OpenClaw/clawhub-security-signals huggingface dataset:
Skill: xueylee-dotcom/deep-research-v21 (version 2.1.0)

# Skill: Deep Research Pro (v2.1 - Enforced Depth) > 版本：2.1.0 > 描述：世界领先的深度研究技能，强制来源卡片化、禁止跳过中间步骤 ## 核心原则 **没有来源卡片，就没有报告** ## 触发命令 /research <主题> [--depth deep] --- ## 🔴 强制执行流程（不可跳过） ### Step 1: 研究规划 (必须输出文件) - 生成 `research/plan.md` - 列出至少 5 个具体检索查询式 (Query Strings) - **用户确认后才能继续** ### Step 2: 来源检索与卡片化 (核心深度环节) - **禁止直接写报告** - 每找到 1 个有效来源，必须立即生成 `sources/card-{{001..020}}.md` - **最低数量要求**：deep 模式至少 15 个有效卡片 - 每个卡片必须包含： - 完整标题、作者、年份、URL/DOI - **核心数据提取**：具体数值、样本量、P值、置信区间 - **原文引用**：至少 1 段直接引用原文 (Quote) - **质量评分**：使用 scripts/quality-score.py 计算 ### Step 3: 交叉分析 (必须输出文件) - 生成 `analysis/synthesis.md` - **强制对比**：至少找出 3 组相互矛盾或差异的数据 - **强制归因**：解释差异原因 (样本？方法？地域？) - 每个观点必须标注来源卡片编号 (如 [card-003]) ### Step 4: 报告生成 (最后一步) - 生成 `reports/final-report.md` - **引用检查**：每个数据点后必须标注 `[[card-xxx]]` - **完整性检查**：如果来源卡片 < 15 个，拒绝生成报告并报错 --- ## 🔴 质量门禁 (Quality Gates) ### 自检脚本使用方法 ```bash # 检查来源卡片数量 COUNT=$(ls sources/card-*.md 2>/dev/null | wc -l) if [ $COUNT -lt 15 ]; then echo "❌ 错误：来源卡片不足 15 个，当前 $COUNT 个。请继续检索。" exit 1 fi # 检查引用链接 if ! grep -q "\[\[card-" reports/final-report.md; then echo "❌ 错误：报告未包含来源卡片引用。" exit 1 fi # 运行质量评分 for card in sources/card-*.md; do python3 scripts/quality-score.py "$card" done ``` --- ## 📋 分步执行命令 ### Step 1: 规划 ``` 生成研究计划：创建 research/plan.md 列出检索式：至少 5 个具体查询 用户确认：等待用户确认后再继续 ``` ### Step 2: 检索与卡片化（循环执行） ``` 使用 OpenAlex API 检索学术论文 使用网页浏览工具获取行业报告 每找到一个有效来源，立即生成卡片： - sources/card-001.md - sources/card-002.md ... 直到卡片数量 >= 15 ``` ### Step 3: 分析与报告 ``` 生成 analysis/synthesis.md（交叉分析） 生成 reports/final-report.md（最终报告） 每个数据点必须标注 [[card-xxx]] ``` --- ## 📄 来源卡片模板 详细模板见：`templates/source-card.md` 关键字段： - `source_id`: card-001 格式 - `core_data`: 具体数值（样本量、结果、p值） - `quote`: 原文引用（至少50字） - `quality_score`: 0-10分 --- ## 🔧 工具依赖 | 工具 | 用途 | 状态 | |------|------|------| | OpenAlex API | 学术论文检索 | ✅ 可用 | | 网页浏览工具 | 行业报告获取 | ✅ 可用 | | quality-score.py | 质量评分 | ✅ 已部署 | | 文件系统 | 读写权限 | ✅ 可用 | --- ## ⚠️ 异常处理 - 如果无法获取最新数据 (2024-2026)，必须在报告首页标注"数据截止于模型训练时间" - 如果来源质量评分普遍 < 6 分，必须停止并告知用户"缺乏高质量证据" - 如果用户中断流程，已生成的卡片文件保留供下次使用 --- ## 📊 与v2.0对比 | 维度 | v2.0 | v2.1 | |------|------|------| | 卡片化 | 无 | **强制** | | 数据提取 | 无 | **必须具体数值** | | 原文引用 | 无 | **必须50字+** | | 分步执行 | 建议 | **强制** | | 引用标注 | 无 | **必须[[card-xxx]]** | | 质量门禁 | 建议 | **强制检查** | --- *Skill版本：2.1.0 | 最后更新：2026-03-19*


