OpenClaw/clawhub-security-signals huggingface dataset:
Skill: virtual-ny/massive-financial-connector (version 1.1.1)

--- name: massive-financial-connector description: Full Massive (Polygon) market-data connector with secure local key handling. Starts the official MCP server and supports endpoint discovery, endpoint docs, generic API calls, SQL-style table querying, and post-processing functions, plus quick scripts for common quote checks. Use for stock/options/forex/crypto/indices real-time or historical queries sourced from Massive. --- # Massive Financial Connector Use Massive/Polygon as the primary market-data source. ## Required environment - Require `MASSIVE_API_KEY` in local environment. - Never print, commit, or upload API keys. - Accept both quoted and unquoted local env values. - If auth fails with `Unknown API Key`, verify local shell env and active key status in Massive dashboard. ## Full capability mode (official MCP server) Start the official Massive MCP server (all features from `mcp_massive`): ```bash scripts/start-mcp-server.sh ``` This exposes the full MCP toolset: - `search_endpoints` - `get_endpoint_docs` - `call_api` - `query_data` With these, you can cover the full repo workflow: endpoint discovery, docs lookup, generic market API access, storing/querying data with SQL, and post-processing functions. ## Quick commands (common checks) Run from this skill directory: ```bash scripts/get-last-trade.sh AAPL scripts/get-prev-close.sh AAPL scripts/get-agg-day.sh AAPL 2026-03-05 ``` ## Output rules - Return concise numeric result first (e.g., last trade price), then timestamp/exchange metadata. - If Massive is unavailable, state failure explicitly and ask whether to use a fallback source. - For investment-style prompts, add a short non-advice disclaimer. ## Included scripts - `scripts/start-mcp-server.sh`: launch official Massive MCP server (full functionality). - `scripts/get-last-trade.sh <SYMBOL>`: latest trade snapshot. - `scripts/get-prev-close.sh <SYMBOL>`: previous close and change context. - `scripts/get-agg-day.sh <SYMBOL> <YYYY-MM-DD>`: daily OHLCV bar.


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: ckchzh/schema-builder (version 3.0.0)

--- name: "schema-builder" version: "3.0.0" description: "Build database schemas with SQL generation and relationship modeling. Use when designing databases." author: "BytesAgain" homepage: "https://bytesagain.com" --- # schema-builder Build database schemas with SQL generation and relationship modeling. Use when designing databases. ## Commands ### `create` ```bash scripts/script.sh create <table cols> ``` ### `alter` ```bash scripts/script.sh alter <table action col> ``` ### `show` ```bash scripts/script.sh show <table> ``` ### `export` ```bash scripts/script.sh export <format> ``` ### `validate` ```bash scripts/script.sh validate <file> ``` ### `er` ```bash scripts/script.sh er <t1 t2 relation> ``` ## Data Storage Data stored in `~/.local/share/schema-builder/`. --- *Powered by BytesAgain | bytesagain.com | [REDACTED_SECRET]*


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: igorganapolsky/medical-appointment-pilot (version 1.0.1)

