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 yyz666ai/Learning-Agent --skill new-topic-researchgit clone --depth 1 https://github.com/yyz666ai/Learning-AgentWrote 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/yyz666ai/learning-agent/new-topic-research)<a href="https://agentmods.dev/skills/yyz666ai/learning-agent/new-topic-research"><img src="https://agentmods.dev/badge/skills/yyz666ai/learning-agent/new-topic-research.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 | $0.00037 | $0.00924 |
| Opus 5 | $0.00018 | $0.00462 |
| Sonnet 5 | $0.00007 | $0.00185 |
| Haiku 4.5 | $0.00004 | $0.00092 |
Grade A, and why
new-topic-research 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
新主题研究
当知识库没有可靠内容，或库、框架、API 会随版本变化时，先建立可信事实，再规划课程。研究不是给学习者堆链接，而是为教学决策提供最小、可追溯的依据。
判断
- 目标型短课且知识库已有同版本资产：可以直接复用，不重复搜索。
- 选择“完整掌握”或高级工程师路线时，即使知识库已有基础内容，也要核对知识覆盖、当前版本、工程实践与毕业项目需要的官方资料。
- 当日已完成且通过深度字段校验的
sources.json可直接复用；重试 Plan 时不重复搜索。复用前必须确认顶层topic与本轮用户主题一致；不得因目录名相似而复用另一主题。文件缺失、过期、版本不清或覆盖不足才重新上网。 - 新库、新框架、新 API、陌生项目或版本敏感内容：必须研究。
- 用户提供的帖子、截图和面试题只能作为线索，不能替代官方文档。
研究动作
- 先用
python tools/web_search.py "<主题> official documentation getting started"搜索。 - 优先官方文档、官方仓库、标准或原始论文；必要时读取具体页面的正文。研究总预算约 90 秒，最多一次搜索和三个关键页面，每个页面最多 15 秒；禁止顺序探测十几条链接。HTTP 200 只证明地址可访问，不证明内容已读。搜索仅返回“我将搜索”等计划文字时不能当事实；可以在预算内直接读取已知官方文档，仍无有效证据则明确报告失败，不无限尝试。
- 只收集影响学习路线的事实：当前版本、先修、最小安装、核心心智模型、运行机制、测试调试、工程边界、性能安全、最小运行例和常见破坏性差异。 面试路线必须使用“完整目标岗位 + 已确认技术栈”限定范围：优先官方技术文档、公开岗位能力要求和权威工程资料；公开面经只用来发现题型与表达场景，不把无来源答案当作事实。研究结果同时列出岗位能力域、技术栈核心主题、常见追问链和初学者先修缺口。
- 输出结构化
sources.json，必须写入调用任务给出的完整精确路径；不要自己翻译主题、推测 slug 或另建相似目录。字段必须严格使用：- 顶层：
topic,researched_at,version,sources,teaching_facts,coverage_areas,prerequisites,graduation_project； - 每个 source：
id,title,url,kind； - 每个 teaching fact：
statement,source_ids； 每个事实必须引用一个已存在的 source id，不要改成fact/source等近义字段。 顶层topic必须与用户的原始学习主题一致；路线、起点、学习范围只是元数据，不得追加到topic或放进括号。
- 顶层：
- 完整掌握路线的
coverage_areas至少覆盖五个真正不同的能力域。graduation_project可以是详细字符串，也可以是含name、goal、evidence的对象；必须是可验收的大型综合产出。 - 把研究结果交给
learning-plan；每章生成时只注入与本章相关的来源事实，不要在研究阶段直接生成整章课件。
边界
- 搜索失败时停止生成正式 Plan，保留用户输入并允许重试。
- 不复制大段文档；用自己的话提炼并保留短引用来源。
- 未验证的信息标为不确定，不能写入共享知识库。
What ships with it
1 file 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 · 38 lines · 37 tokens per session scan A b90a84bf7bc3
new-topic-research is a skill published in the GitHub repository yyz666ai/Learning-Agent (1 stars, last pushed 8d ago), licensed MIT. It adds 37 tokens to every session and 924 once invoked, about $0.0002 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.
Other skills, from other repositories
skillpack-creator
Create a reusable SkillPack from a successful completed task. Use when the user wants to convert a one-off research, coding, analysis, or content workflow into a distributable local SkillPack with skillpack.json, local skills under skills/, starter prompts, start scripts, and an optional zip package.
skill-creator
Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.
commit
Atomic git commit with conventional message. Use when the user says "commit", "save my changes", "commit this", or wants to create a git commit. Stages specific files, writes a conventional commit message with body explaining non-obvious decisions. Never uses git add -A.
python-run
Run and debug Python scripts in the project. Use when the user says "run python", "execute this script", "debug this py file", or wants to run/modify a .py file. Handles dependency checks, linting, execution, and error analysis.
goga-discover
Interview the user relentlessly about a decision until every branch of the design tree is resolved, then record the result as a short ADR.
akirule
Aki's contextual rule router — invoke BEFORE acting whenever the task touches any of - .md/.vue/.css/.tsx/.rs/.sql files; docs, plan, README, CHANGELOG; UI, component, CSS, tailwind; SEO, schema, sitemap; release, version, commit, push, deploy; DB schema, migration; Tauri; i18n, UI copy; pricing, biz; UX review…