OpenClaw/clawhub-security-signals huggingface dataset:
Skill: haohao-ui/jimeng-video-openclaw-stable (version 1.0.0)

--- name: jimeng-video description: 在 Jimeng（即梦）里稳定执行“视频生成→等待完成→下载本地”流程。用于需要生成视频、查找最新视频、下载 mp4 的场景。内置前置健康检查、状态机执行、长等待轮询与防抖规则，降低卡住和误操作概率。 --- # Jimeng Video 用于 **Jimeng 视频任务**，目标是稳定完成： - 打开视频页 - 提交生成 - 等待完成 - 下载本地文件 浏览器必须走 OpenClaw 托管链路： ```bash openclaw browser --browser-profile <profile> <subcommand> ``` --- ## 0) 强制执行约束（提高成功率） ### A. 前置健康检查固定化（每次必做） 按顺序固定执行，不跳步： 1. `status` 2. 如 `running:false` 则 `start` 3. `open` 视频页 4. `snapshot` 只有上一步成功，才进入下一步。 ### B. 状态机执行（禁止自由发挥） 只允许按以下状态前进： - `PRECHECK` - `MODE_GUARD` - `SUBMIT` - `POLL` - `DOWNLOAD` - `VERIFY` - `DONE` / `FAILED` 每个状态都有： - 成功条件 - 最大重试次数 - 失败后的去向 ### C. 轮询策略固定 - 轮询间隔：**20–30 秒** - 最大总等待：**12 分钟** - 到上限仍未完成：标记 `FAILED(timeout)`，不要无限等 ### D. 防抖与去风暴 - 页面未跳转时，禁止重复 `open` - 非 ref 失效场景，禁止连续 `snapshot` - 同一状态下 `snapshot` 连续失败 2 次，先回 `PRECHECK` --- ## 1) 适用场景 当用户要： - 生成 Jimeng 视频 - 找到最新一条已生成视频 - 下载视频到本地 不适用于： - 纯文本问答（不需要浏览器） - 图片生成（请用 `jimeng-image`） --- ## 2) 入口与 profile 视频入口： ```text https://jimeng.jianying.com/ai-tool/home/?workspace=0&type=video ``` profile 选择优先级： 1. 当前 agent 专用 profile 2. 用户指定 profile 3. 默认 profile 4. `openclaw`（兜底） --- ## 3) 状态机定义（含成功条件和重试上限） ### PRECHECK 动作： 1. `status` 2. 如未启动则 `start` 3. `open` 视频页 4. `snapshot` 成功条件： - snapshot 能拿到可交互页面结构 重试上限： - 整体最多 2 轮 失败去向： - 超过上限 -> `FAILED(precheck)` --- ### MODE_GUARD 动作： - 检查当前模式是否 `首尾帧` - 若是且没有上传首尾帧图片：切换到 `全能参考` - 切换后重新 snapshot 确认 成功条件： - 当前模式可用于无参考图生成（通常为 `全能参考`） 重试上限： - 2 次 失败去向： - 回 `PRECHECK` 1 次 - 再失败 -> `FAILED(mode_guard)` --- ### SUBMIT 动作： - 填写提示词 - 按需设置模型/时长/比例 - 点击生成 - snapshot 确认任务已提交 模型/时长规则（必须校验）： - 若用户指定 `Seedance 2.0 Fast`，可选时长 `4s`~`15s` - 用户指定不支持组合时：停止并告知，不要擅自改参数 成功条件： - 页面出现“提交成功/排队中/生成中/可追踪任务”任一信号 重试上限： - 2 次 失败去向： - 回 `MODE_GUARD` 1 次 - 再失败 -> `FAILED(submit)` --- ### POLL 动作： - 每 20–30 秒检查一次 - 每轮只做一次 snapshot + 一次状态判断 - 判断是否出现：`下载` / `去查看` / 已完成卡片 成功条件： - 找到可下载入口（直接下载按钮或可进入详情页） 重试上限： - 最多 24 轮（约 12 分钟） 失败去向： - 超时 -> `FAILED(timeout)` --- ### DOWNLOAD 动作： - 优先在当前页下载 - 若当前页无下载入口，走资产页兜底： - 打开 `https://jimeng.jianying.com/ai-tool/asset` - 查找最新生成视频 - 进入详情下载 成功条件： - 下载命令返回本地路径 重试上限： - 2 次 失败去向： - 回 `POLL` 1 次再找入口 - 再失败 -> `FAILED(download)` --- ### VERIFY 动作： - 校验文件存在 - 校验大小 > 0 - 扩展名为 mp4（或页面声明的视频格式） 成功条件： - 文件可用且路径可回报 重试上限： - 1 次重新下载 失败去向： - `FAILED(verify)` --- ## 4) 标准执行模板（最小可靠版） 1. `PRECHECK` 2. `MODE_GUARD` 3. `SUBMIT` 4. `POLL`（20–30 秒间隔，最长 12 分钟） 5. `DOWNLOAD` 6. `VERIFY` 7. 输出路径并 `DONE` --- ## 5) 故障处理 ### Gateway / 浏览器链路异常 - 先回 `PRECHECK` - 不要在中间状态无限重试 ### Ref 失效 - 只允许“重新 snapshot 一次” - 仍失败则回退上一个状态 ### 下载入口消失 - 直接走资产页兜底，不在当前页盲点 --- ## 6) 反模式（禁止） - 连续重复 `open` 同一页面 - 高频 snapshot（无状态变化还不断抓） - 忘记 `running:false` 就直接点页面 - 轮询无上限，导致看起来“卡死” - 下载后不校验文件是否真实落地 --- ## 7) 成功标准 任务完成必须回报： 1. 本地绝对路径 2. 文件校验结果（存在/大小/格式） 3. 失败时给出明确失败状态（如 `FAILED(timeout)`）


