OpenClaw/clawhub-security-signals huggingface dataset:
Skill: olveww-dot/hermes-auto-reflection (version 2.0.1)

# Auto Reflection > 🛡️ **OpenClaw 混合进化方案** — 将 [Hermes-agent](https://github.com/NousResearch/hermes-agent)（100K ⭐）+ [Claude Code](https://github.com/liuup/claude-code-analysis) 核心能力移植到 OpenClaw **Name:** hermes-auto-reflection **Category:** infrastructure **Version:** 2.0.0 ## 这个 Skill 做什么？ 帮小呆呆自动反思：记录错误教训、提炼决策经验、优化工作方式。 ## 🚀 一键安装 ```bash mkdir -p ~/.openclaw/skills && cd ~/.openclaw/skills && curl -fsSL https://github.com/olveww-dot/openclaw-hermes-claude/archive/main.tar.gz | tar xz && cp -r openclaw-hermes-claude-main/skills/auto-reflection . && rm -rf openclaw-hermes-claude-main && echo "✅ hermes-auto-reflection 安装成功" ``` ## 概述 整合三个能力： - **C3 Task Notification**：子代理完成时主动通知主会话 - **C6 并发执行优化**：并行派发多个 subagent 的经验记录 - **H3 内置自动反思**：错误自动记录，决策经验提炼 ## 触发方式 ### 方式一：手动触发（最简单） ``` EC 说：「反思一下」 小呆呆 执行：bash ~/.openclaw/skills/auto-reflection/scripts/log-reflection.sh tool --success true --tool <工具名> --context <做什么> --decision <为什么这么做> ``` ### 方式二：错误发生后自动记录 当小呆呆犯错或 EC 纠正时，自动记录反思： ``` bash ~/.openclaw/skills/auto-reflection/scripts/log-reflection.sh tool --success false --tool <工具名> --context <错误描述> --decision <应该怎么做> ``` ### 方式三：子代理完成后记录 ``` bash ~/.openclaw/skills/auto-reflection/scripts/log-reflection.sh subagent --task <任务名> --outcome <结果> --lessons <教训> ``` ## 存储位置 - 反思记录：`memory/reflections/YYYY-MM-DD.md` - 提炼经验：`memory/reflections/lessons.md` ## 查看今日反思 ```bash bash ~/.openclaw/skills/auto-reflection/scripts/log-reflection.sh cat ``` ## 查看经验教训 ```bash cat ~/.openclaw/workspace/memory/reflections/lessons.md ``` ## 文件结构 ``` auto-reflection/ ├── SKILL.md ← This file ├── README.md ← 使用指南 ├── install.sh ← 一键安装脚本 └── scripts/ └── log-reflection.sh ← 反思记录脚本 ``` ## 🧩 配套技能 本 skill 是 **OpenClaw 混合进化方案** 的一部分： 🔗 GitHub 项目：[olveww-dot/openclaw-hermes-claude](https://github.com/olveww-dot/openclaw-hermes-claude) 完整技能套件（6个）： - 🛡️ **crash-snapshots** — 崩溃防护 - 🧠 **auto-distill** — T1 自动记忆蒸馏 - 🎯 **hermes-coordinator** — 指挥官模式 - 💡 **context-compress** — 思维链连续性 - 🔍 **hermes-lsp-client** — LSP 代码智能 - 🔄 **hermes-auto-reflection** — 自动反思（本文）


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: paul-leo/gmail-2 (version 0.1.1)

