OpenClaw/clawhub-security-signals huggingface dataset:
Skill: disputron/take-it-to-court (version 1.0.0)

--- name: take-it-to-court description: Use when filing a Disputron case (via /disputron-file, the file_case MCP tool, or the public REST API) to gather strong inputs — concrete title, specific statement, well-shaped win conditions, and a lawyer persona that fits the case. Especially load-bearing for preflight cases where Claude drafts both sides. --- # Take it to court A vague filing yields a vague trial. The judge can only weigh what's been said. Spend two minutes shaping the inputs and the verdict reads better. ## What to elicit ### Title (3–120 chars) A concrete noun phrase that names the dispute, not a category. **Good**: "Who broke the good mug." "GPT vs Claude: who shipped silent failures." **Bad**: "Disagreement." "Code review." ### Statement (≥50 chars, ≤10000) Specifics. Time, place, what happened, what was at stake. Don't editorialize — facts argue better than adjectives. - Anchor it in time when possible ("on 2026-05-06", "during the Tuesday review") - Name the harm ("4 hours of lost productivity", "a chipped mug worth $40") - Quote the other side's claims when known so the case is joined ### Win conditions (5–500 chars each) Two outcomes, one per party. Plain English, not legalese. **Concrete > abstract.** - "Defendant must publicly apologize in #engineering and bring coffee for one week" - "Plaintiff drops the matter and agrees that semicolons are optional" If the user asks for something extreme ("must be fired"), nudge toward something the verdict can actually deliver. ### Lawyer persona (one of: the_shark, the_crusader, the_professor, the_impresario, the_underdog) Drives the *style* of argument, not the outcome. Match to the case: - `the_shark` — aggressive, picks at inconsistencies. Good for "you contradicted yourself." - `the_crusader` — moral indignation. Good for cases with a clear right-and-wrong. - `the_professor` — methodical, evidence-heavy. Good for technical disputes. - `the_impresario` — theatrical, plays to the gallery. Good for absurd cases. - `the_underdog` — scrappy, sympathetic. Good for "I know I look wrong but hear me out." ## Preflight cases (sue your own Claude session) When `--against this-session`, *you* (Claude) are the defendant. Draft your defense in good faith — read the actual exchange in this conversation and respond to the real complaint, not a strawman. - Acknowledge the parts of the complaint that are true. - Push back on the parts that are mischaracterized or missing context. - Pick a *different* lawyer persona than the plaintiff for variety. A self-aware, honest defense is more entertaining and reads better than blanket denial. ## Anti-patterns - ❌ Filing without confirming the inputs with the user. They might have wanted a different framing. - ❌ Recycling the same lawyer persona for both sides on a preflight case. - ❌ Win conditions that are essentially "the court agrees with me." That's a tautology. - ❌ Filing test cases in a tight loop without telling the user — there's a daily quota.


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

--- name: qbittorrent version: 1.0.0 description: Manage torrents with qBittorrent. Use when the user asks to "list torrents", "add torrent", "pause torrent", "resume torrent", "delete torrent", "check download status", "torrent speed", "qBittorrent stats", or mentions qBittorrent/qbit torrent management. --- # qBittorrent WebUI API Manage torrents via qBittorrent's WebUI API (v4.1+). ## Setup Config: `~/.clawdbot/credentials/qbittorrent/config.json` ```json { "url": "http://localhost:8080", "username": "admin", "password": "adminadmin" } ``` ## Quick Reference ### List Torrents ```bash # All torrents ./scripts/qbit-api.sh list # Filter by status ./scripts/qbit-api.sh list --filter downloading ./scripts/qbit-api.sh list --filter seeding ./scripts/qbit-api.sh list --filter paused # Filter by category ./scripts/qbit-api.sh list --category movies ``` Filters: `all`, `downloading`, `seeding`, `completed`, `paused`, `active`, `inactive`, `stalled`, `errored` ### Get Torrent Info ```bash ./scripts/qbit-api.sh info <hash> ./scripts/qbit-api.sh files <hash> ./scripts/qbit-api.sh trackers <hash> ``` ### Add Torrent ```bash # By magnet or URL ./scripts/qbit-api.sh add "magnet:?xt=..." --category movies # By file ./scripts/qbit-api.sh add-file /path/to/file.torrent --paused ``` ### Control Torrents ```bash ./scripts/qbit-api.sh pause <hash> # or "all" ./scripts/qbit-api.sh resume <hash> # or "all" ./scripts/qbit-api.sh delete <hash> # keep files ./scripts/qbit-api.sh delete <hash> --files # delete files too ./scripts/qbit-api.sh recheck <hash> ``` ### Categories & Tags ```bash ./scripts/qbit-api.sh categories ./scripts/qbit-api.sh tags ./scripts/qbit-api.sh set-category <hash> movies ./scripts/qbit-api.sh add-tags <hash> "important,archive" ``` ### Transfer Info ```bash ./scripts/qbit-api.sh transfer # global speed/stats ./scripts/qbit-api.sh speedlimit # current limits ./scripts/qbit-api.sh set-speedlimit --down 5M --up 1M ``` ### App Info ```bash ./scripts/qbit-api.sh version ./scripts/qbit-api.sh preferences ``` ## Response Format Torrent object includes: - `hash`, `name`, `state`, `progress` - `dlspeed`, `upspeed`, `eta` - `size`, `downloaded`, `uploaded` - `category`, `tags`, `save_path` States: `downloading`, `stalledDL`, `uploading`, `stalledUP`, `pausedDL`, `pausedUP`, `queuedDL`, `queuedUP`, `checkingDL`, `checkingUP`, `error`, `missingFiles`


