基于 SOC 职业分类
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt;运行前请先检查来源。
npx skills add https://github.com/TuYv/ccpm --skill understand-onboard命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地?可下载 SkillsMP 当前能够提供的文件。
正在显示 SKILL.md
Use when auditing a paid ad account for incremental contribution, wasted spend, or measurement integrity before scaling; runs a typed 20-item ROAS profile with verified vetoes and a SHIP/FIX/BLOCK/UNDECIDED gate on own exported data. Not for campaign structure design — use campaign-architect; not for creative production — use ad-creative-builder. 付费广告账户审计/ROAS评分
Use when the user asks to "write ad copy", "generate RSA headlines", or "build ad creative at volume"; produces ad units — RSA headlines/descriptions, hooks, and an angle matrix — message-matched to the destination landing page. Not for scoring an ad account — use ad-account-auditor; not for the post-click page — use landing-optimizer; not for organic articles — use content-writer. 广告创意/广告文案/RSA标题
Use when the user asks to "design an A/B test", "set up a creative/landing test", "run an incrementality test", or "is this result statistically and practically material?"; produces a hypothesis, variant matrix, sample-size/duration/power plan, and a documented effect/uncertainty read from own exported results. It applies only a precommitted owner-approved action rule; the statistical helper never chooses a business action. Not for producing variants — use ad-creative-builder; not for reading back one shipped change — use paid-measurement-loop. 广告AB测试设计/实验设计/显著性判定/增效测试
| name | understand-onboard |
| description | Use when you need to generate an onboarding guide for new team members joining a project |
Generate a comprehensive onboarding guide from the project's knowledge graph.
The knowledge graph JSON has this structure:
project — {name, description, languages, frameworks, analyzedAt, gitCommitHash}nodes[] — each has {id, type, name, filePath?, summary, tags[], complexity, languageNotes?}
file:path, function:path:name, config:path, article:pathedges[] — each has {source, target, type, direction, weight}
layers[] — each has {id, name, description, nodeIds[]}tour[] — each has {order, title, description, nodeIds[]}Resolve the data directory $UA_DIR. Run UA_DIR=$([ -d .understand-anything ] && echo .understand-anything || echo .ua) — this is the legacy .understand-anything/ when it already exists, otherwise the new .ua/. Check that $UA_DIR/knowledge-graph.json exists. If not, tell the user to run /understand first.
Check graph freshness before using graph-derived context:
project.gitCommitHash from the graph metadata as GRAPH_COMMIT_RAW. Resolve it as a commit before using it in any Git diff, then compare it with git rev-parse HEAD and inspect project-scoped committed and working-tree changes from the project root:
GRAPH_COMMIT=$(git rev-parse --verify --end-of-options "${GRAPH_COMMIT_RAW}^{commit}" 2>/dev/null)
git rev-parse HEAD
git diff --name-only "$GRAPH_COMMIT" HEAD -- .
git diff --cached --name-only -- .
git diff --name-only -- .
git ls-files --others --exclude-standard -- .
-- . pathspec is required: commits that only touch a sibling monorepo project must not make this graph stale. A hash mismatch alone is not stale when the project diff is empty..ua/ or legacy .understand-anything/) in every command's output because it contains generated graph artifacts, not project source drift./understand to refresh the graph.GRAPH_COMMIT_RAW resolves successfully. If the graph commit or Git metadata is missing, invalid, or unavailable, give a brief best-effort warning and continue instead of blocking.Read project metadata — use Grep or Read with a line limit to extract the "project" section (name, description, languages, frameworks).
Read layers — Grep for "layers" to get the full layers array. These define the architecture and will structure the guide.
Read the tour — Grep for "tour" to get the guided walkthrough steps. These provide the recommended learning path.
Read file-level structural nodes only — use Grep to find nodes with file-level types (file, config, document, service, pipeline, table, schema, resource, endpoint) in the knowledge graph. Skip function-level and class-level nodes to keep the guide high-level. Extract each node's name, filePath, summary, and complexity.
Identify complexity hotspots — from the file-level nodes, find those with the highest complexity values. These are areas new developers should approach carefully.
Generate the onboarding guide with these sections:
Format as clean markdown
Offer to save the guide to docs/UA_ONBOARDING.md in the project
Suggest the user commit it to the repo for the team