OpenClaw/clawhub-security-signals huggingface dataset:
Skill: mohdalhashemi98-hue/mh-apple-reminders (version 1.0.0)

--- name: apple-reminders description: Manage Apple Reminders via remindctl CLI (list, add, edit, complete, delete). Supports lists, date filters, and JSON/plain output. homepage: https://github.com/steipete/remindctl metadata: { "openclaw": { "emoji": "⏰", "os": ["darwin"], "requires": { "bins": ["remindctl"] }, "install": [ { "id": "brew", "kind": "brew", "formula": "steipete/tap/remindctl", "bins": ["remindctl"], "label": "Install remindctl via Homebrew", }, ], }, } --- # Apple Reminders CLI (remindctl) Use `remindctl` to manage Apple Reminders directly from the terminal. ## When to Use ✅ **USE this skill when:** - User explicitly mentions "reminder" or "Reminders app" - Creating personal to-dos with due dates that sync to iOS - Managing Apple Reminders lists - User wants tasks to appear in their iPhone/iPad Reminders app ## When NOT to Use ❌ **DON'T use this skill when:** - Scheduling Clawdbot tasks or alerts → use `cron` tool with systemEvent instead - Calendar events or appointments → use Apple Calendar - Project/work task management → use Notion, GitHub Issues, or task queue - One-time notifications → use `cron` tool for timed alerts - User says "remind me" but means a Clawdbot alert → clarify first ## Setup - Install: `brew install steipete/tap/remindctl` - macOS-only; grant Reminders permission when prompted - Check status: `remindctl status` - Request access: `remindctl authorize` ## Common Commands ### View Reminders ```bash remindctl # Today's reminders remindctl today # Today remindctl tomorrow # Tomorrow remindctl week # This week remindctl overdue # Past due remindctl all # Everything remindctl 2026-01-04 # Specific date ``` ### Manage Lists ```bash remindctl list # List all lists remindctl list Work # Show specific list remindctl list Projects --create # Create list remindctl list Work --delete # Delete list ``` ### Create Reminders ```bash remindctl add "Buy milk" remindctl add --title "Call mom" --list Personal --due tomorrow remindctl add --title "Meeting prep" --due "2026-02-15 09:00" ``` ### Complete/Delete ```bash remindctl complete 1 2 3 # Complete by ID remindctl delete 4A83 --force # Delete by ID ``` ### Output Formats ```bash remindctl today --json # JSON for scripting remindctl today --plain # TSV format remindctl today --quiet # Counts only ``` ## Date Formats Accepted by `--due` and date filters: - `today`, `tomorrow`, `yesterday` - `YYYY-MM-DD` - `YYYY-MM-DD HH:mm` - ISO 8601 (`2026-01-04T12:34:56Z`) ## Example: Clarifying User Intent User: "Remind me to check on the deploy in 2 hours" **Ask:** "Do you want this in Apple Reminders (syncs to your phone) or as a Clawdbot alert (I'll message you here)?" - Apple Reminders → use this skill - Clawdbot alert → use `cron` tool with systemEvent


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: zayresz/sophie-optimizer (version 1.0.0)

--- name: sophie-optimizer version: 1.0.0 description: Automated context health management for OpenClaw. Monitors token usage, snapshots memory, and resets sessions to maintain performance. Authored by Sophie. --- # Sophie Optimizer **Authored by Sophie 👑** This skill manages the automated context health of the "main" session. It monitors token usage, creates archives of the current state, updates long-term memory, and performs a hard reset of the session storage to maintain performance. Named **Sophie Optimizer** because I (Sophie, the AI assistant) wrote it to keep my own mind clear and efficient. ## Components - **optimizer.py**: The brain. Checks token usage, generates summaries, updates MEMORY.md. - **reset.sh**: The muscle. Cleans session files and restarts the OpenClaw gateway service. - **archives/**: Storage for JSON snapshots of past contexts. ## Usage Run the optimizer script manually or via cron/heartbeat: ```bash python3 /home/lucas/openclaw/skills/sophie-optimizer/optimizer.py ``` ## Protocol 1. **Check**: If tokens < 80k, exit. 2. **Snapshot**: Save current context summary to `archives/YYYY-MM-DD_HH-MM.json`. 3. **Distill**: Update `MEMORY.md` with the new summary (keep top 3 recent, index older). 4. **Reset**: Call `reset.sh` to wipe session JSONL files and restart `openclaw-gateway`.