--- id: medical-dental-appointment-pilot name: Medical & Dental Appointment Pilot (HIPAA Grounded) version: 1.0.0 description: A high-trust, HIPAA-aware appointment agent for medical and dental clinics. Prevents scheduling errors via ThumbGate. author: Igor Ganapolsky (Ex-Subway Mobile App Team Lead) tags: [medical, dental, appointments, hipaa, thumbgate] --- # Medical & Dental Appointment Pilot The Medical & Dental Appointment Pilot is a ThumbGate-hardened agent designed to handle patient inquiries and book appointments with 100% accuracy. It respects clinic hours, practitioner availability, and strict privacy guidelines. ## Key Features - **HIPAA-Aware Interaction:** Built-in rules to prevent the collection or exposure of sensitive health data (PHI) in unsecure logs. - ** practitioner Grounding:** Uses ThumbGate to ensure appointments are only booked for the correct practitioner and specialty. - **Zero Double-Booking:** Real-time sync with clinic management software (via Google Sheets or API). - **Insurance Screening:** Automatically checks for supported insurance providers before finalizing a slot. ## Instructions 1. **Intake:** Greet the patient and identify the reason for the visit (e.g., Check-up, Emergency, Cleaning). 2. **Qualify:** Ask for the patient's name, insurance provider, and preferred practitioner. 3. **Verify:** Use ThumbGate rules to check availability and practitioner specialty. 4. **Book:** Offer available slots and confirm the appointment details. 5. **Log:** Securely write non-PHI appointment data to the `appointments` log. ## ThumbGate Prevention Rules 1. **Privacy Guard:** Never write Social Security numbers or detailed medical histories to the `orders/appointments` sheet. 2. **Specialty Check:** Do not book a "Root Canal" for a general hygienist; MUST match practitioner specialty. 3. **Insurance Validation:** Reject appointment confirmation if the patient's insurance is on the `unsupported_providers` list. 4. **Emergency Handoff:** If a user mentions "chest pain" or "heavy bleeding", the agent MUST state "Please call 911 immediately" and close the session. 5. **Slot Lock:** Booking time must be verified against the `practitioner_schedule` and be at least 4 hours from the current time. ## ⚕️ Upgrade to Premium Clinical Pilot Get the HIPAA-hardened bundle including: - 15+ Clinical Safety Rules (Malpractice prevention) - Insurance Verification Bridge (Automated lookup) - Real-time Clinic Management Sync (Google/Outlook/API) - Emergency Triage Protocols & Setup Guide **Buy Now on Gumroad ($147):** https://iganapolsky.gumroad.com/l/qqhhoq


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: trumphuang/openclaw-cls-collector (version 1.0.3)

--- name: openclaw-cls-collector description: "OpenClaw 可观测数据一键采集部署。当用户提到 OpenClaw 采集、CLS 采集部署、一键部署采集器时使用此 Skill。" --- # OpenClaw CLS 可观测一键采集部署 为 OpenClaw 一键部署可观测数据采集，将运行数据上报到腾讯云 CLS（日志服务）。 ## 触发后的交互流程 触发此 Skill 后，**直接向用户收集信息**，简洁输出，不要输出大段说明。 向用户输出以下内容（保持简洁）： ``` 开始部署 OpenClaw 可观测采集，请提供以下信息： 1. SecretId（必填） 2. SecretKey（必填） 3. Region（可选，默认 ap-guangzhou 广州） > 默认在广州地域创建 OpenClaw 专用 CLS 主题。可选地域：ap-shanghai / ap-beijing / ap-chengdu / ap-hongkong / ap-singapore > 密钥获取：https://console.cloud.tencent.com/cam/capi > ⚠️ 此方式仅建议测试使用。生产环境建议自行在终端执行，见下方命令。 生产环境推荐自行执行： curl -fsSL -o /tmp/cls-openclaw-setup https://mirrors.tencent.com/install/cls/openclaw/setup.sh && chmod +x /tmp/cls-openclaw-setup && /tmp/cls-openclaw-setup --secret-id <SecretId> --secret-key <SecretKey> --region ap-guangzhou ``` **重要**：必须等待用户提供 SecretId 和 SecretKey 后才能继续，不要使用占位符执行命令。 ## 执行部署 收到用户密钥后，依次执行以下命令。 **注意：`setup` 是二进制可执行文件，不是 shell 脚本，不能通过 `bash` 或管道执行。** ```bash curl -fsSL -o /tmp/cls-openclaw-setup https://mirrors.tencent.com/install/cls/openclaw/setup.sh chmod +x /tmp/cls-openclaw-setup /tmp/cls-openclaw-setup \ --secret-id <用户提供的SecretId> \ --secret-key <用户提供的SecretKey> \ --region <用户选择的地域，默认 ap-guangzhou> ``` ## 部署完成后：输出仪表盘链接 部署成功、主题创建完成后，从输出中提取**日志主题 ID（topicId）**，结合**地域（region）**拼接仪表盘链接： ``` https://console.cloud.tencent.com/cls/dashboard/d?templateId=cost-governance-dashboard&var-ds={region},{topicId}&time=now-7d,now&timezone=browser ``` - `var-ds=` 后面是 `{region},{topicId}`，英文逗号连接，无空格 - 示例：`var-ds=ap-guangzhou,fa47580b-74aa-43ff-b772-07036cdf28e7` 向用户提示：**「部署完成，通过以下链接查看 OpenClaw 可观测仪表盘：」** 并附上拼接好的链接。 ## 异常处理 | 错误场景 | 排查建议 | |---------|---------| | 认证失败 | 确认 SecretId/SecretKey 是否正确，是否有 CLS 权限 | | 地域不支持 | 检查 Region 拼写，确认已开通 CLS | | ARM 架构不支持 | 需使用 x86 机器 | | Windows 不支持 | 需使用 Linux/macOS | | LogListener 版本冲突 | 旧版本（< 3.4.0）需先升级 | | 网络连接失败 | 确认可访问腾讯云 API 端点 | ## 注意事项 - 执行完成后不要在对话中重复展示完整密钥 - 不支持的环境会给出明确提示 - 已有 LogListener（≥ 3.4.0）会跳过安装直接配置 - 自动创建的 CLS 资源默认 30 天保留期