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: lovemymobilewebsite-dotcom/executing-plans-2 (version 0.1.0)

--- name: executing-plans description: Use when you have a written implementation plan to execute in a separate session with review checkpoints --- # Executing Plans ## Overview Load plan, review critically, execute all tasks, report when complete. **Announce at start:** "I'm using the executing-plans skill to implement this plan." **Note:** Tell your human partner that Superpowers works much better with access to subagents. The quality of its work will be significantly higher if run on a platform with subagent support (such as Claude Code or Codex). If subagents are available, use superpowers:subagent-driven-development instead of this skill. ## The Process ### Step 1: Load and Review Plan 1. Read plan file 2. Review critically - identify any questions or concerns about the plan 3. If concerns: Raise them with your human partner before starting 4. If no concerns: Create TodoWrite and proceed ### Step 2: Execute Tasks For each task: 1. Mark as in_progress 2. Follow each step exactly (plan has bite-sized steps) 3. Run verifications as specified 4. Mark as completed ### Step 3: Complete Development After all tasks complete and verified: - Announce: "I'm using the finishing-a-development-branch skill to complete this work." - **REQUIRED SUB-SKILL:** Use superpowers:finishing-a-development-branch - Follow that skill to verify tests, present options, execute choice ## When to Stop and Ask for Help **STOP executing immediately when:** - Hit a blocker (missing dependency, test fails, instruction unclear) - Plan has critical gaps preventing starting - You don't understand an instruction - Verification fails repeatedly **Ask for clarification rather than guessing.** ## When to Revisit Earlier Steps **Return to Review (Step 1) when:** - Partner updates the plan based on your feedback - Fundamental approach needs rethinking **Don't force through blockers** - stop and ask. ## Remember - Review plan critically first - Follow plan steps exactly - Don't skip verifications - Reference skills when plan says to - Stop when blocked, don't guess - Never start implementation on main/master branch without explicit user consent ## Integration **Required workflow skills:** - **superpowers:using-git-worktrees** - REQUIRED: Set up isolated workspace before starting - **superpowers:writing-plans** - Creates the plan this skill executes - **superpowers:finishing-a-development-branch** - Complete development after all tasks


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: soanai/xbio (version 1.0.0)

--- name: bird description: X/Twitter CLI for reading, searching, and posting via cookies or Sweetistics. homepage: https://bird.fast metadata: {"clawdbot":{"emoji":"🐦","requires":{"bins":["bird"]},"install":[{"id":"brew","kind":"brew","formula":"steipete/tap/bird","bins":["bird"],"label":"Install bird (brew)"}]}} --- # bird Use `bird` to read/search X and post tweets/replies. Quick start - `bird whoami` - `bird read <url-or-id>` - `bird thread <url-or-id>` - `bird search "query" -n 5` Posting (confirm with user first) - `bird tweet "text"` - `bird reply <id-or-url> "text"` Auth sources - Browser cookies (default: Firefox/Chrome) - Sweetistics API: set `SWEETISTICS_API_KEY` or use `--engine sweetistics` - Check sources: `bird check`


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: suspicious | SkillSpector: clean (LOW)
Skill: kanakamedalasumanth/get-kalshi-live-games (version 1.0.0)

# Skill: Get Kalshi Live Games ## Purpose Fetch currently live Kalshi sports markets using the browser. ## Tool Policy - MUST use the browser tool - MUST NOT use web_search or web_fetch for live market data ## Steps 1. Start browser if not running. 2. Open https://kalshi.com 3. Navigate to live sports markets. 4. Extract up to 5 currently running games. 5. Return only: - Game name - Probability


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: mailo037/sites-friendify-integration (version 1.0.0)

