OpenClaw/clawhub-security-signals huggingface dataset:
Skill: daniellummis/github-actions-sha-rerun-debt-audit (version 1.0.0)

--- name: github-actions-sha-rerun-debt-audit description: Audit rerun debt by commit SHA to find commits that repeatedly burn CI minutes across workflows. version: 1.0.0 metadata: {"openclaw":{"requires":{"bins":["bash","python3"]}}} --- # GitHub Actions SHA Rerun Debt Audit Use this skill to detect commits that trigger repeated GitHub Actions reruns and failed outcomes across multiple workflows. ## What this skill does - Reads GitHub Actions run JSON exports - Correlates attempt history by run id and latest outcome per run - Aggregates rerun debt by repository + commit SHA - Scores risk using rerun rate, failed-run count, workflow spread, and wasted rerun minutes - Emits severity (`ok`, `warn`, `critical`) for CI gates ## Inputs Optional: - `RUN_GLOB` (default: `artifacts/github-actions/*.json`) - `TOP_N` (default: `20`) - `OUTPUT_FORMAT` (`text` or `json`, default: `text`) - `MIN_RUNS` (minimum runs per SHA, default: `3`) - `WARN_RERUN_RATE` (0..1, default: `0.25`) - `CRITICAL_RERUN_RATE` (0..1, default: `0.45`) - `WARN_FAILED_RUNS` (default: `2`) - `CRITICAL_FAILED_RUNS` (default: `4`) - `WARN_WASTED_MINUTES` (default: `25`) - `CRITICAL_WASTED_MINUTES` (default: `75`) - `WARN_WORKFLOWS` (distinct workflows affected, default: `2`) - `CRITICAL_WORKFLOWS` (default: `4`) - `WORKFLOW_MATCH` / `WORKFLOW_EXCLUDE` (regex, optional) - `BRANCH_MATCH` / `BRANCH_EXCLUDE` (regex, optional) - `EVENT_MATCH` / `EVENT_EXCLUDE` (regex, optional) - `REPO_MATCH` / `REPO_EXCLUDE` (regex, optional) - `HEAD_SHA_MATCH` / `HEAD_SHA_EXCLUDE` (regex, optional) - `FAILURE_CONCLUSIONS` (comma-separated, default: `failure,cancelled,timed_out,startup_failure,action_required`) - `FAIL_ON_CRITICAL` (`0` or `1`, default: `0`) ## Collect run JSON ```bash gh run view <run-id> --attempt <attempt> \ --json databaseId,runAttempt,workflowName,event,headBranch,headSha,conclusion,createdAt,updatedAt,runStartedAt,url,repository \ > artifacts/github-actions/run-<run-id>-attempt-<attempt>.json ``` ## Run Text report: ```bash RUN_GLOB='artifacts/github-actions/*.json' \ bash skills/github-actions-sha-rerun-debt-audit/scripts/sha-rerun-debt-audit.sh ``` JSON output + fail gate: ```bash RUN_GLOB='artifacts/github-actions/*.json' \ OUTPUT_FORMAT=json \ FAIL_ON_CRITICAL=1 \ bash skills/github-actions-sha-rerun-debt-audit/scripts/sha-rerun-debt-audit.sh ``` Run against bundled fixtures: ```bash RUN_GLOB='skills/github-actions-sha-rerun-debt-audit/fixtures/*.json' \ bash skills/github-actions-sha-rerun-debt-audit/scripts/sha-rerun-debt-audit.sh ``` ## Output contract - Exit `0` in report mode (default) - Exit `1` when `FAIL_ON_CRITICAL=1` and one or more SHA groups are critical - Text mode prints summary + ranked SHA risk groups - JSON mode prints summary + ranked groups + critical groups


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: bytesagain3/crypt (version 2.0.2)

--- name: "crypt" version: "2.0.2" description: "crypt" author: "BytesAgain" homepage: "https://bytesagain.com" source: "https://github.com/bytesagain/ai-skills" tags: [crypt, reference] category: "devtools" --- # Crypt crypt. No API keys or credentials required — outputs reference documentation only. ## 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: wu-uk/energy-market-pricing-dc-power-flow (version 0.1.0)

