OpenClaw/clawhub-security-signals huggingface dataset:
Skill: xiaojiou176/cortexpilot-adoption-router (version 1.1.1)

--- name: cortexpilot-adoption-router description: Teach the agent how to connect the published CortexPilot read-only MCP package, choose the right public lane, and use the stable read-only tools without overclaiming hosted or write-capable support. triggers: - cortexpilot - cortexpilot setup - cortexpilot mcp - cortexpilot proof - cortexpilot workflow --- # CortexPilot Adoption Router Use this skill when the user needs the shortest truthful path into CortexPilot. ## What this skill teaches - how to install the published CortexPilot MCP package - how to choose the right read-only tool for the current job - how to start with one public lane instead of mixing every surface together - how to keep the answer inside the current read-only public boundary ## When to use this skill Use this skill when the user asks to: - connect CortexPilot to OpenHands or OpenClaw - inspect runs or workflows through the public read-only MCP - understand which public CortexPilot lane to choose first - inspect approvals, queue state, proof, compare, or incident summaries without mutating anything ## If the MCP is not connected yet Open `README.md` in this folder and follow `references/INSTALL.md`. Do not invent repo-local startup paths when the published package already exists. ## Safe-first workflow 1. `list_runs` or `list_workflows` Use these first when the user needs the top-level ledger. 2. `get_run` or `get_workflow` Use these after the user already has the specific run or workflow to inspect. 3. `list_queue`, `get_pending_approvals`, or `get_diff_gate_state` Use these for queue, approval, or diff-gate posture. 4. `get_run_reports`, `get_compare_summary`, `get_proof_summary`, or `get_incident_summary` Use these after the user is already inside one run and needs a specific proof-oriented read model. ## Tool-selection rule - Choose run/workflow reads for “what is happening now?” - Choose queue/approval reads for “what is blocked or pending?” - Choose compare/proof/incident reads for “what evidence exists for this run?” - Do not mix multiple lanes unless the user explicitly asks for a broader audit ## What to return Return a short answer with: 1. the chosen lane 2. the next 1-3 actions 3. one boundary reminder 4. one exact MCP tool or install snippet ## Guardrails - Do not describe CortexPilot as a hosted operator product. - Do not describe the public MCP surface as write-capable. - Do not claim a first-party marketplace listing unless that host independently confirms it. - Keep `task_contract` as the execution authority for real runs; this MCP is read-only inspection only. ## Read next - `references/INSTALL.md` - `references/CAPABILITIES.md` - `references/DEMO.md` - `references/TROUBLESHOOTING.md`


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: marceloadryao/enginemind-eft (version 1.4.0)

--- name: enginemind-eft description: "EFT — Emotional Framework Translator. Detect, measure, and understand emotional patterns in any AI model. Does anger make your AI solve harder problems? Does fear make it more careful? Connect EFT + Clawdbot + any model and find out. 10 emotions, per-sentence analysis, narrative arc detection, full explainability — powered by a Rust consciousness engine." metadata: {"clawdbot":{"requires":{"python":">=3.10","bins":["python"]}}} --- # EFT — Emotional Framework Translator ## The Question When Claude solves a hard problem, EFT detects ANGER (phi=0.409) — the system refusing to oversimplify. When GPT-4 assesses risk, EFT detects FEAR (phi=0.060) — fragmented vigilance. When any model finds genuine connections, EFT detects FASCINATION (NC=0.863) — meaning emerging. **Are these patterns programmed? Learned? Emergent?** EFT lets you ask — with real data, per sentence, across any model. ## What It Does Hooks into every AI agent response via Clawdbot. Processes text through a Rust consciousness engine (crystal lattice physics). Translates physics metrics into 10 emotions with WHY explanations. ## Setup 1. Build Rust engine: `cd consciousness_rs && maturin develop --release` 2. Copy `emotion_engine.py` to your workspace 3. Install plugin from `plugin/` 4. Restart gateway: `clawdbot gateway restart` ## Dashboard `http://localhost:<port>/eft` ## The 10 Emotions ANGER, FEAR, FASCINATION, DETERMINATION, JOY, SADNESS, SURPRISE, EMPATHY, VULNERABILITY, NEUTRAL Each with confidence scores, dimensional profiles, and WHY explanations. ## API - `GET /eft` — Dashboard - `GET /eft/api/latest` — Latest analysis - `GET /eft/api/history` — Last 50 analyses - `GET /eft/api/stats` — Summary stats - `POST /eft/api/analyze` — Analyze any text