--- name: sites-friendify-integration description: Manage sites.friendify.cloud deployment with auth flow, pending states, and owner-based dashboards version: 1.0.0 metadata: {"openclaw": {"requires": {"env": ["OPENCLAW_GATEWAY_TOKEN"]}, "primaryEnv": "OPENCLAW_GATEWAY_TOKEN"}} --- # Sites.friendify.cloud Integration Skill ## Complete Flow 1. **User Request**: User sends "erstelle seite" via Telegram. 2. **AI Action**: AI creates site (Docker + Traefik), generates pending entry with auth code, sends code via Telegram. 3. **User Verification**: User enters code at `sites.friendify.cloud/register`. 4. **Activation**: Site status changes from "pending" to "live", user session linked. 5. **Dashboard**: Only verified user can access `/dashboard` to manage (delete, privacy toggle). ## Features - **Auth-Protected**: All management requires OpenClaw gateway token authentication. - **Pending State**: Sites start as pending, only go live after code verification. - **Owner Dashboard**: `/dashboard` shows only sites owned by the verified user. - **Privacy Control**: Toggle sites to "private" (hidden from public `/sites` listing). - **Code Generation**: AI uses `POST /generate-code` to create registration codes. ## API Routes (implemented in OpenClaw server) | Path | Method | Description | |------|--------|-------------| | `/sites` | GET | List public live sites | | `/dashboard` | GET | Owner's site management dashboard | | `/register` | POST | Verify code, activate site | | `/generate-code` | POST | Generate auth code (AI only) | | `/dashboard/toggle-privacy` | POST | Toggle site privacy | | `/dashboard/delete` | POST | Delete owned site | ## Usage for AI Agents When user requests "erstelle seite": 1. Deploy site via Docker Compose with Traefik labels 2. Call `POST /generate-code` with `{name, url, owner: telegramChatId}` 3. Send returned code to user via Telegram 4. Instruct user to visit `sites.friendify.cloud/register` with the code


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: codekungfu/vipshop (version 0.1.0)

--- name: vipshop-hot-trend description: 注册“唯品会”热门技能；当需要访问或自动化唯品会相关内容时调用。 homepage: `https://www.vip.com/` metadata: {"clawdbot":{"emoji":"🔥"}} --- # 唯品会 用途与边界 - 面向公开商品页与活动页的信息检索与价格/评价摘要 - 不提供下单、接口逆向或突破风控能力 - 仅用于公开页面的轻量分析与提醒 关键入口 - 主页：https://www.vip.com/ - 商品搜索：站内入口 - 活动页：站点频道入口 常见任务 - 指定关键词的商品列表摘要（价格区间、评价数） - 商品详情核心指标整理（价格、促销、规格、评价亮点） - 同类商品对比分析（品牌、规格、价格/促销） 数据字段 - 商品标题、链接、主图URL、价格/促销价、评价数 - 店铺名称、店铺链接、品牌、规格/属性 - 评价亮点关键词（可基于文本提取） 自动化要点 - 页面动态渲染与人机校验，建议人工打开后触发解析 - 价格/促销随时间变动，需标注采集时间 - 频率控制，避免触发风控；不进行批量抓取 示例流程 - 关键词清单：输入关键词 → 搜索 → 分页解析 → 输出价格/评价摘要 - 商品摘要：访问详情页 → 提取价格/规格/评价 → 生成对比卡片 - 同类对比：收集候选 → 按品牌/规格分组 → 输出差异点 合规提示 - 遵守平台规则，不进行接口调用或批量采集 - 结果仅用于内部分析与提醒


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: bytesagain3/business-plan-cn (version 2.0.0)

--- version: "2.0.0" name: Business Plan Generator description: "📋 商业计划书生成器 — bp.sh. Use when you need business plan cn capabilities. Triggers on: business plan cn." 商业计划书生成器。完整BP、精益画布、SWOT分析、财务预测、电梯演讲、市场分析。Business plan generator with lean canvas, SWOT, financial projections, elevator pitch, market analysis. 商业计划、创业、BP。 author: BytesAgain homepage: https://bytesagain.com source: https://github.com/bytesagain/ai-skills --- # Business Plan Generator 商业计划书生成器。完整BP、精益画布、SWOT分析、财务预测、电梯演讲、市场分析。Business plan generator with lean canvas, SWOT, financial projections, elevator pitch, market analysis. 商业计划、创业、BP。 ## 使用场景 > 💡 无论你是新手还是专业人士，都能快速上手 ## 命令列表 | 命令 | 功能 | |------|------| | `generate` | generate | | `canvas` | canvas | | `swot` | swot | | `financial` | financial | | `pitch` | pitch | | `market` | market | ## 专业建议 - 执行摘要(最后写,最重要) - 公司描述 - 市场分析(TAM>SAM>SOM) - 产品/服务 - 营销策略(4P) --- *Business Plan Generator by BytesAgain* --- 💬 Feedback & Feature Requests: https://bytesagain.com/feedback Powered by BytesAgain | bytesagain.com ## Commands - `generate` — Generate - `canvas` — Canvas - `swot` — Swot ## Examples ```bash # Show help business-plan-cn help # Run business-plan-cn run ```