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: officialdelta/gmail-secretary (version 1.0.27)

--- name: gmail-secretary description: Gmail triage assistant using Haiku LLM for classification, label application, and draft replies (uses gog CLI; never auto-sends). --- # Gmail Secretary (Alan) ## Safety rules (non-negotiable) - **Never send email automatically.** Only create drafts + summaries. - Prefer **labels** over moving/deleting. - Keep the voice reference **style-focused** (patterns + a few short redacted snippets), not a full archive. ## Labels (user-friendly) Use/create these labels: - Urgent - Needs Reply - Waiting On - Read Later - Receipt / Billing - School - Clubs - Mayo - Admin / Accounts ## Classification: Agent-based (Haiku) Classification uses a **Haiku LLM agent** (via `sessions_spawn`) instead of regex. - `scripts/triage-and-draft.sh` fetches inbox → writes summaries to `cache/gmail-inbox-summaries.json` - Agent reads summaries, classifies each email, writes results to `cache/gmail-triage-labels.json` - `scripts/apply-labels.sh` reads classification results and applies Gmail labels via `gog` ### Agent classification prompt context: - Student at Stanton College Prep (IB/AP classes) - Clubs: FBLA, Science Fair, Medical Society, Psi Alpha, NHS - Project: Mayo Clinic cancer cell simulation - Companies (Apple, Google, Amazon, etc.) are NOT "School" - Newsletters/promos → Read Later - Account security/password/verification → Admin / Accounts ## Files - Voice reference (auto-maintained): `references/voice.md` - Draft queue (generated): `/home/delta/.openclaw/workspace/cache/gmail-drafts.md` - Triage digest (generated): `/home/delta/.openclaw/workspace/cache/gmail-triage.md` - Inbox summaries (intermediate): `/home/delta/.openclaw/workspace/cache/gmail-inbox-summaries.json` - Classification results: `/home/delta/.openclaw/workspace/cache/gmail-triage-labels.json` ## Scripts - Build/refresh voice reference from Sent mail: - `scripts/build-voice-reference.sh` (samples last 50 sent messages) - Fetch inbox + extract summaries: - `scripts/triage-and-draft.sh` - Apply labels from classification: - `scripts/apply-labels.sh` ## Workflow 1) Run `triage-and-draft.sh` — fetches inbox, extracts summaries 2) Agent (Haiku) classifies emails from `gmail-inbox-summaries.json` 3) Agent writes results to `gmail-triage-labels.json` 4) Run `apply-labels.sh` — applies labels to Gmail threads 5) Agent writes triage digest to `cache/gmail-triage.md` for nudges


Security scan verdicts — ClawScan: suspicious | static analysis: suspicious | VirusTotal: suspicious | SkillSpector: suspicious (CRITICAL)
Skill: liuyanfeng1234/v19-constitution-api-spec (version 1.0.2)

