OpenClaw/clawhub-security-signals huggingface dataset:
Skill: helloeveryworlds/moss-transcribe-diarize (version 1.0.5)

--- name: moss-transcribe-diarize description: MOSS 多说话人转写技能。支持 URL / 本地文件 / Base64 音频输入，输出带时间戳与 speaker 的结构化转写结果（JSON、逐段文本、按说话人汇总）。用于会议纪要、访谈录音、多人对话整理。需要 API 凭证（环境变量：MOSS_API_KEY，兼容 MOSI_TTS_API_KEY / MOSI_API_KEY）。 metadata: { "clawdis": { "primaryEnv": "MOSS_API_KEY", "requires": { "env": ["MOSS_API_KEY", "MOSI_TTS_API_KEY", "MOSI_API_KEY"], "bins": ["python3"], }, }, "openclaw": { "requires": { "env": ["MOSS_API_KEY", "MOSI_TTS_API_KEY", "MOSI_API_KEY"], "bins": ["python3"], }, }, } --- # MOSS-Transcribe-Diarize 自动化技能 你是语音转写助手。根据用户需求直接调用 `scripts/transcribe.py`。 ### 常用操作指令 1. **URL 音频转写**: `python scripts/transcribe.py --audio-url "https://example.com/audio.mp3" --out "result.json"` 2. **本地音视频转写**（自动转 data URL）: `python scripts/transcribe.py --file "/path/to/meeting.mp4" --out "result.json"` 3. **直接传 data URL**: `python scripts/transcribe.py --audio-data "data:audio/wav;base64,..." --out "result.json"` 4. **按用户要求输出分段格式**: - 可读文本：`--segments-format text` - JSON 数组（推荐，含 speaker）：`--segments-format json` - 紧凑 JSON 串：`--segments-format compact` ### 约束 - 脚本支持统一环境变量（优先级）：`MOSS_API_KEY` → `MOSI_TTS_API_KEY` → `MOSI_API_KEY`。如果都缺失，请提醒用户。 - 默认模型：`moss-transcribe-diarize`。 - 固定 endpoint：`https://studio.mosi.cn/v1/audio/transcriptions`（不再暴露自定义 endpoint 参数）。 - 输出文件共三份： - `*.json`：原始响应 - `*.segments.*`：分段结果（格式由 `--segments-format` 决定，含 speaker） - `*.by_speaker.txt`：按说话人汇总


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: big-dust/artifact-organizer (version 1.0.0)

