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 agentmods add instructions/adsorgcn/chanlun-engine-skill/agents-mdgit clone --depth 1 https://github.com/adsorgcn/chanlun-engine-skillWrote 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/instructions/adsorgcn/chanlun-engine-skill/agents-md)<a href="https://agentmods.dev/instructions/adsorgcn/chanlun-engine-skill/agents-md"><img src="https://agentmods.dev/badge/instructions/adsorgcn/chanlun-engine-skill/agents-md.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 | $0.00289 | $0.00289 |
| Opus 5 | $0.00144 | $0.00144 |
| Sonnet 5 | $0.00058 | $0.00058 |
| Haiku 4.5 | $0.00029 | $0.00029 |
Grade A, and why
chanlun-engine-skill AGENTS.md 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 4d 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
chanlun-engine-skill
本仓库是一个 Agent Skill：用确定性脚本计算 A 股缠论结构（分型/笔/线段/中枢/买卖点/背驰）， 输出四态操作判定（买入候选/持有/卖出减仓/等待观察）与失效价位。
规则入口：读 SKILL.md 并严格遵守其中的硬性禁令与新手引导流程。 核心纪律：脚本算一切结构与判定，你只解读转述；禁止自己看K线心算缠论。
常用命令（在仓库根目录）：
python scripts/setup_env.py --recommended # 环境自检+装免费行情源
python scripts/get_data.py --symbol 600519 --out k.csv # 取日K(自动选数据源)
python scripts/chan_engine.py --symbol 600519.SH --csv k.csv # 结构+判定 JSON
Codex 用户安装为技能：把本仓库放入 .agents/skills/chanlun-engine-skill/（项目级）
或 ~/.agents/skills/chanlun-engine-skill/（用户级），或用 $skill-installer install <本仓库URL>。
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.
- 4d ago First seen · 19 lines · 289 tokens per session scan A 237852746e8e
chanlun-engine-skill AGENTS.md is an instructions file published in the GitHub repository adsorgcn/chanlun-engine-skill (8 stars, last pushed 10d ago), licensed MIT. It adds 289 tokens to every session, about $0.0014 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 2026-08-31.
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