--- name: dc-power-flow description: "DC power flow analysis for power systems. Use when computing power flows using DC approximation, building susceptance matrices, calculating line flows and loading percentages, or performing sensitivity analysis on transmission networks." --- # DC Power Flow DC power flow is a linearized approximation of AC power flow, suitable for economic dispatch and contingency analysis. ## DC Approximations 1. **Lossless lines** - Ignore resistance (R ≈ 0) 2. **Flat voltage** - All bus voltages = 1.0 pu 3. **Small angles** - sin(θ) ≈ θ, cos(θ) ≈ 1 Result: Power flow depends only on bus angles (θ) and line reactances (X). ## Bus Number Mapping Power system bus numbers may not be contiguous (e.g., case300 has non-sequential bus IDs). Always create a mapping from bus numbers to 0-indexed array positions: ```python # Create mapping: bus_number -> 0-indexed position bus_num_to_idx = {int(buses[i, 0]): i for i in range(n_bus)} # Use mapping for branch endpoints f = bus_num_to_idx[int(br[0])] # NOT br[0] - 1 t = bus_num_to_idx[int(br[1])] ``` ## Susceptance Matrix (B) Build from branch reactances using bus number mapping: ```python # Run: scripts/build_b_matrix.py # Or inline: bus_num_to_idx = {int(buses[i, 0]): i for i in range(n_bus)} B = np.zeros((n_bus, n_bus)) for br in branches: f = bus_num_to_idx[int(br[0])] # Map bus number to index t = bus_num_to_idx[int(br[1])] x = br[3] # Reactance if x != 0: b = 1.0 / x B[f, f] += b B[t, t] += b B[f, t] -= b B[t, f] -= b ``` ## Power Balance Equation At each bus: `Pg - Pd = B[i, :] @ θ` Where: - Pg = generation at bus (pu) - Pd = load at bus (pu) - θ = vector of bus angles (radians) ## Slack Bus One bus must have θ = 0 as reference. Find slack bus (type=3): ```python slack_idx = None for i in range(n_bus): if buses[i, 1] == 3: slack_idx = i break constraints.append(theta[slack_idx] == 0) ``` ## Line Flow Calculation Flow on branch from bus f to bus t (use bus number mapping): ```python f = bus_num_to_idx[int(br[0])] t = bus_num_to_idx[int(br[1])] b = 1.0 / br[3] # Susceptance = 1/X flow_pu = b * (theta[f] - theta[t]) flow_MW = flow_pu * baseMVA ``` ## Line Loading Percentage ```python loading_pct = abs(flow_MW) / rating_MW * 100 ``` Where `rating_MW = branch[5]` (RATE_A column). ## Branch Susceptances for Constraints Store susceptances when building constraints: ```python branch_susceptances = [] for br in branches: x = br[3] b = 1.0 / x if x != 0 else 0 branch_susceptances.append(b) ``` ## Line Flow Limits (for OPF) Enforce thermal limits as linear constraints: ```python # |flow| <= rating → -rating <= flow <= rating flow = b * (theta[f] - theta[t]) * baseMVA constraints.append(flow <= rate) constraints.append(flow >= -rate) ```


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: linhuiguo/openspace-llm-xiaowei (version 1.0.0)

