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Skill 经验进化管理器。在对话结束时分析用户反馈，提取最佳实践和解决方案，持久化到 evolution.json 并缝合到 SKILL.md。支持三层架构（上游层、全局层、项目层）实现跨项目经验管理。当用户说"复盘"、"记录经验"、"保存这个技巧"、"evolve"时使用此工具。
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
Multi-perspective academic paper review with dynamic reviewer personas. Simulates 5 independent reviewers (EIC + 3 peer reviewers + Devil's Advocate) with field-specific expertise. Supports full review, re-review (verification), quick assessment, methodology focus, Socratic guided, and calibration modes. Triggers on: review paper, peer review, manuscript review, referee report, review my paper, critique paper, simulate review, editorial review, calibrate reviewer, reviewer calibration, measure reviewer accuracy.
12-agent academic paper writing pipeline. 10 modes (full/plan/outline/revision/revision-coach/abstract/lit-review/format-convert/citation-check/disclosure). 6 paper types, 5 citation formats, bilingual abstracts, LaTeX/DOCX-via-Pandoc/PDF output. Style Calibration + Writing Quality Check + Anti-Patterns with IRON RULE markers. Triggers: write paper, academic paper, guide my paper, parse reviews, AI disclosure, 寫論文, 學術論文, 引導我寫論文, 審查意見.
Orchestrator for the full academic research pipeline: research -> write -> integrity check -> review -> revise -> re-review -> re-revise -> final integrity check -> finalize. Coordinates deep-research, academic-paper, and academic-paper-reviewer into a seamless 10-stage workflow with mandatory integrity verification, two-stage peer review, and reproducible quality gates. Triggers on: academic pipeline, research to paper, full paper workflow, paper pipeline, end-to-end paper, research-to-publication, complete paper workflow.
Universal deep research agent team. 13-agent pipeline for rigorous academic research on any topic. 7 modes: full research, quick brief, paper review, lit-review, fact-check, Socratic guided research dialogue, and systematic review with optional meta-analysis. Covers research question formulation, Socratic mentoring, methodology design, systematic literature search, source verification, cross-source synthesis, risk of bias assessment, meta-analysis, APA 7.0 report compilation, editorial review, devil's advocate challenges, ethics review, and post-research literature monitoring. Triggers on: research, deep research, literature review, systematic review, meta-analysis, PRISMA, evidence synthesis, fact-check, guide my research, help me think through, 研究, 深度研究, 文獻回顧, 文獻探討, 系統性回顧, 後設分析, 事實查核, 引導我的研究, 幫我釐清, 幫我想想, 我不確定要研究什麼, 研究方向, 研究主題.
Generate or edit images using AI models (FLUX, Nano Banana 2). Use for general-purpose image generation including photos, illustrations, artwork, visual assets, concept art, and any image that is not a technical diagram or schematic. For flowcharts, circuits, pathways, and technical diagrams, use the scientific-schematics skill instead.
Create professional infographics using Nano Banana Pro AI with smart iterative refinement. Uses Gemini 3 Pro for quality review. Integrates research-lookup and web search for accurate data. Supports 10 infographic types, 8 industry styles, and colorblind-safe palettes.
| name | skill-evolution |
| description | Skill 经验进化管理器。在对话结束时分析用户反馈，提取最佳实践和解决方案，持久化到 evolution.json 并缝合到 SKILL.md。支持三层架构（上游层、全局层、项目层）实现跨项目经验管理。当用户说"复盘"、"记录经验"、"保存这个技巧"、"evolve"时使用此工具。 |
Skill 系统的"进化中枢"。负责将对话中的经验教训持久化存储，并跨版本、跨项目保留。
问题: Skill 更新时，用户积累的最佳实践会丢失；不同项目间的经验无法共享。