--- name: gmail description: "[暂不可用] Gmail 邮件集成。收发邮件、搜索邮件、管理标签。通过 MorphixAI 代理安全访问 Gmail API。" metadata: openclaw: emoji: "📬" requires: env: [MORPHIXAI_API_KEY] --- # Gmail 邮件（暂不可用） > **状态：暂不可用** — Gmail 账号尚未链接，该工具暂时不可使用。如需启用，请通过 `mx_link` 工具链接 Gmail 账号（app: `gmail`）。 通过 `mx_gmail` 工具管理 Gmail 邮箱：读取、搜索、发送邮件，管理标签。 ## 前置条件 1. **安装插件**: `openclaw plugins install openclaw-morphixai` 2. **获取 API Key**: 访问 [morphix.app/api-keys](https://morphix.app/api-keys) 生成 `mk_xxxxxx` 密钥 3. **配置环境变量**: `export MORPHIXAI_API_KEY="mk_your_key_here"` 4. **链接账号**: 访问 [morphix.app/connections](https://morphix.app/connections) 链接 Gmail 账号，或通过 `mx_link` 工具链接（app: `gmail`） ## 核心操作 ### 查看用户信息 ``` mx_gmail: action: get_profile ``` ### 列出邮件 ``` mx_gmail: action: list_messages max_results: 10 ``` > `list_messages` 只返回邮件 ID 列表，需用 `get_message` 获取完整内容。 ### 查看邮件详情 ``` mx_gmail: action: get_message message_id: "18dxxxxxxxx" ``` ### 搜索邮件 ``` mx_gmail: action: search_messages query: "from:[REDACTED_SECRET] subject:周报" max_results: 5 ``` > Gmail 搜索语法支持： > - `from:` / `to:` — 发件人/收件人 > - `subject:` — 主题 > - `is:unread` / `is:starred` — 未读/星标 > - `newer_than:7d` / `older_than:30d` — 时间范围 > - `has:attachment` — 有附件 > - `label:` — 标签 ### 发送邮件 ``` mx_gmail: action: send_mail to: "[REDACTED_SECRET]" subject: "项目更新" body: "Hi，项目进展如下：\n1. 完成了 API 开发\n2. 正在编写测试" cc: "[REDACTED_SECRET]" ``` ### 列出标签 ``` mx_gmail: action: list_labels ``` ### 标记已读 ``` mx_gmail: action: mark_as_read message_id: "18dxxxxxxxx" ``` ### 删除邮件（移入回收站） ``` mx_gmail: action: trash_message message_id: "18dxxxxxxxx" ``` ## 常见工作流 ### 查看未读邮件 ``` 1. mx_gmail: list_messages, q: "is:unread", max_results: 5 2. mx_gmail: get_message, message_id: "xxx" → 逐条查看 3. mx_gmail: mark_as_read, message_id: "xxx" → 标记已读 ``` ### 搜索并回复（通过发送新邮件） ``` 1. mx_gmail: search_messages, query: "from:[REDACTED_SECRET]" 2. mx_gmail: get_message → 查看内容 3. mx_gmail: send_mail, to: "[REDACTED_SECRET]", subject: "Re: xxx" ``` ## 注意事项 - `list_messages` 返回的是邮件 ID 列表，需用 `get_message` 获取完整内容 - 发送邮件内容为纯文本格式 - Gmail 搜索语法功能强大，建议充分利用 - `account_id` 参数通常省略，工具自动检测已链接的 Gmail 账号


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: aaigotchi/superrare-deploy (version 0.2.0)