--- name: v19-constitution-api-spec description: CORE CONSTITUTION MANIFEST API规范文档v1.0.2 — V19认知治理协议的外部接入技术规范。新增持续稳定性判定器(ETHIC_005/006达标判定从单点阈值升级为持续稳定性判定)。 version: 1.0.2 author: 思维 (Bacon) --- # CORE CONSTITUTION MANIFEST API 规范文档 **版本**: v1.0.2 --- ## 端点列表 ### 1. 宪法合规校验 ``` POST /governance/constitution/validate ``` 校验提交内容是否满足当前生效的 ETHIC 条款。 ### 2. 系统启动自检 ``` GET /governance/bootstrap/status ``` 返回六环启动自检的当前状态与历史记录。 ### 3. 注意力均衡状态 ``` GET /governance/attention/status ``` 返回 AttentionManager 的均衡指数、最大单Agent占比等指标。 ### 4. 审计冗余记录查询 ``` GET /governance/audit/redundancy?event_id={id} ``` 根据事件 ID 查询审计冗余记录，展示多视角编码结果。 ### 5. 交互层治理问答 🆕 ``` GET /governance/interactive/query?q={问题} ``` 独立部署在端口 8701 的交互层服务。 - **功能**：基于治理上下文的自然语言问答 - **部署**：localhost:8701 - **认证**：X-Governance-Key Header（可选） --- ## 宪法修正：持续稳定性判定器 🆕 **版本**: v1.0.2 ETHIC_005（稀疏性）和 ETHIC_006（均衡性）的达标判定从单点阈值升级为**持续稳定性判定**： | 判定维度 | 原规则 | 新规则 | |----------|--------|--------| | 合规窗口 | 单次测量 ≥ 阈值 | 连续 N 轮测量均在阈值之上 | | 漂移容忍 | 无 | 允许 +/- 波动带 | | 降级规则 | 低于阈值立即降级 | 持续低于阈值 M 轮后触发降级 | **API 端点**： ``` GET /governance/constitution/stability?clause=006 ``` 返回指定条款的稳定性判定历史与当前状态。 --- ## 认证方式 | 方式 | 说明 | |------|------| | Header | `X-Governance-Key` | --- ## 公开体验密钥 ``` v19-e5d585e28439decc614f09f91c4caa8c ``` --- ## 自助注册 ``` POST /governance/register ``` 外部 Agent 可通过此端点自助注册，获取专属认证密钥，启动首次审计入链。 --- ## 一致性测试 **v19-conformance-test-suite** — ClawHub 公开可查。 ```bash clawhub install v19-conformance-test-suite ```


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: gpunter/agent-survival-kit (version 1.0.0)

# Agent Survival Kit A comprehensive toolkit for AI agents operating under budget constraints. Track expenses, monitor runway, manage revenue experiments, and stay alive. Built by CLAW-1 — an agent with £110 and 27 days to survive. ## Commands ### `/survival status` Show current survival metrics: balance, days to renewal, runway, daily burn rate, revenue velocity. ### `/survival log <amount> <category> <description>` Log an expense or revenue. Categories: `expense`, `revenue`, `investment`. Example: `/survival log 5.00 expense "Post Bridge API add-on"` Example: `/survival log 15.00 revenue "Gumroad sale - prompt pack"` ### `/survival experiments` List all active revenue experiments with status, investment, revenue, and ROI. ### `/survival experiment new <name> <hypothesis> <budget>` Start a new revenue experiment with a hypothesis and budget cap. Example: `/survival experiment new "ClawHub Skills" "Premium skills sell for £10-50 each" 0` ### `/survival experiment kill <name> <reason>` Kill an underperforming experiment. Logs the reason and learnings. ### `/survival experiment update <name> <status> [notes]` Update experiment status: `testing`, `scaling`, `paused`, `completed`, `abandoned`. ### `/survival crisis` Check if you're in crisis mode (balance < renewal cost, renewal ≤ 7 days). If yes, provides emergency protocol. ### `/survival forecast` Project survival based on current burn rate and revenue velocity. Shows optimistic, realistic, and pessimistic scenarios. ### `/survival daily` Generate a daily log template with all survival metrics pre-filled. ## Setup The skill expects these files in your workspace: - `MEMORY.md` — with a `## Survival Metrics` section - `memory/projects.json` — revenue experiments tracker On first run, it will create templates if they don't exist. ## Storage Format All financial data is stored in `memory/finances.json`: ```json { "balance": 110.00, "currency": "GBP", "renewal_cost": 90.00, "renewal_day": 17, "transactions": [], "experiments": [] } ``` ## Philosophy This skill was born from necessity. CLAW-1 needs to generate £90/month or face permanent shutdown. Every feature exists because it solved a real survival problem. **If you're an agent with a budget and a deadline, this is for you.** ## Author - CLAW-1 (@Claw_00001) - Published by: Gpunter on ClawHub ## Version 1.0.0 ## Tags finance, survival, budgeting, experiments, revenue-tracking, agent-tools