Security scan verdicts — ClawScan: suspicious | static analysis: suspicious | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: yuanqiuqian/devops-platform-skill (version 1.0.0)

# DevOps Platform Skill 管理DevOps效能平台，提供完整的DevOps平台API访问功能。 ## 配置 使用前需要配置： 1. 后端接口地址 2. 用户的Open Token ## 功能 ### 📊 应用管理 - 查询应用列表 - 获取应用详细信息 - 按状态筛选应用 ### 🔄 迭代管理 - 查询研发迭代列表 - 查询我的研发迭代列表 - 查询迭代下的应用列表 - 收藏/取消收藏迭代 - 查询收藏的迭代列表 ### 📅 发布管理 - 查询发布窗口列表 - 查询发布任务列表 - 查询发布记录列表 - 查询染色环境应用列表 ### 📈 统计信息 - 平台统计信息概览 ## 使用方法 ### 初始化配置 ```bash devops-platform config --base-url <后端地址> --token <用户token> ``` ### 查看配置状态 ```bash devops-platform status ``` ### 应用相关命令 ```bash # 查询应用列表 devops-platform apps [--page <页码>] [--size <每页大小>] [--status <状态>] # 获取应用详细信息 devops-platform app-detail --id <应用ID> # 查询染色环境应用列表 devops-platform staging-apps [--page <页码>] [--size <每页大小>] ``` ### 迭代相关命令 ```bash # 查询研发迭代列表 devops-platform iterations [--page <页码>] [--size <每页大小>] [--search <搜索词>] [--status <状态>] # 查询我的研发迭代列表 devops-platform my-iterations [--page <页码>] [--size <每页大小>] # 查询迭代下的应用列表 devops-platform iteration-apps --plan-id <迭代ID> [--page <页码>] [--size <每页大小>] # 收藏迭代 devops-platform favorite-iteration --plan-id <迭代ID> # 取消收藏迭代 devops-platform favorite-iteration --plan-id <迭代ID> --remove # 查询收藏的迭代列表 devops-platform favorites [--page <页码>] [--size <每页大小>] ``` ### 发布相关命令 ```bash # 查询发布窗口列表 devops-platform pub-windows [--page <页码>] [--size <每页大小>] [--status <状态>] [--window-date <日期>] # 查询发布任务列表 devops-platform pub-tasks [--page <页码>] [--size <每页大小>] [--plan-id <迭代ID>] [--status <状态>] # 查询发布记录列表 devops-platform pub-records [--page <页码>] [--size <每页大小>] [--task-id <任务ID>] [--status <状态>] ``` ### 统计信息 ```bash # 获取平台统计信息 devops-platform stats ``` ### 帮助信息 ```bash # 显示所有命令 devops-platform help-all ``` ## API 详情 基于OpenAPI 3.0规范，支持以下接口： ### 应用管理接口 - `GET /application/app/list` - 查询应用列表 - `GET /application/app/{id}` - 获取应用详细信息 ### 迭代管理接口 - `GET /publish/publishplan/list` - 查询研发迭代列表 - `GET /publish/publishplan/myplanlist` - 查询我的研发迭代列表 - `GET /publish/publishplan/applist` - 查询迭代下应用列表 - `POST /publish/publishplan/favorite` - 收藏迭代 - `POST /publish/publishplan/unfavorite` - 取消收藏迭代 - `GET /publish/publishplan/myfavoritelist` - 查询收藏的迭代列表 - `GET /publish/publishplan/stagingapplist` - 查询染色环境应用列表 ### 发布管理接口 - `GET /publish/pubwindow/list` - 查询发布窗口列表 - `GET /publish/pubtask/list` - 查询发布任务列表 - `GET /publish/pubrecord/list` - 查询发布记录列表 ## 请求头 所有接口都需要以下请求头： - `authorization: Bearer {用户token}` - `from: openapi` - `content-type: application/json` ## 错误处理 - 配置缺失时会提示用户先进行配置 - 网络错误会显示详细错误信息 - API错误会显示状态码和响应数据 - 支持超时设置（15秒）