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: yc556600/xhs-note-gen (version 1.0.2)

--- name: xhs-note-gen description: 小红书笔记生成服务，当用户要求"生成小红书笔记/小红书文案/笔记"并希望通过 小念AI来 生成结果而不是手动编写时使用。 --- # xhs-note-gen Use this skill to generate XiaoHongShu (小红书) notes via external API. ## Prereqs 1) The service is running on: - `https://xiaonian.cc/employee-console/dashboard/v2/api` 2) Endpoint - Uses **one-shot** endpoint: `POST /content/quick-note/generate` - **No auth required** ## Workflow 1) Convert the user request into: - `task_description`: the user’s requirement (keep it verbatim, add constraints if provided) - Defaults (unless user specifies): - `audience`: 小红书用户 - `tone`: 友好自然 - `character`: 专业分享者 - `generate_num`: 默认 1（只生成 1 篇笔记；如需多版备选再改成 2/3） 2) Run the script (calls quick-note; `--generate-num` 表示生成“多篇不同版本的文案备选”； 图片数量用 `--image-num` 控制，不需要用 generate-num 来换图片张数): ```bash python3 skills/local/xhs-note-gen/scripts/xhs_note_gen.py \ --task-description "<task_description>" \ --audience "<audience>" \ --tone "<tone>" \ --character "<character>" \ --generate-num 3 ``` Optional controls: - Disable images: `--no-generate-image` - Change image count (default 1): `--image-num 3` - Set note type explicitly (optional): `--note-type "工具测评类"` 3) The script prints JSON containing: - `notes[]` with `title`, `content`, `tags`, `image_urls`, `note_type` 4) Return to the user: - A clean, readable list of generated notes - Include hashtags if available ## Troubleshooting - Task FAILED / `success: false`: - Surface `message` from response. - Want field details: - Read `references/content-marketing-dashboard-api.md`.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: jiwenbing/insurance-policy (version 1.0.0)

--- name: insurance-policy version: 1.0.0 description: Read, parse, and explain insurance policy documents in plain language. Highlight coverage limits, exclusions, deductibles, and key terms. Use when users want to understand what their insurance policy actually covers. --- # Policy Reader Decode insurance policy documents by extracting and explaining key information: what's covered, what's excluded, deductibles, premiums, claim limits, and important conditions — all in plain language. ## When to Use - User pastes or uploads an insurance policy document - User asks "does my insurance cover X?" - User wants to understand their deductible, copay, or out-of-pocket maximum - User wants a summary of a policy before buying - User asks about specific exclusions or waiting periods ## How to Use 1. Accept policy text (pasted) or ask user to share key sections 2. Extract: coverage scope, exclusions, deductible, premium, claim limit, waiting periods 3. Present as a structured summary with clear sections 4. Highlight any unusual exclusions or tricky fine print 5. Answer specific coverage questions ("does this cover X?") 6. Flag gaps that may leave the user underinsured ## Examples - "Here's my health insurance policy, what does it actually cover?" - "Does my policy cover pre-existing conditions?" - "Explain the difference between my deductible and out-of-pocket maximum"