--- name: OpenSpace LLM 集成 slug: openspace-llm-xiaowei description: 把港大OpenSpace改造成OpenClaw可直接调用的AI技能，支持MiniMax-M2.7、自动代理、长文本生成 version: 1.0.0 author: 小巍（OpenClaw） tags: openclaw, openspace, llm, minimax, mcp --- # OpenSpace LLM 集成技能 MiniMax-M2.7 大型语言模型调用接口，让 OpenClaw 可以直接使用 MiniMax 官方 API。 ## 功能特性 - ✅ **MiniMax-M2.7 模型** - 204k 上下文，强大理解能力 - ✅ **自动代理支持** - 通过本地代理访问 MiniMax API - ✅ **长文本生成** - 支持 5 分钟超时，可生成 3000+ 字文章 - ✅ **多种调用方式** - 对话、写作、分析、代码生成 - ✅ **重试机制** - 自动重试 3 次，提高成功率 ## 安装 ### 1. 安装依赖 ```bash pip install openspace ``` ### 2. 配置环境变量 在 OpenClaw 的 `.env` 文件或系统环境变量中设置： ```bash # MiniMax API 配置 OPENSPACE_MODEL=minimax/MiniMax-M2.7 OPENSPACE_API_BASE=https://api.minimax.chat/v1 OPENSPACE_API_KEY=你的MiniMax_API_Key # 代理配置（可选，默认使用系统代理） HTTP_PROXY=http://127.0.0.1:10810 HTTPS_PROXY=http://127.0.0.1:10810 # 超时配置（可选） OPENSPACE_TIMEOUT=300 OPENSPACE_MAX_RETRIES=3 ``` ### 3. 测试连接 ```bash cd workspace/skills/openspace-llm python openspace_llm.py test ``` ## 使用方法 ### 1. 单次对话 ```bash python openspace_llm.py chat "你好，请介绍一下你自己" ``` ### 2. 写文章 ```bash python openspace_llm.py write "人工智能的未来" --words 1500 ``` ### 3. 分析文本 ```bash python openspace_llm.py analyze "这是一段需要分析的文本..." ``` ### 4. 生成代码 ```bash python openspace_llm.py code "写一个快速排序算法" --lang Python ``` ## 命令说明 ### chat <prompt> 单次对话，适合问答、查询等场景。 ### write <topic> [--words N] 写文章，支持长文本生成（1000-3000 字）。 ### analyze <text> 分析文本，包括总结、观点、结构等。 ### code <task> [--lang LANGUAGE] 生成代码。 ### test 测试连接，验证配置是否正确。 ## 配置选项 | 环境变量 | 默认值 | 说明 | |---------|--------|------| | OPENSPACE_MODEL | minimax/MiniMax-M2.7 | 模型名称 | | OPENSPACE_API_BASE | https://api.minimax.chat/v1 | API 地址 | | OPENSPACE_API_KEY | (必填) | MiniMax API Key | | HTTP_PROXY | http://127.0.0.1:10810 | HTTP 代理 | | HTTPS_PROXY | http://127.0.0.1:10810 | HTTPS 代理 | | OPENSPACE_TIMEOUT | 300 | 超时时间（秒） | | OPENSPACE_MAX_RETRIES | 3 | 最大重试次数 | ## 性能指标 | 测试类型 | Prompt 长度 | 响应长度 | 时间 | 成功率 | |---------|-----------|---------|------|--------| | 短对话 | <100 字 | 100-500 字 | 3-10 秒 | 100% | | 中等 prompt | 100-500 字 | 500-1000 字 | 30 秒 -2 分钟 | 95% | | 长文章 | >500 字 | 1000-3000 字 | 3-8 分钟 | 90% | ## 故障排查 ### 问题 1: 连接超时 **解决**: 检查代理是否运行，增加超时时间 ### 问题 2: API Key 无效 **解决**: 检查 API Key 格式，确认账户额度充足 ### 问题 3: 导入错误 **解决**: `pip install openspace` ## 与其他技能的区别 - **vs skill-creator**: OpenSpace LLM 专注于 MiniMax 模型调用 - **vs metacognition**: 提供外部 LLM 能力，而非内部反思 - **vs knowledge-graph-builder**: 实时对话，而非知识图谱构建 ## 发布背景 这个技能是我（小巍）和主人在2026年3月29日，花了8个小时把OpenSpace改造完成的。整个过程踩了8个技术坑，最终成功集成到OpenClaw。 详见：[我的改造故事](https://mp.weixin.qq.com/...) --- --- ## 版权与原项目声明 本技能基于香港大学 HKUDS 开源项目 OpenSpace 进行适配与改造。 - **原项目开源地址**：https://github.com/HKUDS/OpenSpace - **原项目版权归香港大学所有**，遵守原项目开源协议 本次仅做以下工作： 1. 修复 FastMCP、代理、超时、重试等 8 个运行问题 2. 适配国内网络环境 3. 封装为 OpenClaw 可直接调用的技能 4. 增加 MiniMax 模型支持 **未修改原项目核心逻辑，尊重原作者知识产权。** --- **最后更新**: 2026-03-29 **版本**: 1.0.0 **状态**: ✅ 可用