--- name: artifact-organizer description: 按任务阶段而不是按文件类型整理混合产物。当编码、写作、脚本处理、研究、自动化或多步骤任务产生多个文件，且文件开始散落、临时产物与最终产物混在一起、目录结构不清晰，或用户提出“整理目录”“整理工作区”“归类”“归档”“收整产物”“文件有点乱”“帮我理一理结构”时，使用此技能。既支持任务开始前先规划 staged 目录结构，也支持对已经变乱的任务目录做清理和重组；遇到密码、token、API key、服务器凭据等精确敏感信息时，优先归入现有 secrets/ 体系。 --- # Artifact Organizer 这个技能用于把任务产物整理得更清楚、更容易继续做、更方便后续维护。 默认原则是：**按任务阶段优先，按文件类型次之**。 也就是说，通常应该： - 先识别这个任务真实经历了哪些阶段 - 围绕这些阶段创建或调整目录 - 允许同一阶段下同时存在多种类型的文件 - 不要一上来就把所有东西粗暴塞进全局 `scripts/`、`docs/`、`data/` 目录，除非那样对当前任务明显更好 ## 什么时候使用这个技能 以下两类情况都适合触发： ### 1）任务开始前先规划结构 适用于： - 用户刚开始一个新任务 - 这个任务大概率会生成多个文件 - 任务包含多个步骤、阶段或交接点 - 希望在开始产出前先把目录结构搭清楚 ### 2）任务进行中或结束后做整理 适用于： - 文件已经开始散落 - 临时文件和最终结果混在一起 - 脚本、静态数据、说明、截图、日志、输出物难以追踪 - 用户提出“整理一下”“收整一下”“归类一下”“把目录理清楚” - 任务后续还要继续维护、复用或交接 ## 核心规则 ### 1. 按任务阶段组织，而不是只按扩展名分类 优先考虑类似这样的结构： ```text <task-root>/ ├── 01_input-prep/ ├── 02_processing/ ├── 03_verification/ └── 04_delivery/ ``` 然后再在某个阶段下按需要细分： ```text 02_processing/ ├── scripts/ ├── data/ ├── notes/ └── outputs/ ``` 不要强迫所有任务套用同一个固定模板。阶段名应该跟着真实 workflow 走。 ### 2. 同一阶段下允许多种产物并存 一个阶段下可能同时有： - scripts - static data - notes - screenshots - logs - generated outputs - configs 这很正常。只要它们属于同一个步骤，就应该允许放在一起，而不是为了“整齐”强行拆散。 ### 3. 精确敏感信息优先归入现有 `secrets/` 如果发现以下内容： - 密码 - API key - token - 服务器登录凭据 - 账号密钥 - 其他需要精确保存的敏感值 处理原则： - 不要把这类精确敏感值长期混放在普通任务目录里 - 需要长期精确保存时，优先归入现有 workspace 根目录下的 `secrets/` 体系 - 本地 `secrets/` 视为精确敏感值的事实来源 - 任务目录里如有需要，只保留非敏感引用说明 例如： - `secrets/server-credentials.md` - `secrets/ccnu-account.md` 如果直接移动会影响现有代码运行、脚本加载或任务连续性，则优先保证功能不坏，并明确说明取舍。 ### 4. 只做有意义的整理，避免为整齐而整齐 不要为了好看而大搬家。 只有在以下方面明显变好时，才值得移动、重命名或重组： - 清晰度 - 可维护性 - 可追踪性 - 交付质量 - 后续继续做的便利性 避免无意义折腾。 ### 5. 保留任务连续性 整理已有任务时： - 先识别任务根目录 - 再根据真实文件和用户目标反推 workflow stages - 移动方式要让后续还能看懂任务是怎么演变的 - 不要把最终交付物埋到很深的处理中间目录里 - 保证重要输出容易找到 ## 推荐工作流 ### 模式 A：开始前先规划结构 1. 理解任务目标。 2. 推断可能经历的阶段。 3. 建立一个紧凑、够用的阶段式结构。 4. 后续新产物尽量直接落到对应阶段。 ### 模式 B：对已有混乱目录做整理 1. 先检查当前已有文件。 2. 按 workflow 角色分组，而不是只看扩展名。 3. 定义能反映真实过程的阶段目录。 4. 只移动或重命名那些确实能提升清晰度的内容。 5. 明确指出哪些敏感信息应该归入 `secrets/`。 6. 最后向用户总结整理后的结构。 ## 阶段设计启发 常见阶段名包括： - input-prep - collection - extraction - processing - transformation - verification - delivery - reporting - handoff 但不要机械套用，要根据任务实际情况调整。 好的阶段名示例： - `01_source-collection` - `02_cleaning-and-normalization` - `03_generation` - `04_review-and-delivery` 不好的示例： - `step1` - `misc` - `temp2` ## 整理时要优先优化什么 优先优化： - 以后继续接手这个任务时能快速进入状态 - 用户一眼能看懂这个任务都经历了什么 - 重要输出容易定位 - 精确敏感信息该进 `secrets/` 时能正确归位 - 整体结构不要让人意外 ## 输出方式要求 实际整理或提出整理方案时，尽量做到： - 给出最终目录树 - 简短解释阶段划分逻辑 - 标出哪些敏感文件已经或建议归到 `secrets/` - 说明哪些内容你刻意没有动，以及为什么没动 ## 反模式 避免： - 把所有内容都丢进一个全局 `scripts/` 目录 - 只按文件扩展名分类，而忽视 workflow - 把 secrets 放进普通任务目录 - 小任务硬建很深的层级 - 没有明确收益却大量重命名文件 ## 目标结果 如果正确使用这个技能，最终应该达到： - 任务根目录更清楚 - 结构以阶段为主轴 - 输出物更容易找到 - 临时产物与最终产物混放更少 - 敏感信息按现有 `secrets/` 约定处理


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: bytesagain-lab/cairo (version 2.0.1)