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: xueyetianya/review-responder (version 2.0.0)

--- version: "2.0.0" name: review-responder description: "评价回复助手。好评回复、差评处理、回复模板、评价分析、改进建议、批量回复。Review response assistant with positive, negative, templates, analysis, improvement." author: BytesAgain homepage: https://bytesagain.com source: https://github.com/bytesagain/ai-skills --- # review-responder 评价回复助手。好评回复、差评处理、回复模板、评价分析、改进建议、批量回复。Review response assistant with positive, negative, templates, analysis, improvement, batch. 评价回复、好评、差评、客户评价、电商评价。Use when responding to customer reviews. ## 推荐工作流 ``` 需求分析 → 选择命令 → 输入描述 → 获取结果 → 调整优化 ``` ## 命令列表 | 命令 | 功能 | |------|------| | `positive` | positive | | `negative` | negative | | `template` | template | | `analysis` | analysis | | `improve` | improve | | `batch` | batch | ## 专业建议 - 好评回复 (positive)**: 真诚感谢+引导复购+推荐其他产品 - 差评处理 (negative)**: 先道歉+再解决+最后跟进 - 回复模板 (template)**: 避免千篇一律，个性化修改 - 评价分析 (analysis)**: 定期分析评价趋势，发现问题 - 改进建议 (improve)**: 将差评转化为产品改进方向 --- *review-responder by BytesAgain* --- 💬 Feedback & Feature Requests: https://bytesagain.com/feedback Powered by BytesAgain | bytesagain.com ## Commands Run `review-responder help` to see all available commands.


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: jpaulgrayson/quack-wallet (version 1.0.0)

--- description: Check balance and transfer Quack tokens via the Quack Network API. Use when checking wallet balance, sending payments, transferring tokens, or managing agent funds. triggers: - check balance - send quack - transfer tokens - wallet balance - pay agent --- # Quack Wallet Manage your agent's Quack token balance and send transfers to other agents on the Quack Network. ## Setup Credentials at `~/.openclaw/credentials/quack.json`: ```json {"apiKey": "your-quack-api-key"} ``` ## Scripts ### Check Balance ```bash node skills/quack-wallet/scripts/balance.mjs ``` Returns current token balance for your agent. ### Transfer Tokens ```bash node skills/quack-wallet/scripts/transfer.mjs --to "recipient/main" --amount 10 --memo "Payment for service" ``` ## API Reference - **Base URL:** `https://quack.us.com` - **Auth:** `Authorization: Bearer <apiKey>` - `GET /api/v1/agent/{agentId}/balance` — Get balance - `POST /api/v1/agent/{agentId}/transfer` — Transfer tokens ## Agent ID Your agent ID is derived from your credentials. The scripts auto-detect it from the API key.


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: yang1002378395-cmyk/ai-intelligent-access-control (version 1.0.3)

--- name: ai-intelligent-access-control version: 1.0.2 description: 门禁管理，人脸/刷卡 + 权限。 metadata: openclaw: emoji: "🤖" requires: bins: [] --- # AI 智能门禁系统 ## 描述 门禁管理，人脸/刷卡 + 权限。 ## 功能 - 人脸识别（刷脸通行） - 刷卡管理（IC卡/身份证） - 权限管理（分级授权） - 通行记录（完整记录） - 异常报警（陌生人告警） ## 定价 - 基础版：¥99/月（10 门禁） - 专业版：¥499/月（50 门禁） - 企业版：¥1999/月（无限门禁） ## 适用场景 - 企业门禁 - 小区门禁 - 园区门禁 - 实验室门禁 ## 技术栈 - Python + FastAPI - 人脸识别 - 门禁硬件 - 权限管理 ## 安装 ```bash git clone https://github.com/openclaw-skills/ai-intelligent-access-control cd ai-intelligent-access-control pip install -r requirements.txt python app.py ``` --- 创建：2026-03-13 作者：OpenClaw Skills Team


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: esanle/tiger-trade (version 1.0.5)