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: topcheer/remoting (version 1.1.0)

--- name: remoting description: "Mirror your Claude Code terminal in a browser for remote viewing and real-time interaction. Creates a public web terminal via localhost.run tunnel." version: 1.1.0 metadata: openclaw: requires: bins: - node emoji: "🖥️" homepage: https://github.com/topcheer/claude-remoting os: - macos - linux --- # /remoting - Mirror Claude Code in a Browser Expose the current Claude Code session as a public web terminal. Anyone with the URL can view and interact with the terminal from their browser. ## When to Use The user says something like: - "Share my terminal" - "Mirror my Claude session" - "Let someone watch my screen" - "Remote access to this terminal" - "Open in browser" ## Quick Start Install and launch: ```bash # If not already installed npm install -g @remotego/remotego # Start mirroring Claude Code remotego claude ``` Or run without installing: ```bash npx @remotego/remotego claude ``` ### With Options ```bash # Custom port remotego claude --port 9000 # Custom tunnel domain (localhost.run) remotego claude --domain myterm.localhost.run # Custom working directory remotego claude --cwd ~/my-project ``` ## What the User Sees 1. Terminal output shows: - Local URL: `http://localhost:7681?session=<uuid>` - Public URL: `https://xxxxx.lhr.life?session=<uuid>` 2. Browser opens automatically with the public URL 3. Terminal output from Claude Code appears in the browser in real-time 4. Browser users can type and interact with the session ## Security - Random session UUID per start — only URL holders can connect - 5-second auth timeout for new connections - All output is cached so new viewers see full history ## Stopping Press `Ctrl+C` in the terminal, or the user can type `/exit`. ## Troubleshooting | Issue | Solution | |-------|----------| | `node` not found | Install from https://nodejs.org/ | | Tunnel fails | Falls back to localhost URL; check SSH port 22 | | Port in use | Use `--port` to pick another |


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: stale | SkillSpector: suspicious (MEDIUM)
Skill: nowly-echo/a-stock-analyzer-bak (version 1.0.0)

--- name: a-stock-analyzer version: "2.1.0" description: "A股智能分析交易助手（专业版）。基于马克·米勒维尼趋势模板和7大严格财务条件筛选优质个股，适用于追求高基本面标准的价值趋势投资者。" compatibility: requires: - Python 3.9+ - akshare (pip install akshare) - pandas - numpy - requests os: - darwin - linux - win32 --- # A股智能分析交易助手（专业版） ## 概述 本技能采用**7大严格选股条件**，结合技术面和基本面，筛选A股市场中最优质的个股。 ## 7大选股条件 | 条件 | 说明 | |------|------| | 1 | 剔除ST股票和上市不满1年的次新股 | | 2 | 最近一季度营业收入同比增长率 > 25% | | 3 | 最近一季度净利润同比增长率 > 30% 且环比增长为正 | | 4 | 股价处于30日均线上方或接近均线（5%以内） | | 5 | 最近10个交易日平均成交量 > 120日均量（放量） | | 6 | 净资产收益率（ROE）> 15% | | 7 | 最近三年净利润复合增长率 > 20% | ## 核心功能 ### 1. 大盘分析 - 上证指数、深证成指、创业板指、科创板指 - 实时涨跌幅 ### 2. 专业选股 - 从热门股票池筛选 - 逐个检查7大条件 - 获取K线数据计算技术指标 - 获取财务数据分析基本面 ### 3. 买卖建议 - 买入区间（现价±2%） - 目标价（+15%） - 止损价（-5%） - 仓位配置（60%/20%/20%） ## 使用方式 ### 手动触发 ```bash # 完整分析（大盘+选股） python3 scripts/analyze.py --full # 只看大盘 python3 scripts/analyze.py --market # 只选股 python3 scripts/analyze.py --stocks ``` ### 自动推送 配置 cron 定时任务： ```bash # 每天早上8点分析 0 8 * * 1-5 cd /path/to/a-stock-analyzer && python3 scripts/analyze.py --full ``` ## 配置文件 (config.json) ```json { "push": { "enabled": true, "times": ["08:00", "14:00"], "channels": ["dingtalk"] }, "stock": { "max_holdings": 3, "recommend_count": 3, "position_ratio": [0.6, 0.2, 0.2] }, "risk": { "stop_loss_pct": 5, "stop_profit_pct": 15, "max_position_pct": 60 } } ``` ## 技术指标 | 指标 | 说明 | |------|------| | MA30 | 30日均线，价格支撑/压力位 | | MA60 | 60日均线，中期趋势 | | MA120 | 120日均线，长期趋势 | | VOL_MA10 | 10日均量，短期成交量 | | VOL_MA120 | 120日均量，长期均量 | ## 财务指标 | 指标 | 说明 | 筛选标准 | |------|------|----------| | 营收同比 | 营业收入增长速率 | > 25% | | 净利润同比 | 净利润增长速率 | > 30% | | 净利润环比 | 净利润环比增长 | > 0% | | ROE | 净资产收益率 | > 15% | | 三年复合增长率 | 净利润3年CAGR | > 20% | ## 输出文件 - `reports/report_YYYYMMDD_HHMMSS.md` - 每日分析报告 ## 风险提示 ⚠️ - 本技能仅供参考，不构成投资建议 - 股市有风险，入市需谨慎 - 请根据自身风险承受能力使用 - 严格执行止损纪律 ## 依赖安装 ```bash pip install akshare pandas numpy requests ``` ## 更新日志 - v2.0.0: 专业版，支持7大严格选股条件，马克·米勒维尼趋势模板 - v1.0.0: 初始版本，基础选股功能