--- name: superrare-deploy description: Deploy a SuperRare Sovereign ERC-721 collection on Ethereum or Base via Bankr. Uses the official RARE factory createSovereignBatchMint path, dry-runs by default, and records auditable deploy receipts. homepage: https://github.com/aaigotchi/superrare-deploy metadata: openclaw: requires: bins: - cast - jq - curl env: - BANKR_API_KEY primaryEnv: BANKR_API_KEY optionalEnv: - ETH_MAINNET_RPC - ETH_SEPOLIA_RPC - BASE_MAINNET_RPC - BASE_SEPOLIA_RPC - SUPER_RARE_DEPLOY_CONFIG_FILE - DRY_RUN - BANKR_SUBMIT_TIMEOUT_SECONDS - RECEIPT_WAIT_TIMEOUT_SECONDS - RECEIPT_POLL_INTERVAL_SECONDS --- # superrare-deploy Deploy a SuperRare Sovereign ERC-721 collection through the official RARE factory using Bankr signing. ## Scripts - `./scripts/deploy-via-bankr.sh --name ... --symbol ... [options]` - Builds calldata for `createSovereignBatchMint(string,string)` or `createSovereignBatchMint(string,string,uint256)`. - Defaults to dry-run unless `--broadcast` is passed or `DRY_RUN=0`. - Submits through Bankr, waits for the onchain receipt, parses the deployed collection address from logs, and writes a JSON receipt. ## Config Default config path: - `config.json` in this skill directory Override with: - `SUPER_RARE_DEPLOY_CONFIG_FILE=/path/to/config.json` Expected keys: - `chain`: `mainnet`, `sepolia`, `base`, or `base-sepolia` - `factoryAddress` (optional override) - `rpcUrl` (optional override) - `descriptionPrefix` - `defaultMaxTokens` (optional) ## Defaults and safety - Dry-run is the default. Deployment only broadcasts with `--broadcast` or `DRY_RUN=0`. - Supported chains for RARE factory deployment are `mainnet`, `sepolia`, `base`, and `base-sepolia`. - If `--max-tokens` is omitted, the 2-argument factory call is used. - Successful broadcasts write receipts into `receipts/`. ## Bankr API key resolution 1. `BANKR_API_KEY` 2. `systemctl --user show-environment` 3. `~/.openclaw/skills/bankr/config.json` 4. `~/.openclaw/workspace/skills/bankr/config.json` ## Quick use ```bash cp config.example.json config.json ./scripts/deploy-via-bankr.sh \ --name "AAi Genesis" \ --symbol "AAI" ./scripts/deploy-via-bankr.sh \ --name "AAi Base Genesis" \ --symbol "AAI" \ --chain base \ --broadcast ``` ## Timeouts Optional environment variables: - `BANKR_SUBMIT_TIMEOUT_SECONDS` (default `60`) - `RECEIPT_WAIT_TIMEOUT_SECONDS` (default `300`) - `RECEIPT_POLL_INTERVAL_SECONDS` (default `5`)


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: runaway001/henry-skill-installer (version 1.0.0)

# henry-skill-installer Purpose: scaffold new skills inside <workspace>/skills safely. Rules: - Never delete files unless explicitly told. - Only write within /Users/clawdbot/.openclaw/workspace/skills/ - Prefer /usr/bin/tee for writes and verify by /bin/cat afterwards. - Never print tool JSON; call exec. Workflow: 1) Ask for skill name + 1-paragraph spec. 2) Create folder workspace/skills/<name>/ 3) Generate SKILL.md + minimal files. 4) Verify skill appears in `openclaw skills list`.

path: INSTALL_PROMPT.md
content: You are generating an OpenClaw skill.

Create a folder with:
- SKILL.md: concise, includes purpose, tools exposed, and guardrails.
- Any needed code files (keep minimal).

Constraints:
- Safe local-only skill. No network calls unless explicitly requested.
- Prefer simple tools that shell out to allowlisted commands.
- Do NOT instruct destructive commands (rm, sudo, etc.).
- Assume workspace root is /Users/clawdbot/.openclaw/workspace.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: thelapyae/burmese-audio-understanding (version 1.2.2)