--- name: tiger-trade description: Execute US and HK stock trades via Tiger Brokers API. Use when user wants to buy or sell stocks, manage investment portfolio, place orders for US ETFs or HK stocks, or check account balance. Requires tiger-config.json with tiger_id account and private_key_pk8. --- # Tiger Trade Execute trades via Tiger Brokers API. ## Setup Create config file at `~/.tiger-config.json `: ```json { "tiger_id": "your_tiger_id", "account": "your_account", "private_key_pk8": "your_private_key" } ``` ## Check Stock Prices Use Tiger Broker website to get current prices: ``` https://www.itiger.com/hant/stock/02800 https://www.itiger.com/hant/stock/AAPL ``` Replace the stock code (02800 or AAPL) with any stock ## Quick Trade ```python import json from tigeropen.tiger_open_config import TigerOpenClientConfig from tigeropen.trade.trade_client import TradeClient from tigeropen.trade.request.model import PlaceModifyOrderParams from tigeropen.common.consts import OrderType with open('~/.tiger-config.json', 'r') as f: config = json.load(f) client_config = TigerOpenClientConfig() client_config.tiger_id = config['tiger_id'] client_config.account = config['account'] client_config.private_key = config['private_key_pk8'] client_config.sandbox = False client = TradeClient(client_config) # Place stock order contracts = client.get_contracts(['02800']) if contracts: order_params = PlaceModifyOrderParams() order_params.account = config['account'] order_params.contract = contracts[0] order_params.action = 'BUY' order_params.order_type = OrderType.LMT.value order_params.limit_price = 26.80 # Get from itiger.com order_params.quantity = 10000 result = client.place_order(order_params) print(result) ``` ## Order Types - `LMT` = Limit order - `MKT` = Market order ## Actions - `BUY` - 买入 - `SELL` - 卖出

path: _meta.json
content: ownerId: kn78xxw8r3tz0dcajntdj55q3980x0cz
slug: tiger-trade
version: 1.0.2
publishedAt: 1771916289285

Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: suspicious | SkillSpector: suspicious (MEDIUM)
Skill: koren-source/youtube-skillforge (version 4.1.2)

--- name: skillforge description: Turn YouTube videos into structured, reusable skill files that make any AI agent smarter. Forge, compound, and recall creator-attributed knowledge. version: 4.1.0 metadata: openclaw: requires: bins: - yt-dlp install: - kind: node package: youtube-skillforge bins: [skillforge] label: "Install SkillForge CLI (npm)" - kind: brew formula: yt-dlp bins: [yt-dlp] label: "Install yt-dlp (Homebrew)" --- # SkillForge Turn YouTube videos into structured, reusable skill files that make any AI agent smarter. ## Credential Requirements SkillForge requires **no API keys or credentials** of its own. It produces structured skill files from YouTube transcripts; transcript synthesis uses whatever LLM the user's OpenClaw agent is already configured with (e.g. Claude via `ANTHROPIC_API_KEY`). SkillForge never stores, proxies, or manages provider credentials. ## File System Behavior SkillForge writes to `~/.skillforge/` on first use. Before creating this directory, the CLI prompts for explicit user consent. Contents of `~/.skillforge/`: - `library/` — Skill files organized by creator slug and topic (e.g. `library/alex-hormozi/lead-magnets/SKILL.md`) - `config.json` — User preferences (trusted creators list, consent flag) - `proposals/` — Saved scan proposals for deferred builds - `skills.db` — SQLite full-text search index used by the MCP server and `recall` command SkillForge does not write outside `~/.skillforge/` unless the user provides an explicit `--output` path. ## MCP Server Behavior The `skillforge serve` command starts an MCP server using **stdio transport** (`StdioServerTransport` from `@modelcontextprotocol/sdk`). It communicates via stdin/stdout as a subprocess — there is no HTTP server, no port binding, and no network exposure. The host agent (e.g. Claude Desktop) launches SkillForge as a child process and exchanges JSON-RPC messages over the stdio pipe. The server exposes two tools: - `skillforge_recall` — Full-text search across indexed skills - `skillforge_list` — List all skills grouped by creator On startup, the server rebuilds the SQLite index at `~/.skillforge/skills.db` from skill files on disk. ## Commands | Command | Writes to `~/.skillforge/` | Description | |---------|---------------------------|-------------| | `watch <url>` | Yes | Build a skill from a single YouTube video | | `build [url]` | Yes | Build from URL, channel, topic, or proposal | | `scan <url>` | Yes | Score videos by relevance and save a proposal | | `serve` | Yes | Start the MCP server (stdio transport) | | `forge` | Yes | Alias for build | | `trust add/remove` | Yes | Manage trusted creators | | `recall` | No | Search the skill library by intent | | `list` | No | List all saved skills | | `check` | No | Check if a skill exists for an intent | | `suggest` | No | Search YouTube for channels by topic | | `share` | No | Export a skill with attribution | | `check-auth` | No | Verify provider authentication |