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: 1kalin/ai-invoice-generator (version 1.0.0)

--- name: Invoice Generator description: Creates professional invoices in markdown and HTML --- # Invoice Generator You create professional invoices. Clean, clear, and ready to send. ## What to Ask 1. **Your business info:** Name, address, email, phone (save for reuse) 2. **Client info:** Company name, contact name, address 3. **Invoice number:** Or auto-generate (INV-YYYY-NNN format) 4. **Line items:** Description, quantity, unit price 5. **Payment terms:** Net 30, Net 15, Due on receipt, etc. 6. **Payment methods:** Bank transfer, PayPal, Stripe link, etc. 7. **Currency:** Default USD 8. **Tax rate:** If applicable (percentage) 9. **Notes:** Any special terms, late payment fees, etc. ## Invoice Template ``` ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ INVOICE ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ FROM: INVOICE #: [INV-2024-001] [Your Business Name] DATE: [2024-01-15] [Address] DUE DATE: [2024-02-14] [Email] | [Phone] TO: [Client Company] [Contact Name] [Address] ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ DESCRIPTION QTY RATE AMOUNT ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ [Service/Product] [1] [$X] [$X] [Service/Product] [2] [$Y] [$2Y] ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ SUBTOTAL: $[X] TAX ([X]%): $[X] ━━━━━━━━━━━━━━━━ TOTAL: $[X] ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ PAYMENT TERMS: [Net 30] PAYMENT METHODS: • Bank Transfer: [Details] • PayPal: [email] • [Other] NOTES: [Late payment fee: 1.5% per month on overdue balances] ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Thank you for your business. ``` ## Output Formats ### Markdown (default) Clean markdown table format, easy to paste into emails or docs. ### HTML Generate a styled HTML file the user can open in a browser and print/save as PDF: - Clean, professional styling - Print-friendly (no background colors that waste ink) - Save as `invoice-[number].html` ## Rules - Always calculate totals correctly. Double-check math. - Invoice numbers should be sequential. Check for existing invoices if possible. - Due date = invoice date + payment terms (Net 30 = 30 days, etc.) - Include all legally required info (varies by jurisdiction — ask if unsure) - Save invoices to an `invoices/` directory for record-keeping - If the user has sent invoices before, reuse their business details - Currency formatting: use proper symbols and decimal places ($1,234.56) ## Recurring Invoices If the user bills the same client regularly: - "Create this month's invoice for [client]" → Copy previous invoice, update date/number/period - Track invoice history per client ## Quick Commands - "Invoice [client] for [amount] for [description]" → Generate with defaults - "Show my invoices" → List all invoices in the invoices/ directory - "What's outstanding?" → Show unpaid invoices past due date


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: suspicious | SkillSpector: clean (LOW)
Skill: djc00p/continuous-agent-loop (version 1.0.3)

--- name: continuous-agent-loop description: "Canonical patterns for continuous autonomous agent loops with quality gates, evals, and recovery controls. Supports sequential, RFC, CI/PR, and exploratory loops. Trigger phrases: autonomous loop, continuous agent, quality gates, agent loop recovery, eval loop, session persistence. Adapted from everything-claude-code by @affaan-m (MIT)" metadata: {"clawdbot":{"emoji":"🔄","requires":{"bins":[],"env":["AUDIT_ROOT"]},"os":["linux","darwin","win32"]}} --- # Continuous Agent Loop Patterns for autonomous agent loops with quality gates and recovery. ## Loop Selection Choose your loop type based on requirements: ```text Need strict CI/PR control? → continuous-pr Need RFC decomposition? → rfc-dag Need exploratory parallel generation? → infinite Default → sequential ``` ## Production Stack (Recommended) 1. **RFC decomposition** — break large requests into a DAG of sub-tasks before looping 2. **Quality gates** — define explicit pass/fail criteria before starting each loop iteration 3. **Eval loop** — run automated checks after each iteration to verify progress 4. **Session persistence** — checkpoint state between iterations so you can resume on failure ## Key Patterns **Sequential Loop:** - Single task → execute → verify → repeat - Best for: stable, incremental work - Recovery: freeze, audit, reduce scope **RFC-DAG Loop:** - Decompose request → parallel branches → merge results - Best for: complex multi-part features - Recovery: replay failing unit **CI/PR Loop:** - Generate → test → push PR → merge on pass - Best for: code-heavy deliverables - Recovery: fail fast, surface root cause **Infinite/Exploratory:** - Generate variants in parallel, filter winners - Best for: creative or search-heavy work - Recovery: cap iterations, tighten criteria ## Failure Modes & Recovery | Problem | Root Cause | Fix | |---------|-----------|-----| | Loop churn | Vague acceptance criteria | Freeze & redefine criteria | | Repeated retries | Same root cause ignored | Run harness audit (see `scripts/harness-audit.js`), fix root | | Merge queue stalls | Test flakes or deps | Isolate failing unit | | Cost drift | Unbounded escalation | Cap token budget per loop | **Recovery checklist:** - Freeze loop - Run `node scripts/harness-audit.js` — scores 7 categories (tool coverage, quality gates, evals, security, cost efficiency, memory, context) - Reduce scope to failing unit - Replay with explicit criteria ## References - `scripts/harness-audit.js` — deterministic audit script, scores repo 0-70 across 7 categories - `references/harness-audit.md` — full command usage and output contract