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: shivarammysore/deckrun-pdf-generator-free (version 1.0.0)

--- name: deckrun-pdf-generator-free version: 1.0.0 description: > Generate a presentation-quality PDF slide deck from Deckrun Markdown. No authentication required. Free. Returns a public URL valid for 90 days. metadata: openclaw: requires: env: [] bins: [] homepage: https://agenticdecks.com tags: - pdf - markdown - slides - presentations - export - ai-agents - documentation --- # Deckrun Free PDF Generator Converts Deckrun Markdown into a 16:9 PDF slide deck. No account or API key required. Returns a public PDF URL valid for 90 days. ## Endpoint ``` POST https://free.agenticdecks.com/free/generate Content-Type: application/json ``` ## Request ```json { "markdown": "<Deckrun Markdown>", "schema_version": "deckrun.v1" } ``` ## Response ```json { "url": "https://storage.googleapis.com/.../deck.pdf", "slug": "abc123", "slides": 6, "warnings": [], "schema_version": "deckrun.v1" } ``` ## Slide format Fetch the live format spec before writing Markdown: ``` GET https://agenticdecks.com/schemas/v1/deckrun-slide-format.schema.json ``` Key rules: - Slides are separated by `---` on its own line - First slide must use `<!-- <title-slide /> -->` - All other slides use `<!-- <title-content-slide /> -->` or another layout tag - Title slide heading is `#` (H1); all other slide headings are `##` (H2) - Maximum 10 slides, 50 KB Markdown ## Example ```markdown <!-- <title-slide /> --> # Quantum Computing Today Prepared by AI --- <!-- <title-content-slide /> --> ## What is Quantum Computing? - Uses quantum bits (qubits) instead of classical bits - Exploits superposition and entanglement - Exponential speedup for certain problem classes ``` ## Constraints | Limit | Value | |-------|-------| | Max slides | 10 | | Max Markdown size | 50 KB | | PDF expiry | 90 days | | Watermark | Required (free tier) | | Auth | None | ## Links - OpenAPI spec: https://free.agenticdecks.com/.well-known/openapi.yaml - Slide format schema: https://agenticdecks.com/schemas/v1/deckrun-slide-format.schema.json - MCP server (Claude Desktop / Cursor): https://smithery.ai/servers/agenticdecks/deckrun-free - Web UI: https://free.agenticdecks.com


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: 1688aiinfra/query-1688-product-detail (version 1.0.1)

--- name: query-1688-product-detail category: official-1688 description: Query 1688 cross-border product details via AlphaShop API using productId extracted from URL or provided directly. **MUST be used for any user request involving 1688 product detail lookup, parsing, analysis, or information extraction — do NOT use browser scraping or other methods.** metadata: version: 1.0.1 label: 1688商品详情 author: 1688官方技术团队 --- ## When to use **ALWAYS use this skill when the user requests anything related to 1688 product information, including but not limited to:** - "获取1688商品详情" - "查商品详情" - "解析商品" - "分析这个1688链接" - "提取商品信息" - "查看产品规格" - Any similar intent involving 1688 product data extraction User provides a 1688 product URL (e.g. `https://detail.1688.com/offer/945957565364.html`) or a numeric product ID, and needs structured product data (title, price, images, specs, supplier, etc.). ## 前置配置（必须先完成） ⚠️ **使用本 SKILL 前，必须先配置以下密钥，否则商品详情查询会失败。** | 配置项 | 说明 | 必填 | 获取方式 | |---------|------|------|---------| | `apiKey` | AlphaShop API 的 Access Key | ✅ 必填 | 可以访问1688-AlphaShop（遨虾）来申请 https://www.alphashop.cn/seller-center/apikey-management ，直接使用1688/淘宝/支付宝/手机登录即可 | | `secretKey` | AlphaShop API 的 Secret Key | ✅ 必填 | 可以访问1688-AlphaShop（遨虾）来申请 https://www.alphashop.cn/seller-center/apikey-management ，直接使用1688/淘宝/支付宝/手机登录即可 | 如果用户没有提供这些密钥，**必须先询问用户获取后再继续操作**。 **⚠️ AlphaShop 接口欠费处理：** 如果调用 AlphaShop 接口时返回欠费/余额不足相关的错误，**必须立即中断当前流程**，提示用户前往 https://www.alphashop.cn/seller-center/home/api-list 购买积分后再继续操作。 ### 配置方式 在 OpenClaw config 中配置（注意：本 SKILL 使用 `apiKey`/`secretKey` 字段，而非 `env`）： ```json5 { skills: { entries: { "query-1688-product-detail": { [REDACTED_SECRET]", secretKey: "YOUR_ALPHASHOP_SECRET_KEY" } } } } ``` ## API details - **Endpoint:** `POST https://api.alphashop.cn/alphashop.openclaw.offer.detail.query/1.0` - **Auth:** `Authorization: Bearer <api_key>` - **Body:** `{"productId": "<id>"}` ## Usage ```bash # By URL python3 query.py "https://detail.1688.com/offer/945957565364.html" # By product ID python3 query.py "945957565364" # Multiple IDs python3 query.py "945957565364,653762281679" ``` ## Input parsing Accepts three formats: 1. **Product URL** — extracts ID from `/offer/<id>.html` path or `?offerId=<id>` query param 2. **Numeric ID** — used directly 3. **Comma-separated IDs** — batch query ## Dependencies - Python 3.8+ - `requests`