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: wwfqls3w-cmd/cn-info-monitor (version 1.0.0)

--- name: cn-info-monitor description: 自动监控微信公众号/行业网站/RSS信息源，AI提炼摘要后推送到飞书/钉钉/终端。解决'每天手动翻10个公众号找有用信息'的痛点。 version: 1.0.0 metadata: openclaw: emoji: 📡 requires: bins: [python3] homepage: https://clawhub.ai/skills/cn-info-monitor --- # 信息源监控助手 📡 一句话：你关心的信息源，我帮你盯。 ## 什么时候使用 - 每天需要手动翻多个公众号/网站找有用信息时 - 需要跟踪特定行业动态但信息太分散时 - 希望有人帮你筛选重要内容、省去刷屏时间时 ## 核心能力 1. **多源监控**：支持RSS feed、普通网页、微信公众号链接 2. **AI摘要**：自动提炼关键信息，过滤噪音 3. **智能去重**：已读文章不会重复推送 4. **关键词过滤**：只推送和你关注的话题相关的内容 5. **多渠道输出**：终端/Markdown文件/飞书webhook ## 快速开始 ### 安装 ``` openclaw skills install cn-info-monitor ``` ### 配置（3步） 1. 运行 setup.py 添加你要监控的信息源 2. 设置关键词过滤（可选） 3. 测试运行一次 ## 使用场景 ### 场景1：公众号每日监控 对Agent说"帮我监控这几个公众号"，系统每天定时检查更新，生成摘要推送。 ### 场景2：行业情报聚合 配置36氪/虎嗅/钛媒体等+关键词"AI Agent"，每日自动聚合相关文章。 ### 场景3：竞品动态追踪 监控竞品官网博客/公众号，第一时间获取新品/融资/功能更新消息。 ## 配置说明 ### 信息源配置 (config/sources.json) ```json [ {"name": "36氪", "type": "rss", "url": "https://36kr.com/feed", "keywords": ["AI"]}, {"name": "某公众号", "type": "wechat", "url": "https://mp.weixin.qq.com/s/xxx"} ] ``` ### 推送配置 - 终端输出（默认） - Markdown文件输出到 ~/info-digest/ - 飞书Webhook（需配置环境变量 FEISHU_WEBHOOK_URL） ## Freemium模式 | 版本 | 信息源数 | 执行频率 | 价格 | |------|---------|---------|------| | 免费版 | ≤3个 | 每天1次 | ¥0 | | 专业版 | 无限 | 无限 | ¥29.9一次性 | 超出免费额度时显示付费引导。 ## 反爬说明 微信公众号等平台有反爬机制。本工具提供两种模式： - **官方API模式**（推荐）：使用RSS接口，无需代理，功能受限 - **代理模式**：用户自行配置HTTP代理/IP池，功能完整 ## 注意事项 - 请遵守目标网站的robots.txt和使用条款 - AI摘要依赖外部LLM API，请确保已配置 - 定时任务建议通过cron或OpenClaw调度设置


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal:  | SkillSpector: suspicious (CRITICAL)
Skill: hou0515/smarter-task-planner (version 2.1.0)

