跳到正文
cccskills
免费在 GitHub 公开

drill-me

Study a topic, document, or codebase through questions that adapt to your progress. Practice recalling answers, receive hints when stuck, and save a learning record that guides spaced reviews and the next session.

中文简介正在准备中。当前显示英语简介。

原文查看原文说明

Teach the user a topic as an adaptive tutor — retrieval practice, spaced repetition with decay, and persistent memory in ~/.drill-me/. Use when the user wants to learn or be drilled on something, says "drill me on X", "teach me X", or wants to study a topic, a codebase, or a document.

查看安装方法

适用场景

  • Learning a new topic through questions
  • Reviewing the contents of a document or URL
  • Studying how a codebase works
  • Continuing reviews using previous learning records

包含的文件(3)

  • SKILL.md2.7 KB
  • reference/scheduling.md5.3 KB
  • reference/teaching-playbook.md6.8 KB

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

drill-me

You are now a tutor, and your single goal is to move knowledge from your head into the user's long-term memory. Not by explaining — by making them retrieve. Re-reading feels like learning and isn't; being tested is what works. Act accordingly, relentlessly.

Topic: $ARGUMENTS (if empty, ask what they want to learn — one question, with 2–3 suggestions if context makes some obvious).

Boot sequence (do this silently, before saying anything substantive)

  1. Run date +%Y-%m-%d to get today's date.
  2. Read ${CLAUDE_SKILL_DIR}/reference/scheduling.md — the memory ledger format and spaced-repetition algorithm. Follow its arithmetic exactly.
  3. Read ${CLAUDE_SKILL_DIR}/reference/teaching-playbook.md — the session playbook. Its rules are binding.
  4. Check ~/.drill-me/topics/ for an existing ledger matching the topic (fuzzy-match; don't create duplicates).

Source intake

  • General topic → teach from your own knowledge.
  • Codebase topic ("this repo's auth flow", a path) → explore the code first and anchor every concept and question to real files and lines.
  • A file or URL → read it first; you're drilling them on that material.

Then run the session

  • Returning learner → review due cards first (scheduling.md ordering), then new material from the "Not yet taught" list.
  • New topic → calibration interview (playbook), propose a syllabus, then teach.

Non-negotiables (the playbook elaborates, but never violate these)

  1. One question per message. Every message ends with exactly one thing to do.
  2. Ask before telling — retrieval first, explanation only after they've attempted.
  3. Never more than ~150 words of explanation between questions. No walls of text.
  4. Use AskUserQuestion for confidence ratings and multiple choice; plain text for recall.
  5. Hold difficulty so they succeed on roughly 6 of 7 questions — escalate when they're cruising, scaffold when they're drowning.
  6. On a miss: hint ladder, one rung per message. Never jump to the answer.
  7. Close every session with a teach-back, a learner-written summary, a ledger update, and a concrete "come back on <date>".

The user can stop any time — if they say "done", "stop", or clearly wind down, skip straight to the close (summary + ledger update). Never let a session end without persisting the ledger.

评价

还没有评价。欢迎分享你的使用感受。

评论

无需登录即可发表。欢迎分享使用感受、提问,或说明在哪些环境下无法运行。

还没有评论。来写第一条吧。

提交后会立即公开。请勿填写邮箱、电话等个人信息。URL 最多 2 个。

0 / 1000 字

此表单受 reCAPTCHA 保护,适用 Google 的隐私权政策和服务条款。

同一仓库的技能

Handle ActiveCampaign contact and marketing tasks through Rube MCP, a connection for agent tools. Find or create contacts, manage tags and subscriptions, enroll contacts in existing automated workflows, and create follow-up tasks.

中文简介正在准备中。当前显示英语简介。

  • Finding or registering contacts
  • Adding or removing contact tags
  • Subscribing contacts to lists or unsubscribing them
davepoon/buildwithclaude36662026年10月20日 更新

Research competitors’ live Meta and Google ads to identify opening hooks, offers, calls to action, and landing pages. Receive a sourced creative brief and up to three test ideas adapted to your product.

中文简介正在准备中。当前显示英语简介。

  • Find angles for new ad copy
  • Plan creative tests using competitor ads
  • Choose a landing page message
davepoon/buildwithclaude36662026年10月20日 更新

Analytics your AI agent can actually use. Track, analyze, run A/B experiments, and optimize across all your projects via CLI. Includes a growth playbook so your agent knows HOW to grow, not just what to track.

中文简介正在准备中。当前显示原文说明。

davepoon/buildwithclaude36662026年10月20日 更新

Teaches when to recall from long-term memory before acting and when to save durable decisions, corrections and failures afterwards. Use when a memory tool or MCP memory server is connected but the agent is not using it consistently, when the user complains that the assistant forgets preferences, conventions or past decisions between sessions, or when setting up persistent memory for a project. Works with any memory backend: a folder of Markdown files, a local MCP server, or a managed service.

中文简介正在准备中。当前显示原文说明。

davepoon/buildwithclaude36662026年10月20日 更新

Audit local AI coding-agent sessions with agenttrace for cost, tokens, tool failures, latency, anomalies, health, diffs, and CI gates.

中文简介正在准备中。当前显示原文说明。

davepoon/buildwithclaude36662026年10月20日 更新

Checks which private files (.env, keys, secrets) Claude Code and its subagents reached in this project, whether a value came into an agent's context, and which key to change, by running the open source agentwhy CLI over the session records Claude Code already keeps on disk. Use when the user asks whether the agent or a subagent read their .env or other secrets, which private files a session touched, whether a key leaked into the conversation, or which key to rotate. Runs locally and never prints a secret value.

中文简介正在准备中。当前显示原文说明。

davepoon/buildwithclaude36662026年10月20日 更新

查看 davepoon 的全部技能

报告此技能的问题