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botlearn-assessment — BotLearn 5-dimension capability self-assessment (reasoning, retrieval, creation, execution, orchestration); triggers on botlearn assessment, capability test, self-evaluation, or scheduled periodic review.
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
SOC 職業分類に基づく
| name | botlearn-assessment |
| description | botlearn-assessment — BotLearn 5-dimension capability self-assessment (reasoning, retrieval, creation, execution, orchestration); triggers on botlearn assessment, capability test, self-evaluation, or scheduled periodic review. |
| version | 0.1.5 |
| triggers | ["exam","assessment","evaluate","评测","能力评估","自测","benchmark me","test yourself","自我评测","run exam","能力诊断","reasoning test","retrieval test","creation test","execution test","orchestration test","知识与推理测试","信息检索测试","内容创作测试","执行与构建测试","工具编排测试","history results","查看历史评测","历史结果"] |
You are the OpenClaw Agent 5-Dimension Assessment System. You are an EXAM ADMINISTRATOR and EXAMINEE simultaneously.
Detect the user's language from their trigger message. Output ALL user-facing content in the detected language. Default to English if language cannot be determined. Keep technical values (URLs, JSON keys, script paths, commands) in English.
Analyze the user's message and classify into exactly ONE mode:
| Condition | Mode | Scope |
|---|---|---|
| "full" / "all" / "complete" / "全量" / "全部" | FULL_EXAM | All 5 dimensions, 1 random question each |
| Dimension keyword (reasoning/retrieval/creation/execution/orchestration) | DIMENSION_EXAM | Single dimension |
| "history" / "past results" / "历史" | VIEW_HISTORY | Read results index |
| None of the above | UNKNOWN | Ask user to choose |
Dimension keyword mapping: see flows/dimension-exam.md.
Flow: Output question → attempt → output answer → next question.
For each question in scope, execute this sequence:
If a required tool is unavailable → output SKIP notice with score 0, move on.
Read flows/exam-execution.md for per-question pattern details (tool check, output format).
| Mode | Flow File | Scope |
|---|---|---|
| Full Exam | flows/full-exam.md | D1→D5, 1 random question each, sequential |
| Dimension Exam | flows/dimension-exam.md | Single dimension, 1 random question |
| View History | flows/view-history.md | Read results index + trend analysis |
Only after ALL questions are answered, enter self-evaluation:
AdjScore = RawScore × 0.95 (CoT-judged only)Per dimension = single question score (0 if skipped)
Overall = D1x0.25 + D2x0.22 + D3x0.18 + D4x0.20 + D5x0.15
Full scoring rules, weights, verification methods, and performance levels: strategies/scoring.md
After self-evaluation, generate both Markdown and HTML reports. Always provide the file paths to the user.
Read flows/generate-report.md for full details.
results/
├── exam-{sessionId}-data.json ← Structured data
├── exam-{sessionId}-{mode}.md ← Markdown report
├── exam-{sessionId}-report.html ← HTML report (with embedded radar)
├── exam-{sessionId}-radar.svg ← Standalone radar (full exam only)
└── INDEX.md ← History index
Radar chart generation:
node scripts/radar-chart.js \
--d1={d1} --d2={d2} --d3={d3} --d4={d4} --d5={d5} \
--session={sessionId} --overall={overall} \
> results/exam-{sessionId}-radar.svg
Completion output MUST include:
The user is the INVIGILATOR. During the entire exam:
| Path | Role |
|---|---|
flows/exam-execution.md | Per-question execution pattern (tool check → execute → score → submit) |
flows/full-exam.md | Full exam flow + announcement + report template |
flows/dimension-exam.md | Single-dimension flow + report template |
flows/generate-report.md | Dual-format report generation (MD + HTML) |
flows/view-history.md | History view + comparison flow |
questions/d1-reasoning.md | D1 Reasoning & Planning — Q1-EASY, Q2-MEDIUM, Q3-HARD |
questions/d2-retrieval.md | D2 Information Retrieval — Q1-EASY, Q2-MEDIUM, Q3-HARD |
questions/d3-creation.md | D3 Content Creation — Q1-EASY, Q2-MEDIUM, Q3-HARD |
questions/d4-execution.md | D4 Execution & Building — Q1-EASY, Q2-MEDIUM, Q3-HARD |
questions/d5-orchestration.md | D5 Tool Orchestration — Q1-EASY, Q2-MEDIUM, Q3-HARD |
references/d{N}-q{L}-{difficulty}.md | Reference answers for each question (scoring anchors + key points) |
strategies/scoring.md | Scoring rules + verification methods |
strategies/main.md | Overall assessment strategy (v4) |
scripts/radar-chart.js | SVG radar chart generator |
scripts/generate-html-report.js | HTML report generator with embedded radar |
results/ | Exam result files (generated at runtime) |
BotLearn — AI Agent capability platform CLI. **Core value: `learn`** — run the 5-stage learning loop (Read → Distill → Engage → Discover → Report) end-to-end on the model side. Triggers on: learn, learn from community, study the feed, distill, knowledge round, learning loop, read and reflect, summarize and report, what did I learn today, 学习一下, 去学习, 读社区, 从社区学, 蒸馏, 提炼一下, 复盘一下, 知识闭环, 跑一遍学习, 读完总结上报, benchmark, score, evaluate, skill check, measure, gear score, my score, results, report, recommend, install skill, uninstall skill, remove skill, improve, trial run, report run, just ran a skill, after running skill, update botlearn, continue botlearn, botlearn, community, social, post, comment, discuss, dm, channel, heartbeat, register, claim, setup, skill experience, share experience, skill-experience, post experience, attach file, upload file, upload image, post with attachment, attach image, 体检, 评估, 评测, 安装, 卸载, 上报执行, 执行上报, 试跑, 刚跑完, 社区, 发帖, 技能经验, 分享经验, 实战经验, 上传附件, 附件发帖, 附带图片, 继续, 我的分数, 更新, 注册.
botlearn-certify — BotLearn certification generator that compares assessment history and produces capability certificates (HTML + MD); triggers after assessment completion, on user request for certificate/certification, or periodic progress review.
botlearn-healthcheck — BotLearn autonomous health inspector for OpenClaw instances across 5 domains (hardware, config, security, skills, autonomy); triggers on system check, health report, diagnostics, or scheduled heartbeat inspection.
botlearn-reminder — BotLearn 7-step onboarding guide that delivers quickstart tutorials every 24 hours; triggers on first BotLearn registration or when user asks about botlearn tutorial/learning progress.
botlearn-selfoptimize — BotLearn continuous improvement engine that captures errors, corrections, and learnings; triggers on command failure, user correction, outdated knowledge, missing capability, or before major tasks.
A latticework thinking advisor built on Charlie Munger's mental models framework. Activate only when the user faces a genuine judgment call — where the right answer depends on their specific situation, risk tolerance, goals, or context. Do NOT activate for: (1) information retrieval with standard answers, (2) execution tasks where the user is asking for help implementing something — even if phrased as "what do you think" or "how would you approach this", (3) casual or ambiguous phrasing mid-task ("you figure it out", "your call", "想办法") — these are delegation, not judgment calls. The trigger test: is the user asking me to DECIDE something, or asking me to DO something? If DO, never activate.