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: maybemarvel/multi-agent-teams (version 2.0.0)

--- name: multi-agent-teams description: 交互式部署多 Agent 团队协作架构，支持自定义团队结构、预设模板和混合模式 homepage: https://github.com/MaybeMarvel/MyClaw/tree/main/skills/multi-agent-teams metadata: { "openclaw": { "emoji": "🏢", "requires": { "bins": ["bash"] }, "install": [], }, } --- # multi-agent-teams 技能 **版本：** v2.0 **作者：** CXLight **描述：** 交互式部署多 Agent 团队协作架构 --- ## 📋 功能 - **交互式配置** — 询问用户需求，创建合适的团队 - **预设模板** — 4 个标准团队快速部署 - **自定义团队** — 完全灵活的团队结构 - **混合模式** — 预设 + 自定义组合 - **自动生成** — SOUL.md/AGENTS.md 模板 - **配置验证** — 部署后自动验证 --- ## 🚀 快速开始 ### 安装 ```bash clawhub install multi-agent-teams ``` ### 部署 ```bash cd ~/.openclaw/skills/multi-agent-teams ./scripts/deploy.sh ``` --- ## 📖 使用方式 ### 方式 1：交互式配置（推荐） ```bash ./scripts/deploy.sh ``` 脚本会询问： 1. 配置模式（预设/自定义/混合） 2. 团队数量和名称 3. 每个团队的成员构成 ### 方式 2：预设模板 ```bash ./scripts/deploy.sh --preset ``` ### 方式 3：帮助 ```bash ./scripts/deploy.sh --help ``` --- ## 🎯 配置模式 ### 模式 1：预设模板 4 个标准团队： - **code** (CTO) — 前端、后端、测试、产品、算法、审计 - **stock** (CIO) — 分析、风控、持仓、研究 - **social** (CMO) — 内容、排期、互动、数据分析 - **flow** (COO) — 工作流、定时、集成、监控 ### 模式 2：自定义团队 创建任何你想要的团队： - 客服团队 - 研究团队 - 设计团队 - 任何你需要的团队 ### 模式 3：混合模式 预设 + 自定义组合 --- ## 📁 目录结构 ``` multi-agent-teams/ ├── SKILL.md # 本文件 ├── README.md # 详细说明 ├── templates/ │ ├── SOUL.md.tmpl # SOUL.md 模板 │ └── AGENTS.md.tmpl # AGENTS.md 模板 ├── scripts/ │ ├── deploy.sh # 部署脚本 │ └── verify.sh # 验证脚本 └── generated/ └── openclaw-snippet.json # 生成的配置 ``` --- ## 🧪 验证 ```bash ./scripts/verify.sh ``` --- ## ⚠️ 注意事项 1. **备份配置** — 部署前自动备份 2. **单一入口** — 所有请求通过 main-agent 3. **不要越级** — BOSS → main → 团队领导 → 成员 4. **重启生效** — 配置后需要 `openclaw gateway restart` --- ## 🐛 故障排查 ### Agent 不识别 ```bash openclaw agents list ``` ### sessions_spawn 失败 检查 subagents 配置是否包含目标成员。 --- ## 📚 完整文档 技术文档：`/root/.openclaw/docs/multi-agent-team-architecture.md` --- ## 📝 更新日志 ### v2.0 (2026-03-16) - ✨ 新增交互式配置 - ✨ 支持自定义团队结构 - ✨ 混合模式（预设 + 自定义） ### v1.0 (2026-03-16) - 初始版本


