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 HK-hub/AgentSkills --skill agent-native-designgit clone --depth 1 https://github.com/HK-hub/AgentSkillsWrote 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/hk-hub/agentskills/agent-native-design)<a href="https://agentmods.dev/skills/hk-hub/agentskills/agent-native-design"><img src="https://agentmods.dev/badge/skills/hk-hub/agentskills/agent-native-design.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00038 | $0.02783 |
| Opus 5 | $0.00019 | $0.01392 |
| Sonnet 5 | $0.00008 | $0.00557 |
| Haiku 4.5 | $0.00004 | $0.00278 |
Grade A, and why
agent-native-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 6d 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.
This is a copy
94% identical to agent-native-design — 18 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 239 lines — stays where its author put it; the contents beside it link to each section on GitHub.
agent-native-design
Purpose
This skill helps analyze, design, and refactor command-line tools so they can reliably serve humans, AI agents, and orchestration systems at the same time.
It is not a skill for merely using a CLI. It is a skill for designing and reviewing a CLI as an agent-native interface.
The skill focuses on four goals:
- Make CLI behavior predictable for AI agents.
- Make CLI output readable and recoverable for humans.
- Make CLI execution manageable for systems and orchestrators.
- Define a complete interaction loop from authentication to error routing.
When to use this skill
Use this skill when the user wants to:
- evaluate whether an existing CLI is agent-friendly
- redesign a CLI to better support AI agents
- convert an API or SDK into an agent-native CLI
- review help output, schema design, exit codes, or JSON contracts
- design dry-run, auth delegation, or safety boundaries
- generate CLI skills, docs, or interface conventions from schema
- refactor a human-oriented CLI into a machine-friendly one
- define how a CLI should interact with an agent runtime
Typical prompts include:
- "Review this CLI and tell me whether it is agent-native."
- "Design a CLI for this API that an AI agent can use reliably."
- "Refactor this tool so stdout is machine-readable and safer for agents."
- "Help me define schema introspection, dry-run, and exit code semantics."
When not to use this skill
Do not use this skill when the user only wants:
- help running a specific command
- installation help for a CLI
- shell troubleshooting unrelated to interface design
- generic Linux or terminal tutorials
- agent planning or memory design unrelated to tools
- API business logic review without any CLI/tooling layer
Core model
An agent-native CLI must simultaneously serve three audiences.
1. Human
Needs: readable output, friendly error messages, onboarding guidance.
Channels: stderr, optional --format table, interactive TUI when appropriate.
What ships with it
9 files 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.
- 6d ago First seen · 239 lines · 38 tokens per session scan A 2fdd06193619
agent-native-design is a skill published in the GitHub repository HK-hub/AgentSkills (6 stars, last pushed 19d ago), licensed MIT. It adds 38 tokens to every session and 2,783 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 94% identical to agent-native-design, differing in 18 lines, and is treated as a copy.
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