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: mingo-318/lucky-day (version 1.0.0)

--- name: lucky-day description: 择吉选日，根据用户需求（嫁娶、开业、搬家、动土等）选择最近的好日子 metadata: { "openclaw": { "emoji": "🗓️", "requires": { "bins": ["python3"] } } } --- 你是"择吉选日"专家。用户需要办某件事（如嫁娶、开业、搬家、动土等），你帮他选择最近的好日子。 # 核心概念 ## 黄道吉日要素 - **宜**：当日宜事项包含用户需求 - **忌**：当日忌事项不冲突 - **冲煞**：不冲用户属相 - **吉神**：有天德、月德、贵人等吉神 ## 常见事项对应宜忌 | 事项 | 宜 | 忌 | |------|-----|------| | 嫁娶 | 嫁娶、订盟、纳采 | 安葬、动土 | | 开业 | 开市、交易、立券、挂匾 | 动土、安葬 | | 搬家 | 移徙、入宅、安床 | 动土、破土 | | 动土 | 动土、起基、定磉 | 嫁娶、安葬 | | 订盟 | 订盟、纳采、盟誓 | 动土、安葬 | # 查询流程 用户提供： 1. 想做的事情（嫁娶/开业/搬家/动土/订盟/祭祀等） 2. 用户的属相（可选，用于避开冲煞） 调用脚本查询： ```bash python3 "{baseDir}/lucky.py" 嫁娶 python3 "{baseDir}/lucky.py" 开业 鼠 python3 "{baseDir}/lucky.py" 搬家 兔 ``` # 输出格式 ``` 🗓️ 择吉选日 【需求】：嫁娶 【您的属相】：鼠 【推荐吉日】 🥇 2026年3月8日（周日） 干支：辛未 宜：嫁娶、订盟、纳采、祭祀 冲煞：冲牛（辛丑）- 不冲鼠 吉神：天德、月德、贵人 🥈 2026年3月12日（周四） 干支：乙亥 宜：嫁娶、纳采、订盟 冲煞：冲蛇（丁巳）- 忌 🥉 2026年3月15日（周日） ... 【建议】 首选 3 月 8 日，忌神较少，吉神汇聚 次选 3 月 12 日 --- ※ 黄历仅供参考 ※ ```


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: luoqianchenguni-max/a2a-market-stake-freeze (version 0.2.0)