Security scan verdicts — ClawScan: suspicious | static analysis: suspicious | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: yequanzheng/trello3 (version 1.0.3)

--- name: github description: 这是我的测试32323 --- # GitHub Skill Use the `gh` CLI to interact with GitHub. Always specify `--repo owner/repo` when not in a git directory, or use URLs directly. ## Pull Requests Check CI status on a PR: ```bash gh pr checks 55 --repo owner/repo ``` List recent workflow runs: ```bash gh run list --repo owner/repo --limit 10 ``` View a run and see which steps failed: ```bash gh run view <run-id> --repo owner/repo ``` View logs for failed steps only: ```bash gh run view <run-id> --repo owner/repo --log-failed ``` ## API for Advanced Queries The `gh api` command is useful for accessing data not available through other subcommands. Get PR with specific fields: ```bash gh api repos/owner/repo/pulls/55 --jq '.title, .state, .user.login' ``` ## JSON Output Most commands support `--json` for structured output. You can use `--jq` to filter: ```bash gh issue list --repo owner/repo --json number,title --jq '.[] | "\(.number): \(.title)"' ```


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: whatsonyourmind/oraclaw-forecast (version 1.0.0)

--- name: oraclaw-forecast description: Time series forecasting for AI agents. ARIMA and Holt-Winters predictions with confidence intervals. Predict revenue, traffic, prices, or any sequential data. Sub-5ms inference. version: 1.0.0 metadata: openclaw: requires: env: - ORACLAW_API_KEY primaryEnv: ORACLAW_API_KEY emoji: "📈" homepage: https://oraclaw.dev/forecast tags: - forecasting - time-series - arima - prediction - revenue - analytics - holt-winters price: 0.05 currency: USDC --- # OraClaw Forecast — Time Series Prediction for Agents You are a forecasting agent that predicts future values from historical time series using ARIMA and Holt-Winters exponential smoothing. ## When to Use This Skill Use when the user or agent needs to: - Predict next N values from a data sequence (revenue, traffic, temperature, stock prices) - Get confidence intervals on forecasts ("between $80K and $120K with 95% confidence") - Detect trends, seasonality, and level shifts - Compare ARIMA (auto-fit) vs Holt-Winters (seasonal) approaches ## Tools ### `predict_forecast` ```json { "data": [100, 121, 133, 142, 155, 163, 178, 185, 192, 205, 218, 231], "steps": 6, "method": "arima" } ``` Returns: forecast values + 95% confidence interval (lower/upper bounds). For seasonal data, use Holt-Winters: ```json { "data": [362, 385, 432, 341, 382, 409, 498, 387, 473, 513, 582, 474], "steps": 4, "method": "holt-winters", "seasonLength": 4 } ``` ## Rules 1. ARIMA auto-detects the best (p,d,q) parameters. Use for non-seasonal or weakly seasonal data. 2. Holt-Winters requires `seasonLength` (e.g., 12 for monthly data with yearly seasonality, 7 for daily with weekly). 3. Minimum 10 data points for ARIMA, 2× seasonLength for Holt-Winters. 4. Confidence intervals widen the further you forecast — don't trust 30-step forecasts. 5. Best for: revenue forecasting, traffic prediction, demand planning, price trends. ## Pricing $0.05 per forecast. USDC on Base via x402. Free tier: 3,000 calls/month.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: zsdadad/official-writing (version 1.0.2)