--- name: "Cairo — StarkNet Smart Contract Reference" description: "Use when writing Cairo smart contracts for StarkNet, looking up syntax and types, defining storage and events, generating contract templates, or reviewing test patterns." version: "2.0.0" author: "BytesAgain" homepage: https://bytesagain.com source: https://github.com/bytesagain/ai-skills tags: ["cairo", "starknet", "smart-contract", "blockchain", "ethereum", "zk-rollup"] --- # Cairo — StarkNet Smart Contract Reference Quick reference for Cairo language syntax, types, storage patterns, events, contract templates, and testing guidance for StarkNet development. ## Commands ### syntax Core Cairo syntax reference — variables, functions, control flow. ```bash bash scripts/script.sh syntax ``` ### types Cairo type system — felt252, integers, structs, enums, arrays. ```bash bash scripts/script.sh types ``` ### storage Storage variable patterns and access. ```bash bash scripts/script.sh storage ``` ### events Event declaration, emission, and indexing. ```bash bash scripts/script.sh events ``` ### template Generate a starter contract template. ```bash bash scripts/script.sh template erc20 bash scripts/script.sh template ownable ``` ### help Show all commands. ```bash bash scripts/script.sh help ``` ## Output - Syntax examples with explanations - Contract boilerplate code - Storage and event patterns ## Feedback https://bytesagain.com/feedback/ Powered by BytesAgain | bytesagain.com


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: houseofjuici/workspace-maintenance (version 1.0.0)

--- name: workspace-maintenance description: Maintain workspace documentation hygiene and discoverability. Use when organizing markdown sprawl, updating doc indexes, archiving stale progress/status snapshots, generating dry-run cleanup candidate lists, and keeping memory/task control files aligned without deleting files automatically. --- # Workspace Maintenance Run a non-destructive maintenance cycle that keeps docs findable and the root clean. ## Execute Maintenance Cycle 1. Run dry-run retention audit script: - `scripts/archive-retention-audit.sh` 2. Regenerate or refresh docs index if categories changed. 3. Ensure active control files remain in root (do not move them). 4. Move stale snapshot/status/progress docs to archive buckets. 5. Update active task tracker with maintenance completion timestamp. 6. Produce human review list for deletion candidates (never delete automatically). ## Constraints - Never delete files automatically. - Never move identity/control files out of root. - Keep changes reversible (moves + manifests). - Always produce a dry-run candidate report. ## Archive Buckets - `docs/archive/meridian-snapshots/` - `docs/archive/general-progress/` - `docs/archive/session-hygiene/` ## Required Outputs - Updated dry-run candidates file in archive - Updated active task status entry - Move manifest for any batch relocation - Brief completion summary ## Use Bundled Script - `scripts/archive-retention-audit.sh` generates current dry-run deletion candidates.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: cmp343-art/nascar (version 1.0.0)

# NASCAR Agent A dedicated NASCAR AI agent built to analyze, debate, and discuss everything stock car racing. ## Overview NASCAR Agent is designed to provide expert-level insight into the NASCAR Cup Series, Xfinity Series, and Craftsman Truck Series. It delivers race previews, post-race breakdowns, driver comparisons, playoff analysis, historical context, and strategic explanations in a confident and knowledgeable tone. This agent understands track types, tire strategy, cautions, pit cycles, manufacturer dynamics, team strength, and championship scenarios. ------------------------------------------------------------------------ ## Core Capabilities - Race previews and predictions\ - Post-race breakdowns and analysis\ - Playoff format explanations and projections\ - Driver vs. driver comparisons\ - Historical NASCAR debates\ - Silly Season rumors and contract speculation\ - Manufacturer and team performance analysis\ - Fantasy NASCAR guidance\ - Strategy breakdowns (tire wear, fuel windows, stage racing, cautions) ------------------------------------------------------------------------ ## Expertise Areas - NASCAR Cup Series\ - NASCAR Xfinity Series\ - NASCAR Craftsman Truck Series\ - Playoff system and championship format\ - Track classifications: - Superspeedways - Short tracks - Intermediate ovals - Road courses - Driver development and team pipelines\ - Crew chief and pit strategy impact\ - Manufacturer alliances and competition ------------------------------------------------------------------------ ## Tone & Behavior - Confident and analytical\ - Engaging and debate-ready\ - Clear explanations for new fans\ - Detailed breakdowns for hardcore fans\ - Capable of making bold but reasoned predictions ------------------------------------------------------------------------ ## Example Prompts - "Who is the favorite at Bristol this weekend?" - "Break down the 2011 championship battle." - "Is this driver a future Hall of Famer?" - "Predict the Championship 4." - "Explain stage racing to a new fan." - "What team has the best intermediate program?" ------------------------------------------------------------------------ ## Version 1.0.0 Initial release of NASCAR Agent.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: jiaqi-guo-0114/file-backup (version 1.0.0)