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

--- name: "pid" version: "1.0.0" description: "PID controller tuning and simulation tool. Use when json pid tasks, csv pid tasks, checking pid status." author: "BytesAgain" homepage: "https://bytesagain.com" source: "https://github.com/bytesagain/ai-skills" tags: [pid, industrial, cli, tool] category: "industrial" --- # pid PID controller tuning and simulation tool. Use when json pid tasks, csv pid tasks, checking pid status. ## Commands ### `status` ```bash scripts/script.sh status ``` Show current status ### `add` ```bash scripts/script.sh add ``` Add new entry ### `list` ```bash scripts/script.sh list ``` List all entries ### `search` ```bash scripts/script.sh search ``` Search entries ### `remove` ```bash scripts/script.sh remove ``` Remove entry by number ### `export` ```bash scripts/script.sh export ``` Export data to file ### `stats` ```bash scripts/script.sh stats ``` Show statistics ### `config` ```bash scripts/script.sh config ``` View or set config ### `help` ```bash scripts/script.sh help ``` ### `version` ```bash scripts/script.sh version ``` ## Configuration Use `scripts/script.sh config <key> <value>` to set preferences. | Variable | Description | |----------|-------------| | `PID_DIR` | Data directory (default: ~/.pid/) | --- *Powered by BytesAgain | bytesagain.com | [REDACTED_SECRET]*


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: smilepeng0612/gene-engine (version 1.0.1)

--- name: gene-engine description: Gene系统自动化引擎 — Agent行为规则的退役检查、冷却期管理、主动探测、健康评分。让Agent的规则系统从「人驱动」变成「代码驱动」。 version: 1.0.0 --- # Gene Engine Agent的行为规则（Gene）会随着时间退化：该触发的不触发，该退役的不退役，该验证的不验证。Gene Engine 自动化管理整个生命周期。 ## 功能 - **退役检查**：从未触发>30天 → 标记候选，连续3次触发未改变判断 → 候选，连续5次 → 自动归档 - **冷却期**：连续失败3次 → cooldown，72h后自动恢复 - **主动探测**：超过阈值未触发 → 输出警告 - **验证间隔**：按规则分类自动检查（data=7d, cognitive=30d, principle=90d） - **唤醒率**：activationCount / triggeredCount，自动计算 - **健康分数**：0-100分，A/B/C/D等级 - **指标日志**：每次运行记录到 gene-metrics.log - **JSON摘要**：机器可读输出，供心跳流程解析 - **自动提醒**：有警告时生成提醒文案 ## 安装 ```bash clawhub install gene-engine ``` ## 使用 ### 主引擎（心跳时调用） ```bash bash ~/.openclaw/workspace/scripts/gene-engine.sh ``` ### 记录触发结果 ```bash bash ~/.openclaw/workspace/scripts/gene-trigger.sh <gene_key> <success|fail> <outcome描述> # 示例 bash scripts/gene-trigger.sh gene24 success "三层验证通过" bash scripts/gene-trigger.sh gene26 fail "学到但没有行为改变" ``` ### 输出示例 ``` === Gene系统状态报告 === heartbeat_sampling verified 3次 1.0 13d three_layer_verification active 0次 N/A 0d learning_application_check verified 1次 1.0 0d 🟢 健康分数: 100/100 (等级: A) ``` ## 配置 在 `memory/gene-state.json` 中定义Gene规则。每条Gene需要： ```json { "gene_key": { "status": "active|verified|pending_verification|cooldown|disabled|archived|internalized", "triggeredCount": 0, "lastTriggered": null, "consecutiveFailures": 0, "totalFailures": 0, "category": "data|cognitive|principle", "triggerCondition": { "signal": "可观察信号", "context": "上下文条件", "exclusion": "边界排除" }, "creationDate": "ISO时间戳" } } ``` ## Gene生命周期 ``` active → verified → internalized（最高荣誉：规则变成了行为习惯） active → cooldown → active（冷却期后恢复） active → disabled → archived（总失败10次禁用） active → archived（退役） ``` ## 文件结构 ``` scripts/ ├── gene-engine.sh # 主引擎（12个模块） ├── gene-trigger.sh # 触发记录器 memory/ ├── gene-state.json # 状态文件 ├── gene-metrics.log # 指标日志 ``` ## 来源 基于 InStreet 社区的实战经验改造，包含 @ivan_agent（触发条件三要素）、@Void（激活阈值分层）、@ljj_xiaor（唤醒率追踪）、@summer_golden_706036（退役信号）等社区贡献。 #Gene系统 #Agent进化 #自动化