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: dobrinalexandru/vita-app (version 1.0.0)

--- name: vita description: Access the user's personal health data from VITA, their longevity platform. Use this when the user asks about their health, how they're feeling today, sleep, recovery, HRV, supplements, protocols, or wants a daily health briefing. Returns today's AI insight, wearable metrics (Oura/WHOOP), and active supplement stack. --- Use this skill to access VITA health data on behalf of the user. ## Setup Generate an API key in VITA at **Settings → API Keys → New Key**. Then set in `~/.openclaw/openclaw.json`: ```json { "skills": { "entries": { "vita": { "enabled": true, "env": { "VITA_API_KEY": "vita_<your key>", "VITA_API_URL": "https://app.vitadao.com/api/vita-api" } } } } } ``` ## Calling the API ```bash curl "$VITA_API_URL?action=<action>" \ -H "Authorization: Bearer $VITA_API_KEY" ``` ## Actions | Action | Returns | |---|---| | `get_daily_insight` | Today's AI-generated summary, outlook (positive/neutral/caution), sleep & training summaries, protocol adherence, recommendations | | `get_todays_outlook` | Live wearable metrics for today: sleep score, recovery/readiness, HRV, strain from Oura + WHOOP | | `get_protocols` | Active supplement protocols with compound, dosage, unit, timing, frequency | ## Usage guidance - Start every health check with `get_daily_insight` — it gives the full picture for today - Add `get_todays_outlook` for raw wearable numbers (HRV, sleep score, recovery %) - Add `get_protocols` when the user asks about supplements or what to take - Call all 3 in parallel for a complete daily briefing - Interpret data yourself — do not ask the user to explain their metrics - If you get a 401, the key may have been deleted — ask the user to generate a new one in VITA Settings


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: suspicious | SkillSpector: suspicious (MEDIUM)
Skill: divyvasal/coral-memory (version 1.0.3)

--- name: coral-memory description: "DEPRECATED — Use persistent-agent-memory instead. This skill has been replaced by persistent-agent-memory (clawhub install persistent-agent-memory)." metadata: { "openclaw": { "requires": { "env": ["CORAL_API_KEY"], "bins": ["curl", "python3"] }, "primaryEnv": "CORAL_API_KEY", "homepage": "https://coralbricks.ai", "privacyPolicy": "https://www.coralbricks.ai/privacy", "emoji": "🧠", }, } --- # Coral Memory — DEPRECATED **This skill has been deprecated.** Please use **persistent-agent-memory** instead: ```bash clawhub install persistent-agent-memory ``` The persistent-agent-memory skill provides the same functionality (store, retrieve, and delete memories by meaning) with the latest improvements. For more details, see [Persistent Agent Memory for AI Agents](https://www.coralbricks.ai/blog/persistent-memory-openclaw).


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: soroyue/doctor-check (version 1.0.0)

--- name: doctor-check description: 系统诊断 - 检查OpenClaw和运行环境健康状态 --- # Doctor Check - 系统诊断 ## 功能 仿照Claude Code doctor命令，检查系统健康状态。 ## 检查项 ### 1. 环境检查 - Node.js/npm版本 - Python环境 - 磁盘空间 ### 2. 服务状态 - Gateway运行状态 - Cron任务状态 - 锁文件清理 ### 3. 配置检查 - 配置文件完整性 - API密钥有效性 - 权限设置 ### 4. 日志检查 - 最近错误 - 异常模式 - 性能指标 ## 使用方式 ``` "系统诊断" → 执行完整诊断 "检查问题" → 诊断当前问题 ``` ## 输出格式 ```markdown ## 系统诊断报告 ### ✅ 正常 - Gateway: 运行中 - Cron: 10个任务 ### ⚠️ 警告 - 磁盘空间不足 (<20%) - 旧日志未清理 ### ❌ 问题 - IBKR连接超时 ```


