Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add gmh5225/awesome-skills --skill ai-llm-skillsgit clone --depth 1 https://github.com/gmh5225/awesome-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/gmh5225/awesome-skills/ai-llm-skills)<a href="https://agentmods.dev/skills/gmh5225/awesome-skills/ai-llm-skills"><img src="https://agentmods.dev/badge/skills/gmh5225/awesome-skills/ai-llm-skills/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/gmh5225/awesome-skills/ai-llm-skills"><img src="https://agentmods.dev/badge/skills/gmh5225/awesome-skills/ai-llm-skills.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00035 | $0.00726 |
| Opus 5 | $0.00017 | $0.00363 |
| Sonnet 5 | $0.00007 | $0.00145 |
| Haiku 4.5 | $0.00003 | $0.00073 |
Grade A, and why
ai-llm-skills-guide scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 112 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AI Agents & LLM Development Skills
Scope
Use this skill when:
- Finding or adding AI/LLM related skills
- Understanding agent architecture patterns
- Working with RAG, embeddings, or vector databases
- Implementing multi-agent systems
Key Skill Categories
Agent Frameworks
| Framework | Description |
|---|---|
| LangGraph | Stateful, multi-actor AI applications |
| CrewAI | Role-based multi-agent orchestration |
| AutoGen | Microsoft's multi-agent framework |
RAG (Retrieval-Augmented Generation)
| Component | Skills |
|---|---|
| Embeddings | Text embedding models, chunking strategies |
| Vector DBs | Pinecone, Weaviate, Chroma, Qdrant |
| Retrieval | Hybrid search, reranking, context optimization |
Observability & Tracing
| Tool | Purpose |
|---|---|
| Langfuse | Open-source LLM observability |
| LangSmith | LangChain tracing and debugging |
| Weights & Biases | ML experiment tracking |
Memory Systems
| Type | Description |
|---|---|
| Short-term | Conversation buffer, sliding window |
| Long-term | Vector store persistence, entity memory |
| Episodic | Experience-based memory recall |
Context Engineering Skills
Core Concepts
- Context fundamentals: What context is and why it matters
- Context degradation: Lost-in-middle, poisoning, distraction patterns
- Context compression: Summarization, trimming strategies
- Context optimization: Caching, masking, compaction
Multi-Agent Patterns
- Orchestrator pattern
- Peer-to-peer collaboration
- Hierarchical delegation
- Tool-using agents
Where to Add in README
- Agent frameworks:
AI Agents & LLM Development - RAG tools:
AI Agents & LLM DevelopmentorData & Analysis - Observability:
AI Agents & LLM Development - Context engineering:
Context Engineering
Key Repositories
sickn33/antigravity-awesome-skills/skills/
├── langgraph/
├── crewai/
├── langfuse/
├── rag-engineer/
├── prompt-engineer/
├── voice-agents/
├── agent-memory-systems/
└── autonomous-agents/
muratcankoylan/Agent-Skills-for-Context-Engineering/skills/
├── context-fundamentals/
├── context-degradation/
├── context-compression/
├── multi-agent-patterns/
└── memory-systems/
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 112 lines · 35 tokens per session scan A 785117267c75
ai-llm-skills-guide is a skill published in the GitHub repository gmh5225/awesome-skills (48 stars, last pushed 4d ago), licensed MIT. It adds 35 tokens to every session and 726 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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