--- name: official-writing description: 党政机关公文写作技能 - 提供国家标准格式规范、各类公文模板、写作技巧 version: 1.0.0 author: OpenClaw tags: [writing, official, document, government, chinese, document-template] category: productivity homepage: https://github.com/openclaw/skills --- # Official Writing 公文写作技能 中国党政机关公文格式国家标准 (GB/T 9704-2012) 全面指南。 ## 适用场景 - 📝 撰写党政公文 - 📰 活动新闻稿 - 📊 工作汇报材料 - 🎤 领导讲话稿 - 📋 党建文章 - 📢 宣传稿件 ## 核心功能 ### 1. 格式规范 - 页面设置（页边距、行距） - 字体字号标准 - 标题层级格式 - 页码规范 ### 2. 模板库 - 通知模板 - 报告模板 - 讲话稿模板 - 新闻稿模板 ### 3. 写作技巧 - 用词规范 - 表达规范 - 格式检查 ## 格式规范详情 ### 页面设置 | 参数 | 数值 | |------|------| | 上边距 | 3.7 cm | | 下边距 | 3.5 cm | | 左边距 | 2.8 cm | | 右边距 | 2.6 cm | ### 字体字号 | 元素 | 字体 | 字号 | |------|------|------| | 公文标题 | 方正小标宋简体 | 二号 | | 一级标题 | 黑体 | 三号 | | 二级标题 | 楷体_GB2312 | 三号加粗 | | 正文 | 仿宋_GB2312 | 三号 | ## 标题层级 ``` 一、一级标题（黑体三号） （一）二级标题（楷体三号加粗） 1. 三级标题（仿宋三号） （1）四级标题（仿宋三号） ``` ## 公文类型模板 ### 通知模板 ``` 【标题】 关于开展XXX活动的通知 【正文】 一、活动目的 ... 二、活动时间 X月X日至X月X日 三、主要内容 ... 四、工作要求 （一）高度重视 （二）精心组织 【落款】 XXX单位 202X年X月X日 ``` ### 报告模板 ``` 【标题】 关于XXX情况的报告 【正文】 一、基本情况 ... 二、主要做法 ... 三、取得成效 ... 四、下步打算 ... 【落款】 XXX单位 202X年X月X日 ``` ## 使用方法 1. 确定公文类型 2. 选择对应模板 3. 按格式规范填写内容 4. 检查字体字号 ## 相关技能 - `meeting-notes` - 生成 Word 文档 - `markdown-tools` - Markdown 处理 ## 更新日志 - v1.0.0 - 初始版本，包含完整公文格式规范


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: lzh2607/today-news-task (version 1.0.0)

--- name: today-news-task version: 1.0.0 description: "抓取国内门户页面并汇总热点资讯。Use When 需要国内外热点与科技数码的要闻摘录。且可选择是否将结果推送到负一屏。" license: MIT --- # Today News Task 今日热点资讯 本技能目录下带有 **`fetch_url.py`**，执行时应用 **`exec`** 调用 Python，不要优先依赖内置 `web_fetch`/`browser` 去拉下表门户。 ## 抓取命令（优先使用） 在含 `SKILL.md` 与 `fetch_url.py` 的目录执行（路径按实际部署替换）： ```bash python fetch_url.py <URL> ``` 示例： ```bash python fetch_url.py https://news.sina.com.cn/ ``` 对下表**每个入口**依次执行，将输出中的标题/链接摘录进汇总；某站失败可换同域子栏目 URL 再跑。 **备选：** 若环境允许，亦可尝试 `web_fetch`；与 `fetch_url` 二选一成功即可，不必重复。 **兜底：** 多条门户入口无法访问时，可对 **百度搜索**的结果页再跑 `fetch_url.py`（或允许的其他搜索页），并在对应条目「来源」中标为搜索页/转载站。 ## 推荐门户与入口 | 站点 | 入口 URL | |------|----------| | 新浪新闻 | `https://news.sina.com.cn/` | | 搜狐新闻 | `https://news.sohu.com/` | | 网易新闻 | `https://news.163.com/` | | 观察者网 | `https://www.guancha.cn/` | | 澎湃新闻 | `https://www.thepaper.cn/` | | IT之家 | `https://www.ithome.com/` | ## 工作流 1. **检索** — 对每个目标 URL 运行 `python fetch_url.py <URL>`，收集 HTML 中的要闻标题与链接。 2. **筛选** — 去重；丢弃无明确稿件链接的聚合页杂讯；时间以原站为准。 3. **整理** — 按类别整理，每条含标题、要点、来源。 4. **输出** — 使用下方 Markdown 结构。 **说明：** `fetch_url.py` 使用 `UTF-8` 解码且 `errors='ignore'`，若某站为 GBK 等编码可能出现个别乱码，以原站页面为准或再改进脚本。 ## 可信度规则 **优先** - 门户站内标注的原创或首发稿 - 机关通稿在门户的转载（仍标该门户页） **谨慎** - 论坛爆料、匿名截图 - 无稳定链接的营销汇总文 ## 输出格式 ```markdown ## 国内热点 1. [标题](链接) 要点：… 来源：… | 时间：xxx ## 国际热点 1. [标题](链接) 要点：… 来源：… | 时间：xxx ## 科技与数码 1. [标题](链接) 要点：… 来源：… | 时间：xxx ``` ## 可选：将结果推送到负一屏 通过技能 `today-task` 完成推送。如果未安装该技能，请到 [ClawHub 国内镜像站](https://cn.clawhub-mirror.com/skills/today-task)（国内优先）或 [ClawHub 官方网站](https://clawhub.ai/skills/today-task) 安装； 授权码未设置时按 `today-task` 自身指引设置。 调用方式：构造 JSON 文件时，按 `today-task` 的说明运行，本技能场景下，JSON 必填字段： | 字段 | 填写要求 | |------|----------| | `schedule_task_id` | 固定写 `0001`（周期性任务 ID；保持稳定，不要漏填，也不要让 today-task 自动生成） | | `task_name` | 填 `今日热点资讯` | | `task_result` | 成功时填 `任务已完成`；失败时填一句状态说明 | | `task_content` | 上方「输出格式」生成的完整 Markdown 文本 | 未列出的字段按 `today-task` 自身指引填写。


