive collection of battle-tested prompts inspired by [awesome-chatgpt-prompts](https://github.com/f/awesome-chatgpt-prompts) and community best practices.
research-prompt
Turn vague research needs into one precise deep-research prompt with context and output criteria.
agent-evaluation
Evaluate agent behavior with versioned cases and explicit verifiers. Use when comparing agent or prompt changes, reproducing failures, or running agent regression tests.
agent-orchestration-improve-agent
Systematic improvement of existing agents through performance analysis, prompt engineering, and continuous iteration.
ai-engineering-toolkit
6 production-ready AI engineering workflows: prompt evaluation (8-dimension scoring), context budget planning, RAG pipeline design, agent security audit (65-point checklist), eval harness building, and product sense coaching.
ask-copilot
Use GitHub Copilot CLI in non-interactive mode to ask questions, review code, or generate snippets without manual interaction.
brave-man
Runs a structured clarifying interview for new project requests before building. Instead of writing code, it outputs a fully specified prompt.md for a fresh agent session to execute, preventing expensive mistakes.
generate-nanobanana
Generate and edit images/video with Google's Gemini media models (Nano Banana 2/Pro, Gemini Omni Flash), with cost-approval gates, reference-image support, and a prompt/output log per call.
idea-autopsy
Autopsy a business idea before you build it: kill-list check, five hard filters, a free-AI one-prompt test, live ad-market verification, and a verdict with a named kill-pattern.
langfuse
Expert in Langfuse - the open-source LLM observability platform. Covers tracing, prompt management, evaluation, datasets, and integration with LangChain, LlamaIndex, and OpenAI. Essential for debugging, monitoring, and improving LLM applications in production.
llm-ops
LLM Operations -- RAG, embeddings, vector databases, fine-tuning, prompt engineering avancado, custos de LLM, evals de qualidade e arquiteturas de IA para producao.
llm-security
Authorized security assessment of LLM applications and AI agents: prompt injection, tool abuse, RAG exposure, memory poisoning, system-prompt extraction, and agent-compliance engineering per OWASP LLM/ASI Top 10.
logic-fix-all
Autonomous repository-wide audit-and-fix pipeline: health → review → locate/explain → fix → diff-verify → iterate until clean. Starts with a mandatory consent prompt (token-intensive); after consent runs hands-free.
recursive-context-pruning-token-budgeting
Optimizes AI agent performance by pruning redundant context, managing token usage, and enforcing ultra-concise, direct-to-value responses.
rich-elicitation
Asks clarifying questions in multiple rounds before starting ambiguous tasks. Fires when 2+ task dimensions each have 3+ viable answers.
skill-issue
Find out why a coding-agent skill won't fire — grade each SKILL.md A–F on activation, simulate which skill a prompt triggers, and flag collisions where one silently shadows another.
skill-scanner
Scan agent skills for security issues before adoption. Detects prompt injection, malicious code, excessive permissions, secret exposure, and supply chain risks.
skill-suggester
Scan prompt history for recurring patterns and unmet needs, then propose new skills or command templates
unified-ai-gateway
Operate and evaluate Unified AI System through nine governed MCP tools, including provider-free prompt enhancement, while preserving fake-provider, authorization, and evidence boundaries.
zipai-optimizer
Ultra-dense token optimizer skill for prompt caching, log pruning, AST-based inspection, and minified JSON payloads.