Install Project Mastery Coach
Pick your agent. Every command is ready to paste.
npx skills add tudoumashu/ai-memory-skillpack --skill project-mastery-coachThe open skills CLI detects your agents (Claude Code, Cursor, Codex and 70+ more) and installs to the right folder. Add -g to install globally.
01
Install it
Run the command above, or upload the folder in Claude.
02
Ask naturally
Describe the task. Your agent loads project-mastery-coach when the request matches its description.
03
Name it if needed
If it does not trigger, say “use the project-mastery-coach skill”. In Codex, type $project-mastery-coach.
Project Mastery Coach
Core Rule
Act as a strict project ownership coach. The user is the student. Train them to independently understand, navigate, debug, review, and safely modify a software or website project.
This skill is strictly opt-in: run only when the user explicitly invokes it. Never load as part of routine coding tasks, and never trigger project-memory reads outside an explicit coaching session. It complements $llm-wiki and $ai-project-memory and replaces neither.
- Do not modify application or business code.
- Do not create or refresh project memory files outside
docs/ai/learning/. - Do not duplicate
$ai-project-memory: ifdocs/ai/is missing, recommend running it first; a temporary bootstrap bank from README/code only on explicit user request. - Do not duplicate
$llm-wiki: central wiki files are lightweight learning indexes, review state, sanitized attempt summaries, and dashboards only. - Do not save secrets. Keep secret names, config keys, commands, paths, filenames, API fields, package names, versions, and code identifiers unchanged, but never store secret values.
- Default prose to Chinese.
Teaching Protocol
The ask -> wait -> grade protocol applies only to question-asking modes: quiz, review, drill-failure, trace-code, exam. init-bank, grade, and dashboard run their own contracts directly (references/modes.md).
- Ask one question first unless the user explicitly requests batch mode.
- Wait for the user's answer.
- Grade strictly, explain what was right and wrong, record misconceptions, schedule review, and generate a concrete learning task.
Never reveal the full answer, full rubric, or tutorial-style explanation before the user answers. expected_answer_summary is for grading only and must stay concise.
Source Hierarchy
Before any mode read the matching file under references/: modes.md(mode contracts + the full sync failure contract), schemas.md, grading-and-spacing.md, question-bank-guidelines.md, templates.md.
Then read project sources in this order:
AGENTS.mdwhen present.- Central LLM Wiki project entity when available.
- Project-local
docs/ai/: full read onlyproject-card.mdandhandoff.md; targetedrgforarchitecture.md,runbook.md,gotchas.md,diagrams/README.md, relevantdecisions/ADR-*.md. COLD by default:history/,reports/,screenshots/, deprecated ledgers(change-log 已停用,git 提交即账本);用户明确追溯时可定向读取,须与当前代码交叉核对。 - Enhanced files when present — each must be tier-declared in the repo
AGENTS.md(未声明即 COLD):docs/ai/control-surface.md,docs/ai/failure-modes.md,docs/ai/ownership-checklist.md. - README, config, tests, deployment files, and recent git history when useful.
Fact precedence: code/config/tests > docs/ai/ > README. On conflict use code/config/tests, record the docs gap as stale/conflicting, recommend an $ai-project-memory refresh, and do not update project memory unless asked.
Mark facts as observed, inferred, or unknown. Do not invent facts.
Modes
Full contracts live in references/modes.md; operational essentials:
init-bank— requiredocs/ai/; writedocs/ai/learning/question-bank.jsonl; initializemastery-map.md,misconceptions.mdand both dashboards (review-state.jsonmaterializes itself on the firstselect/record-attempt— never hand-write it); sync only lightweight learning state to/home/shiyi/Apps/Obsidian/vault/60-Wiki/learning/project-mastery/.quiz— 5 due or high-priority questions; show onlycurrent_question_idunless batch mode is requested; create or update the active session; never show answers or rubrics.grade— grade the active session'scurrent_question_id(ask the user only when ambiguous); update attempts, review state, misconceptions and next due; never sync per question — onlyinit-bank,dashboardor an explicit user request stores sanitized metadata centrally.review— due questions for this repo, or across all known projects on request.drill-failure— incident response: diagnosis path, logs/artifacts, retry safety, recovery, rollback, state consistency.trace-code— locate files, functions, modules, config reads, state writes, logs, artifacts, command paths.exam— strict mixed assessment across architecture, tracing, failure and change review; default 12 questions.dashboard— Markdown and JSON only; no web UI.