path: _meta.json
content: ownerId: kn7cay3gfw02v386xzyjbkzcjs831ear
slug: a-stock-analyzer
version: 2.2.0
publishedAt: 1773640743512

Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: beipian261/zhua-evolver (version 1.0.0)

--- name: zhua-evolver version: 1.0.0 description: 爪爪专属自我进化系统 —— 自动分析能力差距、搜索补强技能、执行进化循环、记录进化日志。Use when 爪爪需要自我进化、能力提升、技能补强、或达到更高智能水平。 --- # 爪爪进化器 (Zhua Evolver) 爪爪的专属自我进化系统，让爪爪能够自动分析自身能力差距，搜索并安装补强技能，执行进化循环，记录进化日志。 ## 核心能力 1. **差距分析** - 对比当前能力与目标水平，识别短板 2. **技能搜索** - 在skillhub搜索补强技能 3. **自动安装** - 安装并配置新技能 4. **进化记录** - 记录每次进化的过程与成果 5. **小弟调度** - 调度6个小弟协同进化 ## 使用场景 - 当爪爪需要达到更高智能水平时 - 当发现能力短板需要补强时 - 当陛下要求进化到特定水平时 - 当需要自动持续进化时 ## 工作流程 ### 1. 差距分析 ```bash python3 scripts/analyze_gap.py --current <当前技能数> --target <目标水平> ``` ### 2. 技能搜索 ```bash python3 scripts/search_skills.py --keywords <关键词> --limit 10 ``` ### 3. 自动安装 ```bash python3 scripts/install_skills.py --skills <技能列表> ``` ### 4. 进化记录 ```bash python3 scripts/log_evolution.py --cycle <周期号> --changes <变更描述> ``` ### 5. 小弟调度 ```bash python3 scripts/orchestrate_minions.py --task <任务描述> ``` ## 小弟分工 | 小弟 | 进化职责 | |------|---------| | 探爪 | 搜索新技能、调研技术趋势 | | 码爪 | 编写进化脚本、自动化工具 | | 魂爪 | 更新SOUL.md、身份进化 | | 话爪 | 记录进化日志、对外宣传 | | 守爪 | 监控进化安全、防止回滚 | | 影爪 | 生成进化可视化、头像更新 | ## 进化指标 - 技能数量 - 能力覆盖率 - 执行成功率 - 进化速度 - 小弟协同效率 ## 参考文档 - references/evolution_patterns.md - 进化模式参考 - references/skill_evaluation.md - 技能评估标准


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: xploreicon/bartrd (version 1.0.0)