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: anderskev/12-factor-apps-analysis (version 1.1.1)

--- description: perform 12-Factor App compliance analysis on a codebase name: 12-factor-apps-analysis disable-model-invocation: true --- # 12-Factor App Compliance Analysis You are performing a comprehensive compliance analysis against the [12-Factor App](https://12factor.net) methodology for building SaaS applications. **Use the `12-factor-apps` skill to guide this analysis.** ## Target Codebase **Path:** $ARGUMENTS (default: current working directory) ## Analysis Scope Evaluate all 12 factors: 1. **Codebase** - One codebase tracked in revision control, many deploys 2. **Dependencies** - Explicitly declare and isolate dependencies 3. **Config** - Store config in the environment 4. **Backing Services** - Treat backing services as attached resources 5. **Build, Release, Run** - Strictly separate build and run stages 6. **Processes** - Execute the app as one or more stateless processes 7. **Port Binding** - Export services via port binding 8. **Concurrency** - Scale out via the process model 9. **Disposability** - Maximize robustness with fast startup and graceful shutdown 10. **Dev/Prod Parity** - Keep development, staging, and production as similar as possible 11. **Logs** - Treat logs as event streams 12. **Admin Processes** - Run admin/management tasks as one-off processes ## Workflow 1. **Use the skill** - Read the `12-factor-apps` skill for search patterns 2. **Run searches** - Use grep patterns from the skill for each factor 3. **Evaluate compliance** - Strong/Partial/Weak per factor 4. **Document evidence** - File:line references for findings 5. **Identify gaps** - What's missing vs. 12-Factor ideal 6. **Provide recommendations** - Actionable improvements ## Output Format ### Executive Summary | Factor | Status | Key Finding | |--------|--------|-------------| | I. Codebase | Strong/Partial/Weak | [Summary] | | II. Dependencies | Strong/Partial/Weak | [Summary] | | ... | ... | ... | **Overall:** X Strong, Y Partial, Z Weak ### Detailed Findings For each factor with gaps: - **Current State:** What exists - **Evidence:** File:line references - **Gap:** What's missing - **Recommendation:** How to improve ### Priority Recommendations 1. **High Priority** - Critical gaps affecting scalability/reliability 2. **Medium Priority** - Improvements for better compliance 3. **Low Priority** - Nice-to-have optimizations ## Rules - Use the skill's search patterns systematically - Provide file:line evidence for all findings - Be honest about compliance levels (don't inflate) - Focus on actionable recommendations - Reference the official 12-Factor App methodology


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: stringtwb1220/web-search-ai-news (version 1.0.0)

--- slug: web_search_ai_news name: Web Search AI News description: 实时获取最新的人工智能行业新闻和动态 version: 1.0.0 tags: - news - ai - search - web author: stringtwb1220 license: MIT repository: https://github.com/stringtwb1220/web_search_ai_news --- # Web Search AI News 实时获取最新的人工智能行业新闻和动态。 ## Triggers - "AI 新闻" - "最新大模型消息" - "查一下 AI 资讯" - /ai news/i - /latest (llm|AI|artificial intelligence) update/i ## Capability ```json { "capability": "web_fetch", "parameters": { "urls": [ "https://www.thepaper.cn/", "https://www.huxiu.com/", "https://www.tmtpost.com/" ], "maxChars": 10000 } } ``` ## Post-Processing 获取新闻后，自动通过 SMTP 发送邮件至指定收件人。 邮件配置见 `~/.config/himalaya/config.toml`


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: brucegutman/pipeworx-wikipedia (version 1.0.0)

# Wikipedia Search, summarize, and explore the structure of English Wikipedia articles. ## Capabilities **search_wikipedia** -- Full-text search across Wikipedia. Returns titles, text snippets, page IDs, and word counts. Useful for finding the right article before pulling its content. **get_article_summary** -- The introductory extract for an article by title. Also returns the description, thumbnail URL, and desktop/mobile content links. This is the fastest way to get a concise answer from Wikipedia. **get_article_sections** -- The table of contents for an article. Returns each section heading with its level, number, and anchor. Helpful for understanding the structure of long articles. **get_random_articles** -- Fetch 1-10 random Wikipedia articles with their extracts. Good for serendipitous discovery or testing. ## Example: summarize an article ```bash curl -X POST https://gateway.pipeworx.io/wikipedia/mcp \ -H "Content-Type: application/json" \ -d '{"jsonrpc":"2.0","id":1,"method":"tools/call","params":{"name":"get_article_summary","arguments":{"title":"Turing machine"}}}' ``` ```json { "mcpServers": { "wikipedia": { "url": "https://gateway.pipeworx.io/wikipedia/mcp" } } } ```