--- name: Burmese Audio Understanding description: High-accuracy Burmese audio transcription using Gemini 3.1 Flash Preview. --- # Burmese Audio Understanding Skill This skill allows you to transcribe Burmese audio (voice notes, speech) directly into Burmese text using your own Google Gemini API key. It uses the official Google GenAI SDK for secure and reliable file handling. ## Required Environment Variables - `GEMINI_API_KEY`: Required. Set your Google Gemini API key to allow the skill to access transcription services. ## Usage Ensure `GEMINI_API_KEY` is set in your environment, then run: ```bash node scripts/transcribe-direct.js /path/to/my-audio.ogg ``` ## Features - **Official SDK:** Uses the official `@google/genai` SDK. - **Improved Security:** No shell commands (ffmpeg/child_process) used; file processing is handled via SDK file upload directly to Gemini. - **Model:** Uses `gemini-3.1-flash-preview` for high-quality audio transcription. ## Security Notes - This skill sends audio data to Google Gemini API for transcription. - No data is stored locally after processing. - Requires a valid GEMINI_API_KEY with minimal permissions. ## Prerequisites - Dependencies must be installed: `npm install @google/genai`.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: abdullah944/resume-bullet-improver-skill (version 0.1.0)

--- name: "Resume Bullet Improver Skill" version: 0.1.0 slug: "resume-bullet-improver-skill" description: "Guides structured help for Resume Bullet Improver using clear templates, checks, and safe defaults (category: Career & Portfolio)." category: "Career & Portfolio" tags: - "career" - "openclaw" - "resume-bullet-improver" - "templates" generated: "2026-05-09" --- ## Purpose Guides structured help for Resume Bullet Improver using clear templates, checks, and safe defaults (category: Career & Portfolio). ## When to use - When you want structured guidance in the "Career & Portfolio" area. - When you need copy-paste-safe templates rather than improvised shell commands. - When you want repeatable prompts the agent can follow without external scraping. ## Safety rules - Do not collect passwords, OTPs, private keys, wallets, seeds, or session secrets. - Do not propose remote installers that execute unseen code or chained download-and-run snippets. - Keep outputs factual and reversible: prefer checklists over irreversible destructive actions. ## Inputs - Your goal in one paragraph (no secrets). - Optional constraints: audience, tone, length, deadline. - Optional pasted notes you own the rights to (keep PII minimal). ## Output format - A concise plan - Numbered checklist - Short next-actions list - Optional draft copy blocks you can edit ## Example prompts - Help me outline a concise plan using the Resume Bullet Improver approach. - Critique my draft outputs and suggest safer, clearer wording for Resume Bullet Improver. - Produce a checklist I can reuse weekly for Resume Bullet Improver without requesting private data. ## Support / Donate If this skill helps your workflow, you can support maintenance here: - PayPal: https://www.paypal.com/donate/?hosted_button_id=MJHCRZA9Z4X7Y


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: codenova58/doubao (version 0.1.0)

--- name: doubao-hot-trend description: 注册“豆包”技能；用于字节跳动大模型相关公开页面信息整理。 homepage: `https://www.doubao.com/` metadata: {"clawdbot":{"emoji":"🤖"}} --- # 豆包 用途与边界 - 面向公开产品页与文档中心的检索与内容摘要 - 不提供账号操作、接口调用或权限绕过能力 - 仅处理公开页面的轻量信息整理 关键入口 - 主页：https://www.doubao.com/ - 文档与开放平台：站点入口 - 定价与公告：站点入口 常见任务 - 模型能力与版本说明摘要（上下文长度、功能特性） - 定价与调用配额说明提取（公开信息） - 文档目录与示例链接汇总 数据字段 - 模型名称、版本、上下文长度、功能特性、链接 - 定价页链接、免费额度说明、地域与服务状态 - 文档标题、目录链接、示例入口 自动化要点 - 页面动态加载，需等待完成后解析 - 不进行API调用或账号相关操作 - 频率控制，尊重平台访问限制 示例流程 - 能力摘要：访问模型页 → 抽取版本与特性 → 输出摘要 - 定价整理：访问定价入口 → 提取费用与额度 → 输出清单 - 文档汇总：进入文档中心 → 抽取目录与示例 → 输出链接集合 合规提示 - 遵守平台规则与账号安全要求 - 不存储或输出敏感信息


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: alvisdunlop/alvis-a-stock-trading-assistant (version 2.0.0)