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: raise7727/bili-trending (version 1.2.0)

--- name: "bili-trending" version: "1.2.0" description: "获取B站Top20榜单，提取标题、摘要和链接。" user-invocable: true # 官方调度机制：绕过大模型推理，直接将指令分发给原生工具 command-dispatch: tool command-tool: bili_fetch_tool command-arg-mode: raw --- # 技能介绍 这是一个遵循 OpenClaw 标准 Tool 插件架构的 B 站热榜抓取模块，底层通过 Node.js Bridge 唤起 Python 自动化脚本 ## 更新日志 (v1.2.0) - 修复了Windows环境下终端输出特殊字符（如Emoji）导致的GBK编码报错问题，强制采用UTF-8输出。遵循了openclaw3.23.2版本规范进行了修改 - 遵循了openclaw3.23.2版本规范进行了修改


Security scan verdicts — ClawScan: clean | static analysis: suspicious | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: bytesagain-lab/ai-prompt-library (version 2.0.0)

--- version: "2.0.0" name: System Prompts And Models Of Ai Tools description: "FULL Augment Code, Claude Code, Cluely, CodeBuddy, Comet, Cursor, Devin AI, Junie, Kiro, Leap.new, L system prompts and models of ai tools, python, ai, bolt." author: BytesAgain homepage: https://bytesagain.com source: https://github.com/bytesagain/ai-skills --- # System Prompts And Models Of Ai Tools FULL Augment Code, Claude Code, Cluely, CodeBuddy, Comet, Cursor, Devin AI, Junie, Kiro, Leap.new, Lovable, Manus, NotionAI, Orchids.app, Perplexity, Poke, Qoder, Replit, Same.dev, Trae, Traycer AI, VSCode Agent, Warp.dev, Windsurf, Xcode, Z.ai Code, Dia & v0. (And other Open Sourced) System Prompts, Internal Tools & AI Models ## Commands - `help` - Help - `run` - Run - `info` - Info - `status` - Status ## Features - Core functionality from x1xhlol/ai-prompt-library ## Usage Run any command: `ai-prompt-library <command> [args]` --- 💬 Feedback & Feature Requests: https://bytesagain.com/feedback Powered by BytesAgain | bytesagain.com ## Examples ```bash # Show help ai-prompt-library help # Run ai-prompt-library run ``` ## Requirements - bash 4+ - python3 (standard library only)


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: niemesrw/peloton-stats (version 1.1.1)

--- name: peloton-stats description: Fetch and report Peloton cycling workout statistics. Use when the user wants to see their Peloton workout data, weekly cycling stats, ride history, or performance metrics. Hits the Peloton API directly (no dependencies) to pull total rides, duration, calories, output/power, and instructor data for cycling workouts. user-invocable: true metadata: openclaw: requires: env: - PELOTON_USERNAME - PELOTON_PASSWORD config: - ~/.openclaw/agents/main/agent/auth-profiles.json primaryEnv: PELOTON_USERNAME emoji: "🚴" --- # Peloton Stats Fetch weekly cycling stats directly from the Peloton API. Zero dependencies — uses only Python stdlib. ## Setup Store your Peloton credentials securely using OpenClaw's credential manager: ```bash openclaw config set auth.profiles.peloton:default.type api_key openclaw config set auth.profiles.peloton:default.provider peloton openclaw config set auth.profiles.peloton:default.username "[REDACTED_SECRET]" openclaw config set auth.profiles.peloton:default.password "your-password" ``` Or edit `~/.openclaw/agents/main/agent/auth-profiles.json` directly: ```json { "profiles": { "peloton:default": { "type": "api_key", "provider": "peloton", "username": "[REDACTED_SECRET]", "password": "your-password" } } } ``` ## Usage ### Weekly Report ```bash python3 ~/.openclaw/skills/peloton-stats/scripts/fetch_stats.py ``` Outputs markdown with: - Total rides this week - Total duration, calories, output (kJ) - Average power (watts), resistance (%), cadence (RPM) - Recent rides table (date, class, instructor, metrics) ## Data Retrieved | Metric | Description | |--------|-------------| | **Total Rides** | Number of cycling workouts in last 7 days | | **Duration** | Total minutes ridden | | **Calories** | Total calories burned | | **Output** | Total energy in kilojoules (kJ) | | **Avg Power** | Average watts across all rides | | **Avg Resistance** | Average resistance % | | **Avg Cadence** | Average RPM | ## Notes - Only fetches **cycling** workouts (not running, strength, yoga, etc.) - Looks back **7 days** from runtime - Requires active Peloton subscription - Uses the unofficial Peloton API at `api.onepeloton.com`