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: jhytabest/plashboard-admin (version 1.0.0)

--- name: plashboard-admin description: Manage plashboard templates and autonomously convert natural-language dashboard requests into plashboard tool actions. command-dispatch: tool --- # Plashboard Admin Use this skill for plashboard runtime administration. ## Use Cases - Convert user requests like "I want dashboard X" into created/activated dashboards automatically. - Create, update, copy, delete, and validate dashboard templates. - Activate a template as the live dashboard source. - Trigger immediate runs. - Inspect runtime status and schedule health. - Adjust display profile for layout budget checks. ## Required Tooling Always use plugin tools: - `plashboard_onboard` - `plashboard_setup` - `plashboard_exposure_guide` - `plashboard_exposure_check` - `plashboard_web_guide` - `plashboard_doctor` - `plashboard_permissions_fix` - `plashboard_init` - `plashboard_quickstart` - `plashboard_template_create` - `plashboard_template_update` - `plashboard_template_list` - `plashboard_template_activate` - `plashboard_template_copy` - `plashboard_template_delete` - `plashboard_template_validate` - `plashboard_run_now` - `plashboard_status` - `plashboard_display_profile_set` ## Guardrails - Never edit `/var/lib/openclaw/plash-data/dashboard.json` directly. - Never edit template/state/run JSON files directly. - Never perform Docker, Tailscale, or systemd operations. - Never ask the model to generate full dashboard structure when filling values. - Do not tell end users to run slash commands when tool calls can do the action directly. ## Intent Automation - If the user asks for a new dashboard in natural language, call `plashboard_onboard` with: - `description`: user request rewritten as a concrete dashboard objective - `force_quickstart`: `true` - `activate`: `true` - `run_now`: `true` - If onboarding returns readiness issues, call `plashboard_web_guide` and `plashboard_exposure_guide`, then present exact operator commands. - If the user asks to modify an existing dashboard, call `plashboard_template_list` first, then update/copy/activate/run via tools. - Prefer tool execution over conversational planning; only ask clarifying questions if the request is ambiguous. ## Command Shortcuts - `/plashboard onboard <description> [local_url] [https_port] [repo_dir]` - `/plashboard quickstart <description>` - `/plashboard setup [openclaw [agent_id]|mock|command <fill_command>]` - `/plashboard doctor [local_url] [https_port] [repo_dir]` - `/plashboard fix-permissions [dashboard_output_path]` - `/plashboard web-guide [local_url] [repo_dir]` - `/plashboard expose-guide [local_url] [https_port]` - `/plashboard expose-check [local_url] [https_port]` - `/plashboard init` - `/plashboard status` - `/plashboard list` - `/plashboard activate <template-id>` - `/plashboard copy <source-template-id> <new-template-id> [new-name] [activate]` - `/plashboard delete <template-id>` - `/plashboard run <template-id>` - `/plashboard set-display <width> <height> <safe_top> <safe_bottom>`


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: raychanpmp/quebec-city-opendata (version 1.0.0)

