CS146S_CN is a Chinese-language, hands-on course about developing software with coding agents, including agent skills, MCP, specification-driven development, testing, deployment, and software-factory practices. It is for programmers learning how to design and use agent-assisted development workflows. The catalogue entries are commands associated with the course.
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.
git clone --depth 1 https://github.com/ShouZhengAI/CS146S_CNWrote 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/commands/shouzhengai/cs146s_cn/refactor-module)<a href="https://agentmods.dev/commands/shouzhengai/cs146s_cn/refactor-module"><img src="https://agentmods.dev/badge/commands/shouzhengai/cs146s_cn/refactor-module.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 | $0.00000 | $0.00208 |
| Opus 5 | $0.00000 | $0.00104 |
| Sonnet 5 | $0.00000 | $0.00042 |
| Haiku 4.5 | $0.00000 | $0.00021 |
Grade A, and why
refactor-module 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 7d 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.
What it actually says
Refactor a module safely
Refactor the module described by $ARGUMENTS (include old path, new path, and any symbol rename). Refuse to guess if either path is missing.
- Inspect the module, all imports/re-exports, tests, documentation, and string references.
- Establish a clean baseline with
ruff check backendand the narrowest relevant pytest test file. - Move the module once, update all callers and tests, and remove the obsolete path. Do not leave compatibility shims unless requested.
- Run
ruff check backend,black --check backend, and the relevant tests; then runpytest -q backend/tests --maxfail=1. - Search again for the old import path and symbol. Report changed files, verification commands/results, and any intentional remaining textual references.
Preserve public behavior and database data. Do not use destructive Git commands. If validation fails, keep the working tree inspectable and describe how to revert only the files changed by this workflow.
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.
- 7d ago First seen · 11 lines · 0 tokens per session scan A 5d41d8f00057
refactor-module is a command published in the GitHub repository ShouZhengAI/CS146S_CN (1,542 stars, last pushed 6d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 208 tokens. 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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