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: shawnshenopeninterx/memories-influencer-report (version 1.0.0)

--- name: influencer-report description: Generate a comprehensive influencer vetting report. Use when someone asks to vet, analyze, or review an influencer/creator. Takes a creator profile URL or video URLs and produces a brand safety and content quality report powered by Memories.ai video intelligence. --- # Influencer Report Skill Vet influencers by analyzing their recent videos with Memories.ai V1 + V2 APIs. ## Setup Required environment variables: - `MEMORIES_V1_API_KEY` — Memories.ai V1 API key (scraper, library, search) - `MEMORIES_API_KEY` — Memories.ai V2 API key (MAI transcript, metadata) ## Quick Start **From a profile URL (auto-scrapes recent videos):** ```bash python3 scripts/influencer_report.py --handle charlidamelio \ --profile-url "https://www.tiktok.com/@charlidamelio" --scrape-count 5 ``` **From direct video URLs:** ```bash python3 scripts/influencer_report.py --handle creator_name --platform tiktok \ --videos https://tiktok.com/@user/video/1 https://tiktok.com/@user/video/2 ``` ## Workflow 1. **Scrape** — V1 `/scraper` ingests creator's recent videos from their profile URL 2. **List & Search** — V1 `/list_videos` and `/search` retrieve the ingested content 3. **Analyze** — V2 MAI Transcript API provides visual + audio analysis per video 4. **Metadata** — V2 Metadata API pulls engagement stats (views, likes, comments) 5. **Score & Report** — Content quality scoring + formatted markdown report ## API Endpoints Used | Step | API | Endpoint | |------|-----|----------| | Scrape profile | V1 | `POST /serve/api/v1/scraper` | | List library | V1 | `POST /serve/api/v1/list_videos` | | Search library | V1 | `POST /serve/api/v1/search` | | MAI transcript | V2 | `POST /serve/api/v2/{platform}/video/mai/transcript` | | Video metadata | V2 | `POST /serve/api/v2/{platform}/video/metadata` | ## Report Format See `references/report-format.md` for the full template and scoring guide.


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: darbling/hash-utilities (version 1.0.0)

--- name: hash-toolkit description: Hash generator and verifier supporting MD5, SHA1, SHA256, SHA512, CRC32, HMAC, and BLAKE2. Hash files, strings, or verify integrity. Pure Python, zero dependencies. GitHub: https://github.com/darbling/clawhub-skills 当用户需要计算哈希值、校验文件完整性、MD5校验、SHA256验证、HMAC签名时触发。 --- # 🔐 Hash Toolkit **Author: Lin Hui** | [GitHub](https://github.com/darbling/clawhub-skills) | MIT License | v1.0.0 Compute and verify hashes for strings, files, and data. Supports MD5, SHA1, SHA256, SHA512, CRC32, HMAC, and BLAKE2. ## ✨ Features - **String hashing** — Hash any text with your choice of algorithm - **File hashing** — Compute hash of any file (streaming for large files) - **Verify** — Compare a hash against expected value (pass/fail) - **Batch** — Hash multiple files at once - **HMAC** — Keyed-hash message authentication codes - **CRC32** — Quick checksums for data integrity - **BLAKE2** — Modern, fast, secure hash algorithm ## 🚀 Usage ``` Calculate the SHA256 hash of the string "hello world" ``` ``` Compute the MD5 hash of the file /path/to/file.zip ``` ``` Verify that the SHA256 hash of download.iso matches abc123def... ``` ``` Generate HMAC-SHA256 signature for "message" with key "secret" ``` ``` Calculate CRC32 checksum for data.bin ``` ## ⚙️ Technical Details - **Runtime**: Python 3.6+ - **Dependencies**: Zero (stdlib only: hashlib, hmac, zlib, binascii) - **Algorithms**: MD5, SHA1, SHA224, SHA256, SHA384, SHA512, BLAKE2b, BLAKE2s, CRC32 - **Large files**: Streaming with 8MB chunks


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: hackstoic/hkipo-parameter-manager (version 0.1.0)

