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-collect-student-infogit 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-collect-student-info)<a href="https://agentmods.dev/skills/ssmurfgg04-gif/context-m/gaokao-collect-student-info"><img src="https://agentmods.dev/badge/skills/ssmurfgg04-gif/context-m/gaokao-collect-student-info/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-collect-student-info"><img src="https://agentmods.dev/badge/skills/ssmurfgg04-gif/context-m/gaokao-collect-student-info.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 | $0.00099 | $0.02112 |
| Opus 5 | $0.00049 | $0.01056 |
| Sonnet 5 | $0.00020 | $0.00422 |
| Haiku 4.5 | $0.00010 | $0.00211 |
Grade A, and why
gaokao-collect-student-info 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 9d 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.
How it starts
The opening of the file, as written. The whole thing — 124 lines — stays where its author put it; the contents beside it link to each section on GitHub.
高考考生信息采集
本 Skill 是志愿推荐流水线的第一步，仅负责与用户对话并产出 student.json，不调用 API、不做推荐。
核心原则：还原原生描述
只负责收集，不负责加工。 下游专业推荐、院校推荐依赖考生自己怎么说，过度改写会造成信息 gap。
| 做法 | 说明 |
|---|---|
| ✅ 保留原话 | interests、family_situation、career_direction、notes 等文本字段，尽量使用考生原句或贴近原意的完整表述，不润色、不升华、不替考生总结 |
| ✅ 如实记录 | 考生口语、重复、模糊表述均可保留；可在 notes 中补充其原话，而非改写成「标准答案」 |
| ✅ 仅做必要结构化 | province、score、classify、subjects 等 API 必填项，只做格式归一（如分数取整数、选科逗号分隔） |
| ✅ 显式信息才入库 | preferred_* 仅记录考生明确说出的院校、城市、层次、专业类；未提及则不臆造 |
| ❌ 禁止过度干预 | 不把「想搞代码」改写成「计算机科学与技术方向」；不替考生补充其未表达的职业规划；不在本阶段做专业/院校推荐或倾向推断 |
向用户复述确认时，也应引用其原话核对，而非用你改写后的版本代替。
上下游
- 上游：无
- 下游：gaokao-fetch-volunteers 读取本 Skill 输出，将倾向映射为 API 选填参数
采集清单
API 必填（写入 student.json 顶层）
| 字段 | 说明 | 示例 |
|---|---|---|
province |
高考省份 | 山东 |
classify |
文科/理科/物理/历史/综合 | 综合 |
score |
高考成绩（整数） | 650 |
batch |
填报批次 | 本科批 |
subjects |
3+1+2：完整三科（首选科目+两门再选）；3+3：完整三科；老高考 null |
物理,化学,生物 |
gradeType |
仅北京/上海/天津：本科/专科 | 本科 |
rank |
位次，无则 null |
5000 |
辅助画像（原话优先，供下游分析）
| 字段 | 说明 | 填写要求 |
|---|---|---|
interests |
兴趣爱好 | 考生原话，逗号或自然句均可，勿概括 |
family_situation |
家庭情况 | 考生原话，保留其表述的经济、地域、深造态度等 |
career_direction |
未来就业/发展方向 | 考生原话，哪怕模糊也照录，不下结论 |
subject_scores |
各科分数 | 数字字段，按考生填报 |
preferred_cities |
意向城市 | 仅列考生明确提到的城市 |
preferred_provinces |
意向省份 | 考生明确提到则录入；否则可留空，由下游从城市推导 |
preferred_universities |
心仪院校 | 使用考生口中的校名全称或原称，不擅自替换简称 |
preferred_tags |
院校层次意向 | 仅录考生亲口说过的（如「想上 985」），勿自行推断 |
preferred_major_classes |
专业类意向 | 仅录考生明确提到的专业/方向，勿从兴趣推断改写 |
notes |
其他补充 | 不适合归入上述字段的原话、禁忌、特殊诉求 |
倾向字段的 API 映射由下游 gaokao-fetch-volunteers 处理；本阶段不必为凑 API 参数而改写或补全 preferred_*。
工作流程
- 用自然语言逐项询问，缺什么问什么；可分批提问。
- 按省份确定选科模式并填对 API 字段（见下表与 reference.md）。
- 将考生回答按原意录入对应字段；仅对 API 必填项做格式归一。
- 信息齐全后保存
output/student.json，用考生原话复述关键内容并请其确认。
What ships with it
3 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.
- 9d ago First seen · 124 lines · 99 tokens per session scan A f387d614f7bf
gaokao-collect-student-info is a skill published in the GitHub repository ssmurfgg04-gif/context-m (2 stars, last pushed yesterday), licensed Apache-2.0. It adds 99 tokens to every session and 2,112 once invoked, about $0.0005 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.
Other skills, from other repositories
ai-style
A Chinese-language writing guide for producing or revising reader-facing text such as product announcements, public-account articles, emails, and README files. It focuses on reducing patterns that make writing sound machine-generated.
triage
A task-routing guide that identifies goals, dependencies, and acceptance conditions before work begins. It orders work as research, calculation or execution, and writing.
coding
A coding guide for writing and running Python programs in a sandbox. It requires scripts to be small and reproducible, with their actual output or errors reported.
gsd-help
Show available GSD commands and usage guide.
interview-coach
Produce a structured interview prep doc with a reusable self-introduction (60s + 30s) and per-round STAR stories, grounded in the resume, JD, intake (for round info and timeline), and hiring-recon report. Output is one markdown file.
socratic-duel-run
Run Socratic Duel through two participant subagents while the launcher only coordinates and reports.