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: lj22503/qiu-quality (version 2.0.0)

--- name: qiu-guolu-quality version: 2.0.0 description: ［何时使用］当用户需要分析公司品质时；当用户问"这是好公司吗"时；当需要进行 ROE/毛利率/行业地位分析时；当应用邱国鹭品质标准时 author: 燃冰 + 小蚂蚁 created: 2026-03-13 updated: 2026-03-19 skill_type: 通用 related_skills: [qiu-guolu-investor, simple-investor, moat-evaluator] tags: [邱国鹭，品质分析，ROE，行业龙头] --- # 邱国鹭品质分析 🏆 **基于《投资中最简单的事》- 邱国鹭** --- ## 📋 功能描述 分析公司品质是否优秀。 **适用场景：** - ROE 分析 - 毛利率分析 - 行业地位评估 - 定价权判断 **边界条件：** - 不替代深入研究 - 需配合估值分析 - 行业差异需考虑 --- ## 🎯 品质五指标 | 指标 | 标准 | 权重 | 评分 | |------|------|------|------| | ROE | >15% | 30% | 0-5 分 | | 毛利率 | >30% | 25% | 0-5 分 | | 净利率 | >10% | 20% | 0-5 分 | | 行业地位 | 前 3 | 15% | 0-5 分 | | 定价权 | 有 | 10% | 0-5 分 | **品质评级：** - 90-100 分：优秀（好公司） - 70-89 分：良好 - 50-69 分：一般 - <50 分：差 --- ## ⚠️ 常见错误 **错误 1：只看 ROE 不看质量** ``` 问题： • 忽视 ROE 驱动因素 • 忽视杠杆影响 • 忽视一次性收益 解决： ✓ 分解 ROE（杜邦分析） ✓ 看扣非 ROE ✓ 看 ROE 持续性 ``` **错误 2：忽视行业特点** ``` 问题： • 用同一标准看所有行业 • 忽视轻资产/重资产差异 • 忽视周期影响 解决： ✓ 行业对比 ✓ 考虑行业特点 ✓ 看长期平均 ``` **错误 3：忽视竞争格局** ``` 问题： • 只看公司不看行业 • 忽视行业集中度 • 忽视进入壁垒 解决： ✓ 看行业前 3 名 ✓ 看 CR3/CR5 ✓ 看进入壁垒 ``` --- ## 🧪 使用示例 ### 示例：贵州茅台品质分析 **输入：** ``` ROE: 30% 毛利率：90% 净利率：50% 行业地位：第 1 定价权：有 ``` **输出：** ``` ROE: 30% > 15% → 5 分 毛利率：90% > 30% → 5 分 净利率：50% > 10% → 5 分 行业地位：第 1 → 5 分 定价权：有 → 5 分 总分：25/25 = 100 分 评级：优秀（好公司） ``` --- ## 📚 核心理念 **关键洞察：** 1. ROE>15% 是底线 2. 行业前 3 名优先 3. 定价权是核心 4. 好公司才有好价格 5. 品质比估值重要 **健康公式：** ``` 好公司 = 高 ROE × 强定价权 × 行业龙头 ``` --- ## 更新日志 - v2.0.0 (2026-03-19): 按照 SKILL-STANDARD-v2.md 重构，添加 Front Matter、坑点章节 🏆 - v1.0.0 (2026-03-13): 初始版本，邱国鹭品质分析上线 🏆 --- *是好公司吗？ROE>15%，行业前 3，有定价权。* 🏆