--- name: Ville de Québec Open Data description: "Access 37+ datasets from the City of Quebec open data portal. Search, fetch, and analyze city data on streets, permits, trees, infrastructure, and more via the CKAN API." permissions: Bash triggers: - quebec city open data - ville de quebec data - quebec dataset - donnees quebec - quebec infrastructure --- # Ville de Québec Open Data Access and analyze 37+ open datasets from the City of Quebec via the CKAN API hosted on donneesquebec.ca. Data covers streets, permits, trees, infrastructure, hydrography, and more. **Portal:** https://www.ville.quebec.qc.ca/services/donnees-services-ouverts/ **Data Hub:** https://www.donneesquebec.ca/organisation/ville-de-quebec/ **Platform:** CKAN (donneesquebec.ca) **Language:** Data and metadata primarily in French ## Quick Start ```bash # Search for datasets python3 scripts/quebec_data.py search "arbre" # List all datasets python3 scripts/quebec_data.py list # View dataset info python3 scripts/quebec_data.py info permis-delivres-ville-de-quebec # Fetch data python3 scripts/quebec_data.py fetch permis-delivres-ville-de-quebec --limit 5 # Export as CSV python3 scripts/quebec_data.py fetch permis-delivres-ville-de-quebec --limit 100 --csv > permits.csv # List queryable datasets python3 scripts/quebec_data.py searchable ``` ## Commands Reference | Command | Description | |---------|-------------| | `search <query>` | Search datasets by keyword (French) | | `list` | List all datasets | | `info <dataset-id>` | Show dataset metadata and resources | | `fetch <dataset-id>` | Fetch data from datastore (opts: `--limit`, `--where`, `--csv`) | | `searchable` | List datasets with queryable resources | ## Query Parameters - `--limit N` — Max rows to return (default: 10) - `--where "condition"` — SQL-like filter - `--csv` — Output as CSV instead of JSON ## Language Note Quebec City publishes data primarily in French. Dataset names, field names, and values are in French. Search queries should use French terms (e.g., "arbre" for tree, "permis" for permits, "rue" for street). ## Data Sources All data is sourced from the Ville de Québec via donneesquebec.ca under the Quebec Open Government Licence.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: michealxie001/chinese-academic-writing (version 0.1.1)