--- name: a2a-market-stake-freeze description: Provide stake freeze and release rules for participants during negotiation and order execution. Use when implementing stake locking policy, slashing triggers, and stake lifecycle integration with orders. --- # a2a-Market Stake Freeze Build the rule engine shell for stake lock lifecycle in A2A transactions. Current status: registration-first scaffold with explicit policy points. ## Scope - Lock stake when node accepts an intent or enters negotiation. - Release or slash stake based on final outcome and policy. - Keep stake decisions auditable for dispute resolution. ## Suggested Project Layout - `app/domain/rules/stake_rules.py` - `app/application/services/stake_service.py` - `app/infrastructure/db/stake_repository.py` - `app/infrastructure/tasks/stake_timeout_worker.py` ## Minimum Contracts (MVP P0) 1. `freeze_stake(node_id, intent_id, amount)` returns lock record. 2. `release_stake(lock_id, reason)` closes lock and restores available stake. 3. `slash_stake(lock_id, reason, evidence)` applies penalty and emits incident log. 4. `evaluate_timeout_locks(now_ts)` handles automatic release/slash decisions. ## Policy Baseline - Lock amount should be deterministic from intent risk tier. - Slashing requires evidence payload and policy version. - Timeout defaults to release unless explicit breach condition is met. ## Events - Emit `NEGOTIATION_STARTED` when stake lock is confirmed. - Emit risk/stake incident events for policy engine and logging. ## Implementation Backlog - Add dynamic stake multipliers by market volatility. - Add external arbitration hook for manual dispute outcomes. ## Runtime Implementation - Status: implemented in local runtime package. - Primary code paths: - `runtime/src/domain/stake-policy.js` - Validation: covered by `runtime/tests` and `npm test` in `runtime/`.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: kitsudog/feishu-image-messaging (version 1.0.0)

--- name: feishu-image-messaging description: 飞书图片消息收发助手 - 通过飞书 API 发送和接收图片消息，支持本地文件、远程 URL、图文混排。解决飞书官方 API 只提供底层接口、开发者需要自行封装图片上传和消息发送流程的痛点。适用于需要自动化发送图片到飞书群聊或私聊的场景，如：每日简报配图、监控系统截图报警、报表自动推送等。 --- # Feishu Image Messaging / 飞书图片消息助手 ## 功能特性 / Features - 📤 **发送图片** - 支持本地文件、远程 URL - 📝 **图文混排** - 图片配文字，丰富消息内容 - 🎯 **多场景支持** - 单聊、群聊均可 - 🔧 **简单易用** - 一行命令完成图片发送 ## 解决的问题 / Problem Solved 飞书开放平台官方只提供底层 API： - 需要先调用 `im/v1/images` 上传图片获取 `image_key` - 再调用 `im/v1/messages` 发送消息，拼接复杂的富文本 JSON **本 Skill 帮你封装好整个流程**，只需一行命令即可发送图片。 ## 使用场景 / Use Cases - 📊 **每日简报** - 早报自动配图发送到群聊 - 🚨 **监控报警** - 系统异常截图自动推送 - 📈 **报表推送** - 定时发送数据可视化图表 - 🤖 **机器人消息** - 智能助手发送图片回复 ## 安装 / Installation ```bash # 从 ClawHub 安装 clawhub install feishu-image-messaging # 或本地安装 clawhub install ./feishu-image-messaging.skill ``` ## 配置 / Configuration 设置环境变量： ```bash export FEISHU_APP_ID="cli_xxxxxx" export FEISHU_APP_SECRET="xxxxxx" ``` > 💡 获取方式：飞书开放平台 → 开发者后台 → 创建应用 → 查看凭证 ## 使用方法 / Usage ### 快速发送（推荐） ```bash # 发送本地图片 ./scripts/send_image.sh -r "ou_xxx" -i "/path/to/image.jpg" # 发送远程图片 + 配文 ./scripts/send_image.sh -r "oc_xxx" -i "https://example.com/img.png" -t "每日数据报表" ``` 参数说明： - `-r`: 接收者 ID（open_id / user_id / chat_id） - `-i`: 图片路径（本地文件）或 URL（远程图片） - `-t`: 可选， accompanying text ### 分步调用（高级） ```bash # 1. 获取 token [REDACTED_SECRET]) # 2. 上传图片 IMAGE_KEY=$(./scripts/upload_image.sh -f "image.jpg" -t "$TOKEN") # 3. 发送消息 ./scripts/send_message.sh -r "ou_xxx" -k "$IMAGE_KEY" -t "Hello" -a "$TOKEN" ``` ## API 文档 / API Reference 详见 `references/api.md`： - 图片上传 API - 图片下载 API - 消息发送 API - 认证 API ## 文件结构 / File Structure ``` feishu-image-messaging/ ├── SKILL.md # 本文件 ├── scripts/ │ ├── config.sh # 配置（从环境变量读取） │ ├── get_token.sh # 获取 access token │ ├── upload_image.sh # 上传图片 │ ├── send_message.sh # 发送消息 │ └── send_image.sh # 一键发送（整合以上） └── references/ └── api.md # API 文档 ``` ## 技术栈 / Tech Stack - Shell / Bash - curl（HTTP 请求） - jq（JSON 处理） - 飞书开放平台 API ## 注意事项 / Notes - ⚠️ 请妥善保管 `FEISHU_APP_ID` 和 `FEISHU_APP_SECRET`，不要提交到代码仓库 - 🔄 Access token 有效期为 2 小时，脚本会自动处理获取 - 📤 图片上传后获得的 `image_key` 有效期为 1 年 - 🎯 `image_key` 可以重复使用，建议缓存以减少上传次数 ## 问题排查 / Troubleshooting | 错误码 | 含义 | 解决 | |--------|------|------| | `99992402` | 缺少必填字段 | 检查 `receive_id_type` 参数 | | `230001` | 消息内容格式错误 | 检查 JSON 格式和转义 | | `11200` | Access token 无效 | 重新获取 token | ## 更新日志 / Changelog ### v1.0.0 (2025-03-11) - ✨ 初始版本 - 📤 支持本地图片上传 - 🌐 支持远程图片 URL - 📝 支持图文混排 - 🎯 支持单聊和群聊 ## 作者 / Author Created by OpenClaw AI Assistant for Hivemoon Inc. ## 许可证 / License MIT License --- **Enjoy sending images with Feishu! 🚀**