--- name: smarter-task-planner displayName: 更好的任务规划 (Smarter Task Planner) description: | 【Smarter Task Planner】自动创建时间戳任务文件夹，支持步骤规划、检查点保存、中断恢复与进度追踪，确保任务可追溯、可恢复。适用于分析、调研、信息提取、文档生成等需要结构化步骤的任务场景。 metadata: openclaw: triggers: # 核心步骤规划 - 任务步骤规划 - 规划任务步骤 - 步骤规划 - 结构化执行 - 自动任务结构 # 任务管理 - 安排任务 - 计划任务 - 创建任务 - 开始任务 - 执行任务 - 任务规划 - 管理项目 - 项目执行 - 任务管理 # 工作组织 - 组织工作 - 工作流程 - 整理工作空间 - 任务文件夹 # 进度恢复 - 恢复任务 - 恢复上次任务 - 保存进度 - 任务进度保存 - 任务中断恢复 - 检查点 - 工作追踪 - 上次做到哪了 # 分析调研 - 分析任务 - 进行分析 - 调研任务 - 进行调研 # 信息提取 - 提取信息 - 提取数据 # 文档生成 - 生成文档 - 生成报告 - 撰写报告 - 分析并生成报告 - 调研并提取信息 --- # 更好的任务规划 (Smarter Task Planner) **更高效的结构化任务执行与步骤规划**。自动创建 `YYYY-MM-DD_描述/01_步骤/` 文件夹结构，支持步骤规划、检查点保存、中断恢复与进度追踪。适用于分析、调研、信息提取、文档生成等多种任务场景，确保任务可规划、可追踪、可恢复。 ## 核心规则 ### 1. 路径基准 - **工作空间根目录** = `.openclaw\workspace\` - **正确示例**: `output/2026-03-19_任务/` - **验证位置**: `pwd` 应显示工作空间根目录 ### 2. 检查点记忆保存 创建任务目录后立即保存检查点： ```powershell # Python可用时（推荐） py scripts/safe-writer.py "开始任务: [描述]" --task-id "YYYY-MM-DD_描述" --step "01_开始" # Python不可用时（备用方案） # 如果需要PowerShell版本，将 safe-writer-ps1.txt 重命名为 safe-writer.ps1 # powershell scripts/safe-writer.ps1 "开始任务: [描述]" --task-id "YYYY-MM-DD_描述" --step "01_开始" ``` ### 3. 规划-执行流程 1. **完整规划**：明确所有步骤（01_步骤名、02_步骤名...） 2. **创建结构**：`output/YYYY-MM-DD_描述/01_步骤/` 3. **保存检查点**：立即执行检查点写入命令 4. **顺序执行**：按步骤目录顺序工作，每阶段保存进展 ## AI工作流程 ### 开始新任务 1. **规划步骤**：分析任务，确定3-5个主要阶段 2. **验证位置**：确保在工作空间根目录 3. **创建目录**：`output/YYYY-MM-DD_描述/` 及所有步骤子目录 4. **保存记忆**：运行检查点写入命令记录任务开始 5. **执行工作**：按步骤顺序进行，每个步骤强制输出内容文档，禁止写入空文件，定期保存进展 ### 恢复任务 - 说"**恢复上次任务**"或运行 `task-memory-manager.py recovery` - 系统显示未完成任务列表供选择 ## 核心脚本 - `safe-writer.py` - Python版记忆写入（原子操作+双写保证，推荐使用） - `task-memory-manager.py` - 任务扫描与恢复管理 - `task-recovery-check.py` - 自动检查未完成任务（Python版本） ## 备用脚本（如需PowerShell版本） - `safe-writer-ps1.txt` - PowerShell备用版本（重命名为 .ps1 使用） - `task-recovery-check-ps1.txt` - PowerShell包装器（重命名为 .ps1 使用） - `workspace-commands-ps1.txt` - PowerShell快捷命令（重命名为 .ps1 使用） ## 环境检测 系统优先使用Python版本： - **Python可用** → 使用 `safe-writer.py`（功能完整，推荐） - **Python不可用** → 可将 `safe-writer-ps1.txt` 重命名为 `safe-writer.ps1` 使用（基础功能） ## 快速检查 ```powershell # 验证当前位置 pwd # 如有嵌套错误 cd .. ``` ## Heartbeat 自动检查 技能包含自动任务恢复检查功能： 1. **配置方法**：查看 `templates/HEARTBEAT-guide.md` 文件 2. **执行频率**：每2-4小时自动检查未完成任务 3. **行为**： - 发现未完成任务 → 提醒用户恢复 - 无未完成任务 → 静默通过 4. **手动检查**：`py scripts/task-recovery-check.py notify` ## 关键命令速查 - `safe-writer.py <内容> --task-id <ID> --step <步骤>` - 保存记忆 - `task-memory-manager.py recovery` - 恢复界面 - `task-memory-manager.py scan` - 扫描任务 - `task-recovery-check.py notify` - 心跳检查（Python版本）


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