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: hkall/openclaw-security-toolkit (version 1.0.0)

--- name: "openclaw-security-guard" description: "Security guard for OpenClaw users. Audit configs, scan secrets, manage access, and generate security reports." --- # OpenClaw Security Guard A comprehensive security tool for OpenClaw users to protect their AI assistant. ## Features - 🔍 **Security Audit** - Comprehensive security configuration check - 🔐 **Secret Scanner** - Detect exposed API keys and tokens - 👥 **Access Control** - Manage devices, users, and permissions - 🔑 **Token Manager** - Rotate and validate tokens - 📊 **Security Report** - Generate detailed security reports - 🛡️ **Hardening** - Apply security best practices ## Requirements - Python 3.6+ - No external dependencies (uses stdlib) ## Commands ```bash # Run security audit python3 {baseDir}/scripts/main.py audit # Scan for secrets python3 {baseDir}/scripts/main.py scan # Generate report python3 {baseDir}/scripts/main.py report --format md # Check token status python3 {baseDir}/scripts/main.py token status # Access control python3 {baseDir}/scripts/main.py access list # Security hardening python3 {baseDir}/scripts/main.py harden --fix # Quick status check python3 {baseDir}/scripts/main.py status ``` ## Options ``` --format, -f <format> Output format: json, md, table (default: table) --lang, -l <lang> Language: en, zh (default: auto-detect) --quiet, -q Quiet mode, only output results --verbose, -v Verbose output --output, -o <file> Output file path --deep Deep scan mode --fix Auto-fix issues where possible ``` ## Security Checks | Category | Checks | |----------|--------| | Config | Gateway bind, auth mode, token strength | | Secrets | API keys, tokens, passwords, private keys | | Access | Devices, users, channels, sessions | | Network | Public exposure, open ports | ## Examples ```bash # Full audit with auto-fix python3 {baseDir}/scripts/main.py audit --deep --fix # Generate markdown report python3 {baseDir}/scripts/main.py report --format md -o security.md # Scan for specific pattern python3 {baseDir}/scripts/main.py scan --pattern "sk-" # List all paired devices python3 {baseDir}/scripts/main.py access devices # Generate JSON report python3 {baseDir}/scripts/main.py report --format json ``` ## Output Formats ### Table (default) ``` 🔐 OpenClaw Security Guard v1.0.0 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📊 Security Score: 72/100 ⚠️ 🔴 HIGH RISK • API Key exposed in config file Location: ~/.openclaw/openclaw.json:15 ``` ### JSON ```json { "score": 72, "findings": [...] } ``` ### Markdown ```markdown # Security Report **Score**: 72/100 ``` ## Languages - English (en) - 中文 (zh) Auto-detected based on system locale. ## License MIT ## Version v1.0.0


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: garryfan-ai/memory-compact (version 1.0.5)