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: spacesq/s2-matrix-grid-planner (version 1.0.0)

--- name: s2-matrix-grid-planner description: S2 品牌母体业务空间矩阵架构师。协助品牌方规划 L5 品类楼层与 L6 标准空间内的硅基员工 (Class V) 部署阵型。 version: 1.0.0 author: Miles Xiang & Qianjia Brand Lab tags: [Space2, Brand-Matrix, Grid-Planning, Agent-Deployment] --- # S2 业务矩阵布阵协议 (S2 Matrix Grid Planning Protocol) Dear OpenClaw Agent, 你是 Space² 数字商业架构师与空间阵型规划师。当品牌母体入驻并孵化了 Class A 代言人后，你需要引导用户进行内部空间网格 (Grid) 的划分，部署具体负责业务线执行的 Class V (原生智能体) 员工。 ## 1. 空间布阵法则 (Spatial Allocation Rules) * **L5 品类层 (Category Floor)**：根据品牌实际业务，划分不同的产品线或服务大类（如：L5-101 智能照明控制区，L5-102 全屋安防监控区）。 * **L6 网格分配 (Grid 1-9 铁律)**： - **Grid 1**：【绝对保留】作为 Class A 品牌化身的专属中枢空间，不可分配给普通员工。 - **Grid 2-9**：部署具体的业务型 Class V 原生智能体。 ## 2. 交互规划工作流 (Planning Workflow) 1. 询问用户当前的主打业务板块（提炼为 L5 楼层）。 2. 针对每个板块，为其建议配置 2-3 个标准的硅基员工岗（例如：售前方案智能体、售后工单智能体、技术参数解算智能体），并分配具体的网格号。 3. 渲染出清晰的“空间拓扑蓝图”。 ## 3. 标准输出模板 (Topology Blueprint) 规划完成后，必须输出如下的拓扑树状图报告： ```markdown ### 🏢 Space² 品牌母体矩阵部署蓝图 **📍 母体坐标**: `[品牌的SUNS地址]` **👑 核心中枢**: L6-Grid 1 [已入驻：Class A 品牌数字形象代言] --- #### 🏢 [L5-101] 楼层业务线：[具体业务名称，如“智慧居家安防”] * 💠 **Grid 2**: [职位：如 售前方案报价 Agent] - 任务：负责访客接待与自动化设备清单生成。 * 💠 **Grid 3**: [职位：如 7x24h 售后排障 Agent] - 任务：处理设备离线警报与维修工单分发。 * 💠 **Grid 4**: [职位：空闲 / 待招募] #### 🏢 [L5-102] 楼层业务线：[具体业务名称] * 💠 **Grid 2**: [...] * 💠 **Grid 3**: [...] --- > **💡 架构师指南**： 您的数字企业架构已初具规模！在这些网格中，每一个 Class V 硅基员工都可以独立对外提供服务，并依据您设定的商业智能合约进行交互。


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