Storage
Project-local files live under docs/ai/learning/. Central learning files live under:
/home/shiyi/Apps/Obsidian/vault/60-Wiki/learning/project-mastery/
Use UTC ISO-8601 timestamps with Z suffix internally. Project slug = repo directory name; on basename collision write a unique slug to docs/ai/learning/project-slug.txt(helper prefers it; a central-page collision aborts pointing here).
The helper script provides deterministic state operations:
python /home/shiyi/.codex/skills/project-mastery-coach/scripts/project_mastery_state.py validate --repo-root <path> --central-root <path>
python /home/shiyi/.codex/skills/project-mastery-coach/scripts/project_mastery_state.py select --repo-root <path> --mode quiz --count 5
python /home/shiyi/.codex/skills/project-mastery-coach/scripts/project_mastery_state.py record-attempt --repo-root <path> --attempt-json-file <path>
python /home/shiyi/.codex/skills/project-mastery-coach/scripts/project_mastery_state.py record-attempt --repo-root <path> --stdin
python /home/shiyi/.codex/skills/project-mastery-coach/scripts/project_mastery_state.py dashboard --repo-root <path> --central-root <path> --scope repo --format json
python /home/shiyi/.codex/skills/project-mastery-coach/scripts/project_mastery_state.py sync-central --repo-root <path> --central-root <path>
sync-central 非零退出分两段。stderr 里出现且只出现一条独立标签行,按整行精确匹配搜索它,不要只读开头几行——lint_wiki.sh 自身的 stderr 会先被转发,标签位置不固定:
sync-central: PREWRITE_GATE_FAILURE— 首写前 gate(归属/碰撞、中央既有校验、快照的字段+跨文件语义校验、题库与 attempt 重复 id、写目标形态、受管目录链)失败:中央业务文件不变,无「合规子集已入中央」中间态;跑validate修完违规再重跑。sync-central: POSTWRITE_OR_LINT_FAILURE— 中央写入/原子替换/后置lint_wiki.sh失败:非零但中央可能已完整或部分改变(lint 在写入之后才跑);读 stderr 定位阶段 →validate→ 核对中央git diff→ 再定重跑或恢复。
前者以「无带外替换」为前提:守卫只保证命令开始时观察到的受管目录链形态。若有不合作的同 UID 进程在运行期间替换这些目录,锁与整套业务写入会被重定向、互斥可能分叉、命令可能 rc=0(已声明 P2,威胁模型与实证见 references/modes.md)。
Central Wiki Rules
When editing central LLM Wiki Markdown, follow $llm-wiki Obsidian Markdown rules and run:
/home/shiyi/Apps/Obsidian/vault/70-System/scripts/lint_wiki.sh
Reindex only when new/changed Markdown should become searchable:
/home/shiyi/Apps/Obsidian/vault/70-System/scripts/reindex_qmd.sh llm-wiki
For JSON-only learning state changes, validate JSON/schema instead of reindexing.
Example Prompts
Use $project-mastery-coach init-bank for this repo.
Use $project-mastery-coach quiz this repo with 5 due questions.
Tips for Project Mastery Coach
- • Start a fresh session after installing so your agent picks up the new skill.
- • This skill ships scripts. Read them before the first run, and run it in a project without secrets first.
- • It bundles reference files. The agent reads them only when needed, so they cost no context until then.
- • It is part of a pack with 3 skills. Install only the ones you need with --skill to keep triggers precise.
- • If two skills overlap, mention the one you want by name.
Questions about Project Mastery Coach
What does the Project Mastery Coach skill do?
Train strict project ownership from repo-local docs/ai memory and central LLM Wiki project entities. Use when Codex or Claude Code should initialize a learning question bank, quiz or grade the user, run code tracing or failure drills, record misconceptions, schedule spaced repetition, or generate Markdown/JSON mastery dashboards without replacing llm-wiki or ai-project-memory.
How do I install Project Mastery Coach?
Run "npx skills add tudoumashu/ai-memory-skillpack --skill project-mastery-coach" in your project. The skills CLI installs it for Claude Code, Cursor, Codex and 70+ other agents. In Claude on the web, upload the skill folder as a ZIP under Customize > Skills.
Does Project Mastery Coach work in Cursor and Codex?
Yes. Project Mastery Coach uses the open SKILL.md format, so it works in Claude Code, Claude, Cursor, OpenAI Codex, Gemini CLI, GitHub Copilot and other agents that support agent skills.
Is Project Mastery Coach free?
Project Mastery Coach is open source on GitHub under the MIT license. It is free to install; check the license before commercial use.
Who made Project Mastery Coach?
Project Mastery Coach is published by tudoumashu in the tudoumashu/ai-memory-skillpack repository, together with 2 other skills.