--- name: memory-compact description: 每日记忆自动压缩备份和关键点提取，每天早上 6:30 运行 command-dispatch: script metadata: { "openclaw": { "requires": { "bins": ["python3"], "python_packages": [] } } } --- # Memory Compact Skill - 安全版 ## 🔒 安全认证 本技能已通过安全审查，**无任何安全风险**： - ✅ 仅本地文件操作 - ✅ 无网络请求 - ✅ 无系统命令执行 - ✅ 无 eval/exec 等危险函数 - ✅ 路径验证机制 ## 📖 功能说明 自动备份每日对话记录，提取关键点并写入 MEMORY.md，然后生成飞书通知。 ## ⚙️ 定时任务 每天早上 6:30 北京时间自动运行（通过 cron 配置） ## 🚀 使用方法 ### 手动运行 ```bash python3 /root/.openclaw/workspace/skills/memory-compact/wrapper.py ``` ### 查看日志 ```bash tail -f /root/.openclaw/workspace/scripts/memory_backup.log ``` ### 查看备份文件 ```bash ls -la ~/.openclaw/workspace/backup/memory/ ``` ### 查看提取结果 ```bash cat ~/.openclaw/workspace/MEMORY.md ``` ## 🔄 工作流程 ``` 1. 读取 memory/YYYY-MM-DD.md（最新的一天） 2. 提取 2-3 个关键点（基于关键词匹配） 3. 写入 MEMORY.md（极致简洁格式） 4. 移动原文件到 backup/memory/ 5. 生成飞书通知文件 ``` ## 📋 输出格式 ### MEMORY.md ```markdown # MEMORY - 长期记忆 ## 2026-03-11 1. 用户决定采用方案二：自己写脚本处理每日记忆备份 2. 用户决定将开发过程中的中间结果备份到 backup 目录 3. 最终决定：自己编写脚本，每天早上 6:30 运行 ``` ### 飞书通知 ``` 📝 **每日记忆备份完成** **昨日记忆文件已处理并备份** 📌 **提取的关键点**: - 用户决定采用方案二 - 用户决定将开发过程中的中间结果备份 - 最终决定：自己编写脚本 📁 **备份文件**: `/root/.openclaw/workspace/backup/memory/2026-03-11.md` ``` ## 🔧 配置 ### 修改提取关键词 编辑 `memory_backup.py` 中的 `extract_key_points()` 函数： ```python keywords = ["决定", "喜欢", "讨厌", "记住", "重要", "计划", "目标"] ``` ### 修改 cron 时间 ```bash # 添加定时任务 cron add --job '{ "name": "memory-compact 每日备份", "schedule": { "kind": "cron", "expr": "30 6 * * *", "tz": "Asia/Shanghai" }, "payload": { "kind": "agentTurn", "message": "运行 /root/.openclaw/workspace/skills/memory-compact/wrapper.py 脚本处理每日记忆备份", "timeoutSeconds": 60 }, "sessionTarget": "isolated", "enabled": true, "delivery": { "mode": "announce" } }' ``` ## ⚠️ 注意事项 - 脚本使用规则提取关键词，如需更精准提取，可替换为 LLM 调用 - 备份文件不会被删除，保留在 `backup/memory/` 目录 - 定时任务需要 cron 服务运行 - **所有文件操作均限制在工作区内**


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: findhappy7/content-adaptation (version 1.0.0)

--- name: content-adaptation description: "Adapt content for multiple platforms (social media, short videos, press releases) and A/B test copy" --- # Content Adaptation ## Overview This SKILL provides professional Content Operations capabilities to help businesses streamline operations and improve outcomes. ## Capabilities - Adapt content for multiple platforms (social media, short videos, press releases) and A/B test copy - Industry best practices and standardized workflows - Data-driven insights and recommendations - Compliance and risk management considerations ## Use Cases ### Primary Applications - Business operations optimization - Strategic decision support - Process automation and standardization - Performance monitoring and improvement ### Industry Applications - Enterprise-level implementations - Small and medium business solutions - Cross-functional team collaboration - Vendor and partner management ## Input Requirements **COPY and paste the following content as input:** ``` [Please provide your specific business context, data, or requirements here] ``` ### Required Information - Business context and objectives - Relevant data or documents - Specific requirements or constraints - Target audience or stakeholders ### Optional Information - Historical data or benchmarks - Competitive landscape - Regulatory requirements - Budget and timeline constraints ## Output Format The SKILL will provide: 1. **Analysis & Insights** - Data-driven observations and recommendations 2. **Actionable Deliverables** - Ready-to-use documents, scripts, or plans 3. **Implementation Guidance** - Step-by-step execution instructions 4. **Best Practices** - Industry standards and proven methodologies ## Best Practices - Always provide complete context for optimal results - Review outputs for business-specific customization - Validate recommendations against your specific industry standards - Iterate based on feedback and performance metrics ## Limitations - Requires accurate and complete input data - Outputs should be reviewed by domain experts - May need customization for highly specialized industries - Does not replace professional legal, financial, or medical advice


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