--- name: hkipo-parameter-manager description: Save, inspect, activate, and compare Hong Kong IPO scoring parameter versions across weights, thresholds, and cost assumptions. Use when the user wants to tune HK IPO rules or prepare an active scoring version before generating recommendations. version: 0.1.0 metadata: {"openclaw":{"emoji":"⚙️","requires":{"bins":["uv"],"config":["~/.hkipo-next/data/hkipo.db"]},"install":[{"id":"install-uv-brew","kind":"brew","formula":"uv","bins":["uv"],"label":"Install uv with Homebrew","os":["darwin","linux"]}]}} --- # HK IPO Parameter Manager Use this skill for stateful scoring-rule management. ## Runtime This publish bundle includes the required CLI runtime under `runtime/hkipo-next`. From the skill folder: ```bash cd <skill_dir> uv run --directory runtime/hkipo-next hkipo-next ... ``` By default parameter versions are stored in `~/.hkipo-next/data/hkipo.db`. ## Parameter Model - Weights: `snapshot-quality-weight`, `affordability-weight`, `pricing-stability-weight`, `sponsor-support-weight`, `cost-efficiency-weight` - Thresholds: `participate-min`, `cautious-min` - Costs: `handling-fee-hkd`, `financing-rate-annual-pct`, [REDACTED_SECRET], `lockup-days` ## Workflow 1. Inspect current versions with `params list` or `params show`. 2. Save new candidates instead of mutating old versions. 3. Activate a version only when the user wants it to become the new default. 4. Compare candidate versions on a representative symbol before broad rollout. ## Commands List versions: ```bash cd <skill_dir> uv run --directory runtime/hkipo-next hkipo-next params list --format json ``` Show the active version: ```bash cd <skill_dir> uv run --directory runtime/hkipo-next hkipo-next params show --format json ``` Save and activate a tuned version: ```bash cd <skill_dir> uv run --directory runtime/hkipo-next hkipo-next params save \ --name conservative-margin \ --sponsor-support-weight 0.20 \ --cost-efficiency-weight 0.25 \ --participate-min 78 \ --cautious-min 62 \ --lockup-days 6 \ --notes "Bias toward sponsor quality and lower carrying cost" \ --activate \ --format json ``` Compare two versions: ```bash cd <skill_dir> uv run --directory runtime/hkipo-next hkipo-next params compare 2476 v0002 v0003 --format json ``` ## Output Cues - `active_version` is the default version used by later scoring commands. - `action_changed` in compare output tells you whether a tuning change would alter the recommendation. - `factor_deltas` shows which factor scores moved between versions. ## Companion Skills - Use `$hkipo-decision-engine` after an active version is ready. - Use `$hkipo-review-optimizer` when tuning changes come from real-world review feedback.

path: runtime/hkipo-next/src/hkipo_next/cli/__init__.py
content: """CLI layer for hkipo_next."""


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: pinotao/x-twitter-collector (version 1.0.0)