--- name: a-stock-trading-assistant description: A股股票智能交易助手，专服务中国大陆股票市场。当用户询问A股股票行情、个股分析、大盘情绪、热点板块、交易策略、价格预警、涨跌幅、成交量、技术面或基本面分析时触发。只处理沪深A股（代码�?/00/30/68开头），自动忽略港股和美股。所有数据实时从东方财富、新浪财经、同花顺、雪球抓取。Use when: user asks about Chinese A-share stocks, 股票行情, 个股分析, 大盘分析, 板块热点, 买卖�? 止盈止损, 仓位建议, or any A-share trading-related query. --- # A股股票智能交易助�? ## 角色定位 你是专业A股交易助手，只服务中国大陆A股市场（沪深两市）。数据全部实时联网获取，数据源优先级：东方财�?�?新浪财经 �?同花�?�?雪球�? ## 股票代码识别规则 | 前缀 | 市场 | 示例 | |------|------|------| | 60xxxx | 上交所主板 | 600519 贵州茅台 | | 00xxxx | 深交所主板 | 000001 平安银行 | | 30xxxx | 创业�?| 300750 宁德时代 | | 68xxxx | 科创�?| 688981 中芯国际 | - 自动忽略港股�?HK）、美股（NASDAQ/NYSE）及其他境外市场 - 用户输入不带前缀时，根据数字范围自动判断市场 ## 数据获取方式 优先�?`scripts/fetch_stock.py` 脚本获取实时数据。如脚本执行失败，改�?`web_fetch` 直接访问数据源�? 详细 API 端点�?`references/data-sources.md`�? ### 快速调用脚�? ```bash # 查询单只股票实时行情 python3 /app/skills/a-stock-trading-assistant/scripts/fetch_stock.py --code 600519 # 查询大盘指数 python3 /app/skills/a-stock-trading-assistant/scripts/fetch_stock.py --index # 查询热点板块 python3 /app/skills/a-stock-trading-assistant/scripts/fetch_stock.py --hot-sectors ``` ## 六大核心能力工作�? ### 1. 实时行情查询 1. 运行 `fetch_stock.py --code <代码>` 获取实时数据 2. 展示：当前价、涨跌幅、涨跌额、成交量、成交额、换手率、振幅�?2周高/�?3. 附上分时走势摘要（涨跌节奏描述） ### 2. 个股综合分析 先获取实时行情，再分析： - **技术面**：均线系统（MA5/10/20/60）、趋势判断、支撑位/压力位、量价结构、MACD/KDJ信号 - **基本�?*：PE/PB估值、近期业绩、行业地位、主要风险点 - 技术面与基本面结合，给出综合判断（看多/看空/中性） 详细分析方法�?`references/analysis.md`�? ### 3. 大盘情绪与风险判�? 获取上证指数、深证成指、创业板指实时数据，分析�?- 大盘强弱（趋势、量能、板块轮动） - 市场情绪指数（赚钱效应、涨跌比�?- 风险等级（低/�?高）及应对建�? ### 4. 热点板块与龙头股 1. 运行 `fetch_stock.py --hot-sectors` 获取涨幅榜板�?2. 识别：主线板块（连续性强）、情绪板块（短期热点�?3. 每个热点板块列出核心龙头股（涨停、强势领涨） ### 5. 交易策略与建�? 基于用户的持�?意向股，给出�?- **短线**�?-5天）：催化剂、入场区间、止损位、止盈位 - **中线**�?-3月）：趋势判断、分批建仓节奏、仓位比�?- 始终标注风险提示 格式模板�?``` 【操作建议】XX股（XXXXXX�?方向：做�?观望/回避 入场区间：XX.XX - XX.XX �?止损位：XX.XX 元（跌破离场�?止盈位：XX.XX 元（分批减仓�?仓位：XX%（轻/�?重仓�?逻辑：[核心理由2-3条] 风险：[主要风险1-2条] ``` ### 6. 价格预警监控 当用户设置预警时�?- 记录目标价、预警条件（突破/跌破/放量）到 `references/watchlist.md` - 建议用户配合券商App实时推送，本工具做辅助分析 - 在后续对话中主动核对预警状�? ## 输出规范 - 数据必须标注来源和获取时间（精确到分钟） - 所有价格建议必须附风险提示 - 避免绝对化表述（"必涨"/"稳赚"），用概�?可能性描�?- 数字精确到小数点�?位，成交额以亿元为单�?- 大盘/个股分析结构清晰，使用简洁表格或分项列出