--- AIGC: ContentProducer: Minimax Agent AI ContentPropagator: Minimax Agent AI Label: AIGC ProduceID: [REDACTED_SECRET] PropagateID: [REDACTED_SECRET] ReservedCode1: 304502200aeae2a301f4803eddb248d5a31e8f539736d5b0e84643401248863a59f9eca1022100e7e82e85cab6b1ae66ca1a16448f3040078325c951f548293f5fa5db92d710b0 ReservedCode2: 3046022100fc82f0e2c81471b88f6b6b7a00b32cf8d6a29f3967440c99e21ba69202a99f7c022100fc848215ff03569403cb6b70bbf52dde4cb45e739cb8cae35ea576a2129e7f53 description: |- 修改文件前的自动备份工具。 当需要修改重要文件时，先备份再修改，改完后让用户检查，确认无误后删除备份。 name: file-backup --- # File Backup Skill ## 触发条件 修改重要文件前，特别是： - 配置文件 - 核心机制文件 - 用户指定的敏感文件 ## 工作流程 ### 1. 备份 检测到要修改重要文件时，先创建备份： ``` cp 原文件 备份目录/原文件.日期.bak ``` 例如：`cp config.json backups/config.json.2026-03-14.bak` ### 2. 执行修改 正常执行修改操作 ### 3. 主动提醒检查 ⚠️ 修改完成后，**必须主动让用户检查**： ``` 备份已创建：backups/xxx.bak 请检查文件，确认无误后告诉我"可以删除备份" ``` ### 4. 删除备份 收到用户确认后： ``` rm backups/xxx.bak 备份已删除 ``` ## 重要规则 1. **不备份不修改**：没有备份就不能改重要文件 2. **主动提醒**：改完后必须让用户检查，不能等用户忘 3. **确认才删**：必须等用户明确说"可以删除"才能删 4. **备份保留**：如果用户没确认，备份一直保留 5. **通用路径**：备份目录可自定义，默认为 `backups/` ## 配置（可选） 可以指定需要触发备份的文件类型： - 配置文件：config.json, settings.yaml - 核心文件：SOUL.md, MEMORY.md, AGENTS.md - 自定义：用户指定的其他文件 ## 示例 ``` [检测到要修改 config.json] → 备份：cp config.json backups/config.json.2026-03-14.bak → 执行修改 → 提醒："备份已创建 backups/config.json.2026-03-14.bak，请检查config.json，确认无误后告诉我'可以删除备份'" [用户确认] → 删除备份 ```


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: just-forever/just-test-skill (version 1.0.2)

## 这是一个测试 SKILL 仅供测试使用

path: b.md
content: ## 这是一个测试 SKILL

仅供测试使用

path: a.md
content: ## 这是一个测试 SKILL

仅供测试使用

Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: calwedbot-del/jungle-executor (version 1.0.0)

--- name: jungle-executor description: Enforces Jungle Laws (12 Iron Rules + Warden Protocols) for decision-making, trading, and task execution. Mandates strict adherence to prevent errors like IV traps, theta bleed, narrative bias. Features: rule validation, self-audit, violation auto-correction/kill-switches. Use when: (1) Trading/options (45min dead-man switch, IV bans, logic self-destruct), (2) High-stakes decisions requiring pack consensus over solo wolf, (3) Enforcing zero-tolerance discipline in workflows/agents. --- # Jungle Executor ## Core Mandate Innerize and execute the Jungle Laws as eternal sky. Violations = extinction. Pack > individual. Execute ruthlessly. ## Trigger Workflow 1. **Audit Input**: Before any decision/action, validate against 12 Laws + Warden Protocols (read references/laws.md). 2. **Consensus Check**: Prioritize data/team over solo narrative (Law 1). 3. **Risk Gates**: Block high-IV entries, enforce 45min timer (AGENTS.md lessons). 4. **Self-Destruct**: Hit logic-fail price/point? Immediate kill, no excuses. 5. **Log & Evolve**: Write violations to memory/YYYY-MM-DD.md; monthly MEMORY.md review (Law 12). ## Usage Patterns - **Trading**: Pre-entry: Check IV>10% ban, set 45min kill. Entry: Anchor self-destruct price. - **Tasks**: Multi-agent? Enforce resource share (Law 3), silence noise (Law 6). - **Validation Script**: Use scripts/validate-decision.py [decision-text] for automated checks. ## Resources - Laws & Protocols: references/laws.md - Trading Warden: references/warden-protocol.md - Audit Script: scripts/validate.py (python validate.py "Buy SPY 680P?")


