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-design-christophe1997-agent-extentionsgit 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-christophe1997-agent-extentions)<a href="https://agentmods.dev/skills/majiayu000/claude-skill-registry/agent-design-christophe1997-agent-extentions"><img src="https://agentmods.dev/badge/skills/majiayu000/claude-skill-registry/agent-design-christophe1997-agent-extentions/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-christophe1997-agent-extentions"><img src="https://agentmods.dev/badge/skills/majiayu000/claude-skill-registry/agent-design-christophe1997-agent-extentions.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 | $0.00052 | $0.01287 |
| Opus 5 | $0.00026 | $0.00643 |
| Sonnet 5 | $0.00010 | $0.00257 |
| Haiku 4.5 | $0.00005 | $0.00129 |
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 — 197 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent Design Guidelines
Overview
Designing tools for AI agents is as much art as science. The key principle: give agents tools shaped to their own abilities — which you discover by paying attention to their outputs.
The Mental Model
Imagine being given a difficult math problem. What tools would you want?
| Tool | Limitation |
|---|---|
| Paper only | Limited by manual calculations |
| Calculator | Better, but requires knowledge to operate |
| Computer | Most powerful, but requires coding skills |
The right tool depends on your own abilities. Same for agents — design tools that match what the model can actually do well.
Core Principles
1. Claude Must "Like" Calling the Tool
Even the best designed tool doesn't work if Claude doesn't understand how to call it.
- Test if the model naturally uses the tool
- Read outputs to see if it's confused
- Iterate on the interface until it "clicks"
2. Tools That Were Necessary Can Become Constraints
As models improve:
- Old workarounds become unnecessary
- Previous "helps" become limitations
- Constantly revisit assumptions
Example: TodoWrite reminders helped older models but made newer ones think they couldn't modify the list.
3. Progressive Disclosure Over Context Bloat
Instead of stuffing everything in the system prompt:
- Give agents tools to discover context themselves
- Let them search, read, and explore recursively
- Skills can reference other files for nested discovery
4. High Bar for New Tools
More tools = more options to think about = cognitive overhead.
- Claude Code has ~20 tools
- Consider: can this be a subagent? A skill? Progressive disclosure?
- Only add tools when truly necessary
Design Patterns
Pattern: Structured Elicitation (AskUserQuestion)
Problem: Claude asking questions in plain text was slow and unstructured.
Failed Attempts:
- Adding questions to another tool's output → confused the model
- Modified markdown format → unreliable output
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 · 197 lines · 52 tokens per session scan A 453de99eeec4
agent-design is a skill published in the GitHub repository majiayu000/claude-skill-registry (606 stars, last pushed today), licensed MIT. It adds 52 tokens to every session and 1,287 once invoked, about $0.0003 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.
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