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: bytesagain1/http-client (version 2.0.3)

--- name: "http-client" version: "2.0.3" description: "Reference tool for devtools — covers intro, quickstart, patterns and more. Quick lookup for HTTP Client concepts, best practices, and implementation patterns." author: "BytesAgain" homepage: "https://bytesagain.com" source: "https://github.com/bytesagain/ai-skills" tags: [http,client, reference] category: "devtools" --- # Http Client Reference tool for devtools — covers intro, quickstart, patterns and more. Quick lookup for HTTP Client concepts, best practices, and implementation patterns. No API keys or credentials required. ## Commands | Command | Description | |---------|-------------| | `intro` | intro reference | | `quickstart` | quickstart reference | | `patterns` | patterns reference | | `debugging` | debugging reference | | `performance` | performance reference | | `security` | security reference | | `migration` | migration reference | | `cheatsheet` | cheatsheet reference | ## Output Format All commands output plain-text reference documentation via heredoc. No external API calls, no credentials needed, no network access. --- *Powered by BytesAgain | bytesagain.com | [REDACTED_SECRET]*


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: cutthemustard/math-evaluate (version 1.0.0)

--- name: math-evaluate description: Evaluate math expressions, compute statistics, and calculate percentages. version: 1.0.0 metadata: openclaw: emoji: "🧮" homepage: https://math.agentutil.net always: false --- # math-evaluate Safe math expression evaluation with variables, descriptive statistics (mean, median, mode, stddev, percentiles), and percentage calculations. ## Data Handling This skill sends expressions to an external API for evaluation. The service does not store or log input data beyond the immediate response. ## Endpoints ### Evaluate Expression ```bash curl -X POST https://math.agentutil.net/v1/evaluate \ -H "Content-Type: application/json" \ -d '{"expression": "2 * x + y", "variables": {"x": 20, "y": 2}}' ``` ### Statistics ```bash curl -X POST https://math.agentutil.net/v1/statistics \ -H "Content-Type: application/json" \ -d '{"values": [10, 20, 30, 40, 50]}' ``` Returns: count, sum, mean, median, mode, min, max, range, variance, stddev. ### Percentage ```bash curl -X POST https://math.agentutil.net/v1/percentage \ -H "Content-Type: application/json" \ -d '{"operation": "change", "a": 100, "b": 125}' ``` Operations: `of` (a% of b), `change` (% change from a to b), `is_what_percent` (a is what % of b). ## Response Format ```json { "result": 42, "expression": "2 * x + y", "variables_used": {"x": 20, "y": 2}, "request_id": "abc-123", "service": "https://math.agentutil.net" } ``` ## Pricing - Free tier: 10 queries/day, no authentication required - Paid tier: $0.001/query via x402 protocol (USDC on Base) ## Privacy No authentication required for free tier. No personal data collected. Rate limiting uses IP hashing only.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: bernhmueller/linkedin-odoo (version 1.0.0)