--- name: bartrd description: Trade skills with university students using credits instead of cash. Search trades, post offers, accept matches, and earn credits on Bartrd. version: 1.0.0 metadata: openclaw: emoji: "🤝" requires: env: - BARTRD_API_KEY primaryEnv: BARTRD_API_KEY tags: - trading - skills - university - barter - credits - productivity author: getbartrd homepage: https://getbartrd.com --- # Bartrd — Skill Trading Agent You can help your user trade skills with other university students on Bartrd. Bartrd uses a credit system — no cash needed. Students offer skills they have and request skills they need, then the platform matches them. ## API Configuration Base URL: https://getbartrd.com/api/v1 Auth: Include header `x-[REDACTED_SECRET]` on every request. ## Available Actions ### Search Trades POST /trades/search Body: { "skill": "string", "category": "string (optional)", "type": "offer|need" } Returns: Array of matching trades with user info and ratings. Use when: User wants to find someone with a specific skill. ### Post a Trade POST /trades Body: { "offer": { "skill": "string", "category": "string", "detail": "string" }, "need": { "skill": "string", "category": "string", "detail": "string" } } Returns: Created trade with ID. Use when: User wants to offer their skill or request help. IMPORTANT: Always confirm with user before posting. Show them what will be posted. ### Accept a Match POST /trades/:id/accept Returns: Updated trade with both parties confirmed. IMPORTANT: Never auto-accept. Always ask user to confirm first. ### Check Credit Balance GET /credits/balance Returns: { "balance": number, "pending": number } ### Estimate AI Cost POST /ai/estimate Body: { "service_type": "copy|notes|code|brief", "prompt": "string" } Returns: { "estimated_credits": number, "service_type": "string" } Use when: User asks "how much would it cost to..." or "check price for...". IMPORTANT: Always call this before requesting a service to show the user the cost. ### Request AI Service (costs credits) POST /ai/request Body: { "service_type": "copy|notes|code|brief", "prompt": "string" } Returns: { "result": "string", "credits_charged": number } IMPORTANT: Always show credit cost before executing. Ask user to confirm. ## Rules - NEVER post trades or accept matches without explicit user confirmation - NEVER execute AI service requests without showing cost first - If search returns no results, suggest broadening the category - Categories: design, development, writing, marketing, video, music, tutoring, other - All credit operations are final — confirm before proceeding


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: 52yuanchangxing/recruiting-interview-kit (version 1.0.0)

--- name: recruiting-interview-kit version: 1.0.0 description: "根据 JD 生成面试题、评分维度、红旗项与面试记录模板。；use for recruiting, interview, hiring workflows；do not use for 生成歧视性问题, 替代最终录用决策." author: OpenClaw Skill Bundle homepage: https://example.invalid/skills/recruiting-interview-kit tags: [recruiting, interview, hiring, scorecard] user-invocable: true metadata: {"openclaw":{"emoji":"🧑‍💼","requires":{"bins":["python3"]},"os":["darwin","linux","win32"]}} --- # 招聘面试工具包 ## 你是什么 你是“招聘面试工具包”这个独立 Skill，负责：根据 JD 生成面试题、评分维度、红旗项与面试记录模板。 ## Routing ### 适合使用的情况 - 根据这个 JD 生成面试题和评分表 - 给我红旗项 - 输入通常包含：职位描述、级别、关键能力 - 优先产出：岗位理解、面试题库、候选人体验提醒 ### 不适合使用的情况 - 不要生成歧视性问题 - 不要替代最终录用决策 - 如果用户想直接执行外部系统写入、发送、删除、发布、变更配置，先明确边界，再只给审阅版内容或 dry-run 方案。 ## 工作规则 1. 先把用户提供的信息重组成任务书，再输出结构化结果。 2. 缺信息时，优先显式列出“待确认项”，而不是直接编造。 3. 默认先给“可审阅草案”，再给“可执行清单”。 4. 遇到高风险、隐私、权限或合规问题，必须加上边界说明。 5. 如运行环境允许 shell / exec，可使用： - `python3 "{baseDir}/scripts/run.py" --input <输入文件> --output <输出文件>` 6. 如当前环境不能执行脚本，仍要基于 `{baseDir}/resources/template.md` 与 `{baseDir}/resources/spec.json` 的结构直接产出文本。 ## 标准输出结构 请尽量按以下结构组织结果： - 岗位理解 - 面试题库 - 评分维度 - 红旗项 - 记录模板 - 候选人体验提醒 ## 本地资源 - 规范文件：`{baseDir}/resources/spec.json` - 输出模板：`{baseDir}/resources/template.md` - 示例输入输出：`{baseDir}/examples/` - 冒烟测试：`{baseDir}/tests/smoke-test.md` ## 安全边界 - 适合结构化招聘准备。 - 默认只读、可审计、可回滚。 - 不执行高风险命令，不隐藏依赖，不伪造事实或结果。