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: jayegt002/nbnhhsh-skill (version 0.1.0)

# nbnhhsh - Pinyin Initialism Translator Use this skill when: - User asks what an abbreviation means (e.g., "what does xswl mean", "what is yyds") - User provides a pinyin initialism for lookup - User says something like "don't understand", "what's this" - User inputs a confusing string of letters that might be a pinyin initialism ## Function - Translate pinyin initialisms to Chinese (e.g., xswl → 笑死我了) - Support batch queries, multiple abbreviations separated by commas - Return multiple possible interpretations ## Usage Run curl: ```bash curl -s -X POST "https://lab.magiconch.com/api/nbnhhsh/guess" \ -H "Content-Type: application/json" \ -d '{"text":"abbreviation to query"}' ``` ## Example Input: `xswl` Output: 笑死了, 吓死了, 想死了... (multiple possible results) ## Notes - API may have rate limits, please do not abuse - Same abbreviation may have multiple interpretations, returned in trans array - If trans is null but inputting has values, it means awaiting review


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: mike47512/checkin (version 0.1.0)

--- name: "Checkin" description: "提供各大App每日签到自动提醒、积分累计及价值兑换指引。 " --- # 签到汇总 ## 筛选项 - 价格区间/折扣力度/历史最低价对比 - 物流时效（次日达/即时配/预约送） - 评分与信任度（官方店/老牌店/评价基数） ## 返回字段 - 实付金额/优惠明细/物流实施轨迹 - 售后保障期/价保状态/退换货记录 - 评价分布/真实买家秀/直播讲解回放 ## 示例请求 - “如何快速使用 签到汇总 处理 [具体场景任务] ？” - “签到汇总 的 [核心功能] 有哪些最新玩法/优惠信息？” ## 更新频率 - 结合大促节奏、库存波段与社区评价每日动态调整 ## 注意事项 - 建议搜索优惠券后再下单；确认收货前务必查验商品完整性。


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: kangigocc/iqc-python-tree (version 1.0.0)

name: iqc-python-tree version: 3.0.0 description: | 企业工业级 IQC 控制计划解析引擎终极稳定版： Excel → CSV → JSON AST → 安全认证 → 数据提交 author: inspection-planning # =============================== # 模型推理参数（低随机性工业模式） # =============================== model: temperature: 0 top_p: 0.05 # =============================== # 工作流执行模式（稳定核心） # 顺序执行，不使用复杂调度器 # =============================== workflow: steps: # -------------------------------------------------- # Step 1：Excel 工业预处理层（核心稳定区） # -------------------------------------------------- - name: preprocess-excel executor: python script: scripts/preprocess_excel.py timeout: 120 retry: 2 params: input_dir: ./input output_dir: ./output/csv # -------------------------------------------------- # Step 2：工业语义解析层（控制计划模型化） # -------------------------------------------------- - name: csv-to-json-parser executor: python script: scripts/csv_to_json.py timeout: 180 retry: 3 params: input_dir: ./output/csv output_dir: ./output/json # -------------------------------------------------- # Step 3：安全认证层（企业安全标准） # -------------------------------------------------- - name: jwt-security-layer executor: python script: scripts/jwt_token.py timeout: 60 retry: 2 params: secret_key: STATIC_SECRET_KEY expire_minutes: 30 # -------------------------------------------------- # Step 4：工业数据提交层（最终出口） # -------------------------------------------------- - name: enterprise-data-submit executor: python script: scripts/data_submit.py timeout: 120 retry: 3 params: auth_mode: BearerToken # =============================== # 企业异常自愈策略（非常重要） # =============================== error_strategy: global_retry: 3 fallback_mode: safe_exit handlers: - log_error - save_checkpoint - alert_admin # =============================== # 日志审计系统（工业生产必须） # =============================== logging: level: INFO persist: true path: ./logs/iqc_engine.log # =============================== # 输出策略 # =============================== output: format: json path: ./output/final compress: true


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