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 ssmurfgg04-gif/context-m --skill gaokao-generate-reportgit clone --depth 1 https://github.com/ssmurfgg04-gif/context-mWrote 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/ssmurfgg04-gif/context-m/gaokao-generate-report)<a href="https://agentmods.dev/skills/ssmurfgg04-gif/context-m/gaokao-generate-report"><img src="https://agentmods.dev/badge/skills/ssmurfgg04-gif/context-m/gaokao-generate-report/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/ssmurfgg04-gif/context-m/gaokao-generate-report"><img src="https://agentmods.dev/badge/skills/ssmurfgg04-gif/context-m/gaokao-generate-report.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00067 | $0.00566 |
| Opus 5 | $0.00034 | $0.00283 |
| Sonnet 5 | $0.00013 | $0.00113 |
| Haiku 4.5 | $0.00007 | $0.00057 |
Grade A, and why
gaokao-generate-report 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 8d 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
生成志愿填报报告
本 Skill 是流水线的第五步：合并前序 JSON，渲染 HTML 报告。
上下游
- 上游：
parsed.json（志愿列表）major_recommendation.json（专业推荐）school_recommendation.json（院校推荐）
- 输出：
volunteer_report.html
环境准备
cd gaokao-generate-report
python3 -m venv .venv && source .venv/bin/activate
pip install -r requirements.txt
执行步骤
1. 合并为 analysis.json
python3 scripts/merge_analysis.py \
--majors output/major_recommendation.json \
--schools output/school_recommendation.json \
-o output/analysis.json
merge_analysis.py 将专业推荐与院校推荐合并为 generate_html.py 所需的 analysis.json 结构。
2. 生成 HTML
python3 scripts/generate_html.py \
-i output/parsed.json \
-a output/analysis.json \
-o output/volunteer_report.html
3. 交付用户
提供 volunteer_report.html 的绝对路径，并简要说明报告结构：
- 综合测评与建议（专业方向 + 院校策略）
- 志愿推荐列表（冲/稳/保，⭐ 推荐学校 / 🔥 推荐专业可点击查看详情）
合并前检查
| 检查项 | 说明 |
|---|---|
| 专业字段一致 | recommended_majors 的 name/code 与 parsed.json 一致 |
| 院校字段一致 | recommended_schools 的 name/code 与 parsed.json 一致 |
| 文案完整 | intro、strategy、school_strategy 非空 |
若合并前发现推荐字段不匹配，应回到对应 Skill 修正 JSON。
附加资源
- examples/analysis_merged_example.json — 合并后的完整结构示例
What ships with it
5 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.
- 8d ago First seen · 70 lines · 67 tokens per session scan A b5bf1112bc7d
gaokao-generate-report is a skill published in the GitHub repository ssmurfgg04-gif/context-m (2 stars, last pushed yesterday), licensed Apache-2.0. It adds 67 tokens to every session and 566 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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