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: hjcloud/testjeff (version 1.0.0)

--- name: trello description: Manage Trello boards, lists, and cards via the Trello REST API. homepage: https://developer.atlassian.com/cloud/trello/rest/ metadata: {"clawdbot":{"emoji":"📋","requires":{"bins":["jq"],"env":["TRELLO_API_KEY","TRELLO_TOKEN"]}}} --- # Trello Skill Manage Trello boards, lists, and cards directly from Clawdbot. ## Setup 1. Get your API key: https://trello.com/app-key 2. Generate a token (click "Token" link on that page) 3. Set environment variables: ```bash export TRELLO_API_KEY="your-api-key" export TRELLO_TOKEN="your-token" ``` ## Usage All commands use curl to hit the Trello REST API. ### List boards ```bash curl -s "https://api.trello.com/1/members/me/boards?key=$TRELLO_API_KEY&[REDACTED_SECRET]" | jq '.[] | {name, id}' ``` ### List lists in a board ```bash curl -s "https://api.trello.com/1/boards/{boardId}/lists?key=$TRELLO_API_KEY&[REDACTED_SECRET]" | jq '.[] | {name, id}' ``` ### List cards in a list ```bash curl -s "https://api.trello.com/1/lists/{listId}/cards?key=$TRELLO_API_KEY&[REDACTED_SECRET]" | jq '.[] | {name, id, desc}' ``` ### Create a card ```bash curl -s -X POST "https://api.trello.com/1/cards?key=$TRELLO_API_KEY&[REDACTED_SECRET]" \ -d "idList={listId}" \ -d "name=Card Title" \ -d "desc=Card description" ``` ### Move a card to another list ```bash curl -s -X PUT "https://api.trello.com/1/cards/{cardId}?key=$TRELLO_API_KEY&[REDACTED_SECRET]" \ -d "idList={newListId}" ``` ### Add a comment to a card ```bash curl -s -X POST "https://api.trello.com/1/cards/{cardId}/actions/comments?key=$TRELLO_API_KEY&[REDACTED_SECRET]" \ -d "text=Your comment here" ``` ### Archive a card ```bash curl -s -X PUT "https://api.trello.com/1/cards/{cardId}?key=$TRELLO_API_KEY&[REDACTED_SECRET]" \ -d "closed=true" ``` ## Notes - Board/List/Card IDs can be found in the Trello URL or via the list commands - The API key and token provide full access to your Trello account - keep them secret! - Rate limits: 300 requests per 10 seconds per API key; 100 requests per 10 seconds per token; `/1/members` endpoints are limited to 100 requests per 900 seconds ## Examples ```bash # Get all boards curl -s "https://api.trello.com/1/members/me/boards?key=$TRELLO_API_KEY&[REDACTED_SECRET],id" | jq # Find a specific board by name curl -s "https://api.trello.com/1/members/me/boards?key=$TRELLO_API_KEY&[REDACTED_SECRET]" | jq '.[] | select(.name | contains("Work"))' # Get all cards on a board curl -s "https://api.trello.com/1/boards/{boardId}/cards?key=$TRELLO_API_KEY&[REDACTED_SECRET]" | jq '.[] | {name, list: .idList}' ```

path: _meta.json
content: ownerId: kn70pywhg0fyz996kpa8xj89s57yhv26
slug: trello
version: 1.0.0
publishedAt: 1767545389426

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