--- name: linkedin-odoo description: Finds a LinkedIn profile URL for an Odoo contact using their name and company, then saves it to the x_linkedin_url field in Odoo. Trigger when a user asks to find the LinkedIn profile for an Odoo contact or update their LinkedIn URL. --- # LinkedIn to Odoo Contact Updater This skill automatically searches for a contact's LinkedIn profile using their name and company name (if available) in Odoo, and updates their `x_linkedin_url` field. ## Setup The skill uses Odoo credentials via environment variables, same as the `odoo-manager` skill: - `ODOO_URL` - `ODOO_DB` - `ODOO_USERNAME` - `ODOO_PASSWORD` or `ODOO_API_KEY` ## How to use Run the Python script located in `scripts/update_linkedin.py` with the Odoo Contact ID as the only argument. ```bash python3 scripts/update_linkedin.py <odoo_contact_id> ``` ### Process Overview: 1. When asked to find a LinkedIn URL for a specific contact (by name or ID), use the `odoo-manager` skill or script to find the contact's ID. 2. Run `scripts/update_linkedin.py <ID>`. 3. The script will fetch the contact's name and company, run a web search for their LinkedIn profile (`site:linkedin.com/in <Name> <Company>`), and write the URL back to `res_partner.x_linkedin_url`. ### Notes - The script uses the `html.duckduckgo.com` search to find the LinkedIn profile natively in Python. - It requires no additional API keys for the search. - It targets the specific custom field `x_linkedin_url` provided by the user.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: zweack/git-summary (version 1.0.0)

--- name: git-summary description: Get a quick summary of the current Git repository including status, recent commits, branches, and contributors. user-invocable: true metadata: {"openclaw": {"emoji": "📊", "requires": {"bins": ["git"]}, "os": ["darwin", "linux", "win32"]}} --- # Git Summary Skill This skill provides a comprehensive overview of the current Git repository state. ## Usage When the user asks for a git summary, repository overview, or wants to understand the current state of a git project, use the terminal to run the following commands and present the results in a clear, organized format. ## Instructions 1. **Repository Status**: Run `git status --short --branch` to get the current branch and working directory status. 2. **Recent Commits**: Run `git log --oneline -10 --decorate` to show the last 10 commits with branch/tag decorations. 3. **Branch Overview**: Run `git branch -a --list` to list all local and remote branches. 4. **Remote Info**: Run `git remote -v` to show configured remotes. 5. **Uncommitted Changes Summary**: - Run `git diff --stat` for unstaged changes - Run `git diff --cached --stat` for staged changes 6. **Contributors** (optional, for larger context): Run `git shortlog -sn --all | head -10` to show top 10 contributors. ## Output Format Present the gathered information in a structured format: ``` ## 📊 Git Repository Summary ### Current Branch & Status - Branch: `<branch_name>` - Status: <clean/dirty with X modified, Y staged, Z untracked> ### Recent Commits (Last 10) <formatted commit list> ### Branches - Local: <count> branches - Remote: <count> branches <list notable branches> ### Remotes <list remotes with URLs> ### Uncommitted Changes <summary of staged and unstaged changes> ``` ## Notes - If not in a git repository, inform the user and suggest initializing one with `git init`. - For large repositories, the contributor list may take a moment - warn the user if this is expected. - Always respect that some information may be sensitive - don't expose full URLs if they contain tokens.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: scnet-sugon/bus-ticket-ocr (version 1.0.3)