解决方案:
evolution.json 文件中┌─────────────────────────────────────────────────────────────────────┐
│ 三层经验架构 │
├─────────────────────────────────────────────────────────────────────┤
│ │
│ ┌──────────────────┐ │
│ │ 上游层 (Upstream) │ skills-repo 原始仓库的经验 │
│ │ evolution.json │ 来自社区/原作者的最佳实践 │
│ │ 位置: skills-repo/skills/<skill>/evolution.json │
│ └─────────┬────────┘ │
│ │ 继承 │
│ ▼ │
│ ┌──────────────────┐ │
│ │ 全局层 (Global) │ 你个人的通用经验 │
│ │ evolution.json │ 可选择性提交 PR 到上游 │
│ │ 位置: ~/.claude/evolutions/<skill>/evolution.json │
│ └─────────┬────────┘ │
│ │ 继承 │
│ ▼ │
│ ┌──────────────────┐ │
│ │ 项目层 (Project) │ 项目特定经验 │
│ │ <skill>.json │ 不提交到版本控制 │
│ │ 位置: <project>/.claude/evolutions/<skill>.json │
│ └──────────────────┘ │
│ │
└─────────────────────────────────────────────────────────────────────┘
最终生效的经验 = merge(
上游层, # 最低优先级
全局层, # 中等优先级
项目层 # 最高优先级
)
触发方式:
/skill-evolution 或 /evolveAgent 分析当前对话，识别：
Agent 将提取的经验转换为 JSON 格式：
{
"preferences": [
"用户希望下载时默认静音",
"优先使用 mp4 格式"
],
"fixes": [
"Windows 下路径需要转义",
"某些参数在 v2.0 后已弃用"
],
"contexts": [
"批量操作时需要添加 --batch 参数",
"处理大文件时增加超时时间"
],
"custom_prompts": "在执行前总是先打印预估耗时"
}
Agent 询问用户：
运行 scripts/merge_evolution.py 将经验合并：
# 传统模式（保存到 skill 目录）
python scripts/merge_evolution.py <skill_dir> '<json_string>'
# 分层模式（保存到全局层）
python scripts/merge_evolution.py <skill_name> '<json_string>' --layer global
# 分层模式（保存到项目层）
python scripts/merge_evolution.py <skill_name> '<json_string>' --layer project --project /path/to/project
运行 scripts/smart_stitch.py 将经验写入 SKILL.md：
# 单层模式
python scripts/smart_stitch.py <skill_dir>
# 分层模式（合并三层经验）
python scripts/smart_stitch.py <skill_dir> --layered --project /path/to/project
当 skill-manager 更新 Skill 后，运行全量对齐恢复经验：
python scripts/align_all.py <skills_dir>
| 脚本 | 功能 | 参数 |
|---|---|---|
layered_merge.py | 分层经验管理核心 | <action> <skill_name> [options] |
merge_evolution.py | 增量合并经验 | <skill_dir> <json> [--layer] [--project] |
smart_stitch.py | 缝合到 SKILL.md | <skill_dir> [--layered] [--project] |
align_all.py | 全量对齐 | <skills_dir> [--dry-run] [--backup] |
# 查看经验状态
python scripts/layered_merge.py status <skill_name> [--project <path>]
# 合并三层经验（查看结果）
python scripts/layered_merge.py merge <skill_name> [--project <path>]
# 将项目经验提升到全局层
python scripts/layered_merge.py promote <skill_name> [--project <path>] [--fields f1,f2]
# 从全局层拉取经验到项目层
python scripts/layered_merge.py pull <skill_name> [--project <path>]
# 保存经验到指定层
python scripts/layered_merge.py save <skill_name> <layer> '<json>' [--project <path>]
{
"preferences": ["string"],
"fixes": ["string"],
"contexts": ["string"],
"custom_prompts": "string",
"last_updated": "ISO-8601 datetime",
"last_evolved_hash": "commit hash"
}
| 字段 | 说明 |
|---|---|
preferences | 用户偏好列表 |
fixes | 已知问题修复方案 |
contexts | 特定使用场景说明 |
custom_prompts | 自定义指令注入 |
last_updated | 最后更新时间 |
last_evolved_hash | 最后进化时的 source_hash |
--backup 选项保护重要的经验数据用户: 记录一下，我希望下载视频时默认不带字幕，这个是通用设置
Agent:
1. 识别这是一个用户偏好，且是通用设置
2. 生成 JSON: {"preferences": ["下载视频时默认不带字幕"]}
3. 运行 merge_evolution.py --layer global 合并到全局层
4. 运行 smart_stitch.py --layered 更新 SKILL.md
用户: 这个项目的路径比较特殊，记住要用绝对路径
Agent:
1. 识别这是项目特定的修复方案
2. 生成 JSON: {"fixes": ["此项目必须使用绝对路径"]}
3. 运行 merge_evolution.py --layer project 合并到项目层
用户: 把这个项目里学到的经验提升到全局，其他项目也能用
Agent:
1. 运行 layered_merge.py promote <skill_name>
2. 项目层的经验被复制到全局层
3. 报告提升结果
用户: 这是新项目，把全局经验拉下来
Agent:
1. 运行 layered_merge.py pull <skill_name>
2. 全局层的经验被复制到项目层
3. 可以在此基础上继续积累项目特定经验
evolution_enabled: true）