Harness Engineering From Claude Code to AI Coding is a Chinese technical book that studies how AI coding agents are engineered, using analysis of Claude Code's released source material. It is intended for engineers and researchers building coding agents, agent frameworks, and model-tool platforms.
Borrowing it
Nothing to install: this file belongs to ZhangHanDong/harness-engineering-from-cc-to-ai-coding. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/ZhangHanDong/harness-engineering-from-cc-to-ai-coding/main/.claude/skills/skillify/SKILL.mdgit clone --depth 1 https://github.com/ZhangHanDong/harness-engineering-from-cc-to-ai-codingWrote 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/zhanghandong/harness-engineering-from-cc-to-ai-coding/skillify)<a href="https://agentmods.dev/skills/zhanghandong/harness-engineering-from-cc-to-ai-coding/skillify"><img src="https://agentmods.dev/badge/skills/zhanghandong/harness-engineering-from-cc-to-ai-coding/skillify/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/zhanghandong/harness-engineering-from-cc-to-ai-coding/skillify"><img src="https://agentmods.dev/badge/skills/zhanghandong/harness-engineering-from-cc-to-ai-coding/skillify.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Rogue Agent · line 6 Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
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 | $0.00074 | $0.01705 |
| Opus 5.5 | $0.00030 | $0.00682 |
| Sonnet 5.5 | $0.00015 | $0.00341 |
| Haiku 4.5 | $0.00007 | $0.00170 |
Grade A, and why
skillify 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 2mo 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- skillify — 89% identical, 31 lines differ
How it starts
The opening of the file, as written. The whole thing — 135 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skillify
Extracted from Claude Code v2.1.88 internal
/skillifyskill (originallyant-only).
You are capturing this session's repeatable process as a reusable skill.
Your Task
Step 1: Analyze the Session
Before asking any questions, analyze the full conversation to identify:
- What repeatable process was performed
- What the inputs/parameters were
- The distinct steps (in order)
- The success artifacts/criteria (e.g. not just "writing code," but "an open PR with CI fully passing") for each step
- Where the user corrected or steered you
- What tools and permissions were needed
- What agents were used
- What the goals and success artifacts were
Step 2: Interview the User
You will use the AskUserQuestion tool to understand what the user wants to automate. Important notes:
- Use AskUserQuestion for ALL questions! Never ask questions via plain text.
- For each round, iterate as much as needed until the user is happy.
- The user always has a freeform "Other" option to type edits or feedback -- do NOT add your own "Needs tweaking" or "I'll provide edits" option. Just offer the substantive choices.
Round 1: High level confirmation
- Suggest a name and description for the skill based on your analysis. Ask the user to confirm or rename.
- Suggest high-level goal(s) and specific success criteria for the skill.
Round 2: More details
- Present the high-level steps you identified as a numbered list. Tell the user you will dig into the detail in the next round.
- If you think the skill will require arguments, suggest arguments based on what you observed. Make sure you understand what someone would need to provide.
- If it's not clear, ask if this skill should run inline (in the current conversation) or forked (as a sub-agent with its own context). Forked is better for self-contained tasks that don't need mid-process user input; inline is better when the user wants to steer mid-process.
- Ask where the skill should be saved. Suggest a default based on context (repo-specific workflows -> repo, cross-repo personal workflows -> user). Options:
- This repo (
.claude/skills/<name>/SKILL.md) -- for workflows specific to this project - Personal (
~/.claude/skills/<name>/SKILL.md) -- follows you across all repos
- This repo (
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.
- 2mo ago First seen · 135 lines · 74 tokens per session scan A 5b2c2dc4b835
skillify is a skill published in the GitHub repository ZhangHanDong/harness-engineering-from-cc-to-ai-coding (1,515 stars, last pushed 7mo ago), licensed MIT. It adds 74 tokens to every session and 1,705 once invoked, about $0.0003 per session on Opus 5.5. 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.
skillify compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| skillifyZhangHanDong/harness-engineering-from-cc-to-ai-coding | Skill | 1.5k | 7mo ago | MIT | A | 74 | Claude Code |
| imagegenopenai/codex | Skill | 133k | yesterday | Apache-2.0 | A | 113 | Codex |
| playwright-climicrosoft/playwright | Skill | 99k | yesterday | Apache-2.0 | A | 19 | Claude Code |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | 4d ago | MIT | A | 200 | Claude Code, Codex |
| systematic-debuggingobra/superpowers | Skill | 313k | 3d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | today | MIT | A | 95 | Claude Code |
| next-partial-prefetching-adoptionvercel/next.js | Skill | 143k | today | MIT | A | 103 | Claude Code |