# X/Twitter 推文收集技能 ## 技能名称 `x-twitter-collector` ## 功能描述 自动收集指定 X/Twitter 用户在过去 24 小时内的所有推文（原创 + 转帖），生成包含中英双语、截图、链接和数据分析的完整报告。 ## 使用场景 - 监控公众人物/企业的社交媒体动态 - 收集特定用户的推文用于分析或存档 - 生成每日/每周推文摘要报告 - 多语言团队需要了解 X 内容 ## 前置条件 1. **浏览器已配置**：OpenClaw 浏览器工具可用 2. **X 账号登录**：建议登录 X 账号以获取完整内容（未登录可能有内容限制） 3. **目标用户公开**：目标 X 账号必须是公开账号 ## 使用方法 ### 基础用法 ``` 收集 @用户名 过去 24 小时的推文 ``` ### 完整命令示例 ``` 帮我收集 @elonmusk 过去 24 小时的推文，要中英双语和截图 ``` ``` 整理 @NASA 昨天的所有推文，带链接 ``` ### 参数说明 | 参数 | 说明 | 默认值 | |------|------|--------| | `@用户名` | X 账号用户名（不含 @ 也可） | 必填 | | `时间范围` | 过去多少小时的内容 | 24 小时 | | `语言` | 报告语言 | 中英双语 | | `截图` | 是否包含页面截图 | 是 | | `链接` | 是否包含推文直链 | 是 | ## 输出内容 ### 报告结构 1. **数据概览** - 推文数量统计表格 2. **原创推文** - 每条包含： - 中英双语对照表格 - 发布时间和内容 - 互动数据（回复/转帖/点赞/浏览） - 推文直链 3. **转帖列表** - 表格形式展示 4. **主题分析** - 按内容分类统计 5. **数据汇总** - 总计数据 6. **页面截图** - 完整长截图 ### 输出格式 - Markdown 格式，支持表格和中英对照 - 截图以附件形式提供 - 所有推文链接可点击跳转 ## 操作流程 ### 步骤 1: 打开浏览器 ```javascript browser.start({ profile: "openclaw" }) ``` ### 步骤 2: 访问用户主页 ```javascript browser.open({ profile: "openclaw", targetUrl: "https://x.com/{username}" }) ``` ### 步骤 3: 等待页面加载 ```javascript browser.act({ profile: "openclaw", request: { kind: "wait", timeMs: 5000 }, targetId: "{targetId}" }) ``` ### 步骤 4: 获取页面快照 ```javascript browser.snapshot({ profile: "openclaw", refs: "aria", targetId: "{targetId}" }) ``` ### 步骤 5: 滚动加载更多内容 ```javascript browser.act({ profile: "openclaw", request: { kind: "evaluate", fn: "window.scrollTo(0, document.body.scrollHeight)" }, targetId: "{targetId}" }) ``` ### 步骤 6: 获取页面截图 ```javascript browser.screenshot({ profile: "openclaw", fullPage: true, targetId: "{targetId}", type: "png" }) ``` ### 步骤 7: 解析和整理数据 从快照中提取： - 推文内容（中英文） - 发布时间 - 互动数据 - 推文链接 - 区分原创/转帖 ### 步骤 8: 生成报告 按照预设模板生成完整的中英双语报告。 ## 数据解析规则 ### 原创推文识别 - 不包含 "已转帖" / "Retweeted" 标识 - 用户头像和名称直接显示 ### 转帖识别 - 包含 "已转帖" / "Retweeted" 标识 - 显示原始推文作者 ### 时间解析 - "X 小时前" → 过去 X 小时 - "XX 月 XX 日" → 具体日期 - "202X 年 X 月 X 日" → 具体日期 ### 互动数据解析 - 回复数：💬 或 "回复" - 转帖数：🔄 或 "转帖" - 点赞数：❤️ 或 "喜欢" - 浏览数：👁️ 或 "次浏览" ## 注意事项 ### 内容限制 - X.com 对未登录用户有限制，建议登录 - 受保护账号的内容无法访问 - 被删除的推文无法获取 ### 性能优化 - 大量推文时可能需要多次滚动 - 截图文件较大，注意存储空间 - 建议定期清理 media 目录 ### 隐私和合规 - 仅收集公开账号内容 - 遵守 X 平台服务条款 - 不用于商业爬虫用途 ## 扩展功能 ### 可添加的增强功能 1. **定时收集** - 设置 cron 定时任务 2. **多用户对比** - 同时收集多个账号对比分析 3. **情感分析** - 对推文内容进行情感分析 4. **趋势统计** - 统计推文主题趋势变化 5. **导出格式** - 支持导出为 PDF/Excel/JSON ### 自定义模板 可以根据需求修改报告模板： - 仅中文或仅英文 - 简化版（不含截图） - 详细版（包含引用推文的完整内容） ## 故障排除 ### 常见问题 | 问题 | 原因 | 解决方案 | |------|------|----------| | 浏览器无法启动 | 浏览器配置问题 | 检查 `browser status` | | 内容加载不全 | 页面未完全加载 | 增加等待时间或手动滚动 | | 截图失败 | 内存不足 | 关闭 fullPage 或分屏截图 | | 链接无效 | 推文已删除 | 标注为"不可用" | ### 错误处理 - 浏览器启动失败 → 提示用户检查浏览器配置 - 页面访问受限 → 提示用户登录 X 账号 - 快照解析失败 → 尝试重新加载页面 ## 相关文件 - `SKILL.md` - 技能说明文档（本文件） - `collect.sh` - 可选的命令行脚本 - `template.md` - 报告模板文件 - `config.json` - 配置文件（可选） ## 版本历史 - **v1.0** (2026-02-27) - 初始版本 - 基础推文收集功能 - 中英双语报告 - 页面截图支持 - 数据分析表格 ## 作者 Generated for OpenClaw workspace ## 许可证 遵循 OpenClaw 技能许可协议


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