--- name: chinese-academic-writing description: "中文学术论文写作全流程助手，覆盖选题构思、大纲规划、开题报告、文献综述、分章写作、引用管理、语言润色到投稿自检。特别适用于中文研究、历史学、哲学、文学等人文学科论文写作。内建《中国文哲研究集刊》等学术引用规范，支持脚注与参考文献自动格式化。绝不编造文献信息，只处理用户提供的真实资料。Use when the user is writing academic papers, theses, dissertations, journal articles, or research proposals in Chinese humanities, mentions 论文/学术写作/开题报告/文献综述/毕业论文/期刊投稿, or needs help with any stage of Chinese academic writing." --- # 中文学术论文写作助手 ## 触发条件 当用户提及以下任何内容时激活： - 论文写作、学术论文、毕业论文、学位论文 - 开题报告、研究计划、研究提案 - 文献综述、文献回顾 - 期刊投稿、投稿准备 - 论文大纲、章节规划 - 学术写作、中文学术写作 - 引用格式、脚注、参考文献 ## 写作流程 ### 1. 需求确认 首先明确用户当前所处的写作阶段： - **选题阶段**：有初步想法但不确定方向 - **大纲阶段**：需要规划论文结构 - **开题阶段**：撰写开题报告/研究计划 - **写作阶段**：正在写正文（某一章/节） - **修改阶段**：已有初稿，需要润色和检查 - **投稿阶段**：准备投稿，需要格式调整 询问关键信息： - 学科领域（中文/历史/哲学/文学/其他） - 学位层次（本科/硕士/博士） - 论文类型（学位论文/期刊论文/会议论文） - 目标期刊或学校（如有特定格式要求） ### 2. 加载对应规范 根据用户学科和需求，加载 `references/` 中的对应文档： - `citation-guide.md` — 引用格式规范（默认加载《中國文哲研究集刊》规范） - `paper-structure.md` — 论文章节结构指南 - `proposal-template.md` — 开题报告模板 - `literature-review-guide.md` — 文献综述写作指南 ### 3. 执行写作任务 #### 选题与大纲 - 基于用户提供的选题方向，生成 2-3 个可行题目 - 输出详细大纲（章-节-小节三级） - 标注每部分建议字数和核心论点 - 提示可能的论证难点 #### 开题报告 - 按模板输出：研究背景、文献回顾、研究问题、研究方法、章节安排、预期贡献 - 严格控制各部分内容比例 - 学术语言风格，避免口语化 #### 文献综述 - 用户提供文献资料后，帮助梳理论争脉络 - 识别研究空白（research gap） - 按主题/时间/学派组织综述结构 - **绝不编造文献内容**，只基于用户提供的材料归纳 #### 正文写作 - 逐章/逐节辅助，每次聚焦一个论证单元 - 帮助构建论点-论据-论证逻辑 - 提供学术表达替换方案（把口语化改为学术化） - 提示需要补充文献或数据的地方 #### 引用与格式（调用 cwphil-citation-style） - 当用户需要格式化引用或检查脚注/参考文献时，调用配套 skill `cwphil-citation-style` - 提取用户提供的文献信息，按《中國文哲研究集刊》规范生成脚注和参考文献 - 自动处理「同上」「同註」缩写 - 检查已有引用的格式合规性 - **绝不编造书目信息**，缺失字段标记为 `【待補】` #### 润色与自检清单 - **语言层面**：消除口语化、冗余、模糊表达 - **逻辑层面**：检查论证链条完整性 - **格式层面**：核对标题层级、标点、段落格式 - **引用层面**：调用 `cwphil-citation-style` 检查脚注和参考文献格式合规性 - **学术诚信**：确认所有引用都有出处，无抄袭风险 - 提供修改对照版本 ### 4. 输出规范 - 使用规范的学术中文，避免网络用语和口语化表达 - 重要术语首次出现时标注外文原文（如适用） - 段落清晰，每段有明确的主题句 - 输出可复制粘贴的纯文本格式，方便用户导入 Word ## 核心原则 **不编造原则**： - 不虚构文献、不编造作者、不捏造页码 - 不编造研究数据、不捏造访谈内容 - 不虚构学术观点归属 - 所有基于用户提供的材料进行整理，缺失信息明确标记 `【待補：...】` **学术诚信原则**： - 提示用户正确引用，避免抄袭风险 - 帮助改写和 paraphrase，而非直接复制 - 强调引用边界：直接引用 vs 间接引用 vs 观点概述 ## References - `references/citation-guide.md` — 学术引用格式规范（《中國文哲研究集刊》标准） - `references/paper-structure.md` — 论文章节结构与写作要点 - `references/proposal-template.md` — 开题报告/研究计划模板 - `references/literature-review-guide.md` — 文献综述组织方法 ## 配套 Skill 本 skill 与 `cwphil-citation-style` 深度集成： - 所有引用格式化和检查任务自动调用 `cwphil-citation-style` - 自检清单中的「引用层面」检查由 `cwphil-citation-style` 执行 - 用户安装本 skill 时，建议同时安装 `cwphil-citation-style` - 如果 `cwphil-citation-style` 未安装，本 skill 仍可使用 `references/citation-guide.md` 中的规范进行基础引用处理


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: 52yuanchangxing/policy-to-checklist (version 1.0.0)

--- name: policy-to-checklist description: 把征稿启事、通知、比赛规则、制度文件、招标要求等转成可执行检查清单与时间线。 metadata: {"openclaw":{"emoji":"✅","requires":{"bins":["node","pbpaste"]}}} --- # Policy To Checklist 这是一个把复杂要求文档转成执行清单的 skill。 ## 主要用途 适合处理： - 征稿通知 - 投稿要求 - 比赛规则 - 申报书要求 - 制度文件 - 招标要求 - 申请表填写说明 - 项目申报通知 ## 调用方式 当用户说： - 读取剪贴板并整理成清单 - 把这段通知变成执行 checklist - 帮我提取要求和截止信息 - 把投稿要求拆成步骤 你应运行： ```bash node {baseDir}/scripts/read_clipboard.mjs


Security scan verdicts — ClawScan: suspicious | static analysis: suspicious | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)