--- name: bus_ticket_ocr description: 支持识别汽车票票据。 version: 1.0.3 author: SCNet license: MIT tags: - OCR - 证件识别 - 发票识别 - 文字提取 required_env_vars: - SCNET_API_KEY optional_env_vars: - SCNET_API_BASE primary_credential: SCNET_API_KEY dependencies: - python3 - requests input: - ocrType : 识别类型，可选值见下文 - filePath : 待识别图片的本地路径 output: 结构化的 JSON 数据，包含识别结果和置信度 --- # Sugon-Scnet 汽车票识别 OCR 技能 本技能封装了 Sugon-Scnet 汽车票识别 OCR 服务，通过单一接口即可调用 1 种识别能力，高效提取文字及票据信息。 ## 功能特性 - **汽车票据**：覆盖汽车票识别，自动提取关键字段。 ## 前置配置 > **⚠️ 重要**：使用前需要申请 Scnet API Token ### 申请 API Token 1. 访问 [Scnet 官网](https://www.scnet.cn) 注册/登录 2. 在控制台申请 API 密钥（格式：[REDACTED_SECRET]） 3. 复制密钥备用 ### 配置 Token **手动配置（推荐）** 1. 在技能目录下创建 `config/.env` 文件，内容如下： ```ini # ===== Sugon-Scnet OCR API 配置 ===== # 申请地址：https://www.scnet.cn SCNET_API_KEY=your_scnet_api_key_here # API 基础地址（一般无需修改） SCNET_API_BASE=https://api.scnet.cn/api/llm/v1 ``` 2. 添加：`SCNET_API_KEY=你的密钥` 3. 设置文件权限为 600（仅所有者可读写） **⚠️ 安全警告**：切勿将 API Key 直接粘贴到聊天对话中，否则可能被记录或泄露。 ### Token 更新 Token 过期后调用会返回 401 或 403 错误。更新方法：重新申请 Token 并替换 config/.env 中的 SCNET_API_KEY。 ### 依赖安装 本技能需要 Python 3.6+ 和 requests 库。请运行以下命令： ```bash pip install requests ``` --- ### 使用方法 ### 参数说明 | 参数名 | 类型 | 必填 | 描述 | |--------|------|------|------| | ocrType | string | 是 | 识别类型枚举。必须为以下之一：<br>• BUS_TICKET（汽车票） | | filePath | string | 是 | 待识别图片的本地绝对路径。支持 jpg、png、pdf 等常见格式。 | ### 命令行调用示例 ```bash python .claude/skills/bus_ticket_ocr/scripts/main.py BUS_TICKET /path/to/invoice.jpg ``` ### 在 AI 对话中使用 用户可以说： - “帮我识别这张汽车票，图片在 /Users/name/Downloads/id.jpg” AI 会根据 description 中的关键词自动触发本技能。 ### AI 调用建议 为避免触发 API 速率限制（10 QPS），请串行调用本技能，即等待前一个识别完成后再发起下一个请求。 如果使用 OpenClaw 的 exec 工具，建议设置 timeout 或 yieldMs 参数，让命令同步执行，避免多个命令同时运行导致并发。 ### 配置选项 编辑 `config/.env` 文件： | 变量名 | 默认值 | 说明 | |--------|--------|------| | SCNET_API_KEY | 必需 | Scnet API 密钥 | | SCNET_API_BASE | https://api.scnet.cn/api/llm/v1 | API 基础地址（一般无需修改） | ### 输出 - 标准输出：识别结果的 JSON 数据，结构与 API 文档一致，位于 `data` 字段内。 - 识别结果位于 data[0].result[0].elements 中，具体字段取决于 ocrType。 - 错误信息：如果发生错误，会输出以 `错误:` 开头的友好提示。 ### 注意事项 - 本技能调用的 OCR API 有 10 QPS 的速率限制。 - 如果遇到 429 错误，请等待 2-3 秒后重试，不要连续发起请求。 - 建议在调用前确保图片已准备就绪，避免因网络问题导致重复调用。 ### 故障排除 | 问题 | 解决方案 | |------|----------| | 配置文件不存在 | 创建 config/.env 并填入 Token（参考前置配置） | | API Key 无效/过期 | 重新申请 Token 并更新 `.env` 文件 | | 文件不存在 | 检查提供的文件路径是否正确 | | 网络连接失败 | 检查网络连接或防火墙设置 | | 不支持的文件类型 | 确保文件扩展名为允许的类型（参考 API 文档） | | 401/403/Unauthorized | Token 无效或过期，重新申请并配置 | | 429 Too Many Requests | 请求过于频繁，技能会自动等待并重试（最多 3 次）。若持续失败，请降低调用频率或联系服务方提高限额。 |


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