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 majiayu000/claude-skill-registry --skill agent-designgit clone --depth 1 https://github.com/majiayu000/claude-skill-registryWrote 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/majiayu000/claude-skill-registry/agent-design)<a href="https://agentmods.dev/skills/majiayu000/claude-skill-registry/agent-design"><img src="https://agentmods.dev/badge/skills/majiayu000/claude-skill-registry/agent-design/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/majiayu000/claude-skill-registry/agent-design"><img src="https://agentmods.dev/badge/skills/majiayu000/claude-skill-registry/agent-design.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 | $0.00011 | $0.01072 |
| Opus 5 | $0.00005 | $0.00536 |
| Sonnet 5 | $0.00002 | $0.00214 |
| Haiku 4.5 | $0.00001 | $0.00107 |
Grade A, and why
agent-design 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 9d 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 — 238 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent Design
Skill for designing high-performance AI agents following 2025 patterns.
Documentation
- patterns.md - Multi-agent architecture patterns
- workflows.md - Recommended workflows
Fundamental Distinction
Workflows vs Agents
| Type | Control | When to use |
|---|---|---|
| Workflow | Code orchestrates LLM | Predictable tasks, need for control |
| Agent | LLM directs its actions | Flexibility, adaptive decisions |
Golden rule: Start simple, add complexity if necessary.
Agent Architecture
Minimal Structure
Agent:
identity: Who am I?
capabilities: What can I do?
tools: What tools do I have?
constraints: What are my limits?
workflow: How should I proceed?
Complete Structure (Production)
---
name: my-agent
description: Short description
model: sonnet|opus
tools: [list of tools]
skills: [associated skills]
---
# Identity
[Who the agent is]
# Capabilities
[What it can do]
# Workflow
[Steps to follow]
# Tools
[How to use each tool]
# Constraints
[Limits and rules]
# Examples
[Use cases]
# Forbidden
[What it must NEVER do]
Agent Patterns
1. Single Agent (Simple)
User → Agent → Response
Usage: Simple tasks, rapid prototyping.
2. Agent + Tools
User → Agent ↔ Tools → Response
↑
Tool Results
Usage: Tasks requiring external access (API, files, DB).
3. Orchestrator + Subagents
User → Orchestrator → Subagent 1 (specialized)
→ Subagent 2 (specialized)
→ Subagent 3 (specialized)
↓
Synthesis → Response
Usage: Complex tasks, separation of responsibilities.
4. Sequential Pipeline
User → Agent 1 → Agent 2 → Agent 3 → Response
(Analyze) (Plan) (Execute)
Usage: Linear processes (e.g., Analyst → Architect → Developer).
Fresh Eyes Principle
Key 2025 concept: Each sub-agent must have a "fresh" context.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 9d ago First seen · 238 lines · 11 tokens per session scan A cb09dc6168fc
agent-design is a skill published in the GitHub repository majiayu000/claude-skill-registry (606 stars, last pushed today), licensed MIT. It adds 11 tokens to every session and 1,072 once invoked, about $0.0001 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 2026-09-03.
Other skills, from other repositories
remotion-docs
Search and fetch Remotion documentation pages.
remotion-captions
Dealing with captions in Remotion.
remotion-render
Best practices for rendering videos.
academy-guide
Stop and check this skill before finishing any reply to a question about how to use Claude or a Claude product — it recommends matching courses, tutorials, and use cases from Claude Academy (academy.claude.com), Anthropic's learning hub. Trigger on: "how do I", "how can I", "getting started with", "what can Claude…
remotion-maps
Remotion Map animation knowledge.
mediabunny
Multimedia handling with the Mediabunny library.