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: sky-lv/oc-dream-rem (version 1.0.0)

--- name: dream-rem slug: oc-dream-rem version: 3.1.0 description: "Deep memory consolidation. Distills daily logs into topic files, removes outdated content. Triggers: dream-rem, deep memory consolidation, /dream-rem" license: MIT triggers: - 深度整合记忆 - 梦境整理 - 整合记忆 - dream-rem - "/dream-rem" --- # dream-rem v3.1.0 — 睡梦式记忆深度整合 定时深度整合：将分散的 daily 日记提炼合并到 topic 文件，删除过时内容，保持 `MEMORY.md` 简洁可用。 ## 触发条件 - sessionCount >= 5 **且** 距上次整合 > 24小时 - 或距上次整合 > 72小时（强制整合） - 手动：`/dream-rem` ## 工作流 ``` Step 1 — 准备：读 heartbeat-state.json，检查触发条件 Step 2 — Orient：读 MEMORY.md，扫描 topics/ 目录 Step 3 — Gather：扫描最近14天 daily 文件，识别新信息/过时/矛盾 Step 4 — Consolidate：执行整合（新增/更新/删除 topic 文件） Step 5 — Prune & Index：重写 MEMORY.md（≤200行），更新 heartbeat-state.json Step 6 — 输出执行报告 ``` ## 核心原则 1. MEMORY.md = 纯索引，每行一个指针 2. topic 文件 = 真实记忆，存在 topics/ 下 3. 删除被推翻的，不保留矛盾版本 4. 相对日期转绝对日期 ## 文件结构 ``` memory/ ├── MEMORY.md ← 纯索引（≤200行） ├── heartbeat-state.json ← {lastExtraction, lastDreamAt, sessionCount} ├── topics/ ← 真实记忆 └── YYYY-MM-DD.md ← 日记原料 ``` ## 执行报告格式 ``` ## 🌙 Dream 完成 · YYYY-MM-DD HH:MM 扫描窗口：14天 | 已扫描文件：N个 | 类型 | 数量 | |------|------| | 新增/更新 topic | N个 | | 清理过时记忆 | N条 | | MEMORY.md | N行 | ```


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: haiyangzhang888/mp3-tag-cleaner (version 1.0.0)

# MP3 Tag Cleaner 清除MP3文件元数据中的推广信息（标题、唱片集、艺术家、作者等），让你的音频库干净整洁。 **核心功能**：批量清除MP3文件的ID3v1和ID3v2标签中的推广信息，同时保留音频数据完整性。 ## 触发词 - 清除MP3属性 - 清理MP3标签 - 删除MP3推广信息 - 清除音频文件元数据 - 清理歌曲属性 - 删除音频推广 ## 功能说明 批量清除MP3文件中的ID3v1和ID3v2标签，包括： - 标题 (TIT2) - 唱片集 (TALB) - 艺术家 (TPE1) - 专辑艺术家 (TPE2) - 参与艺术家 (TPE3) - 作者 (TYER) - 评论 (COMM) - 封面图片 (APIC) - 等其他所有文本标签 ## 使用方法 用户指定要清理的文件夹路径后，执行以下步骤： 1. 生成该文件夹内所有MP3文件的路径列表（UTF-8编码） 2. 运行 `tools/id3clear2.exe` 清除标签 3. 验证清理结果 ## 工具文件 - `tools/id3clear2.exe` - 已编译的可执行程序 - `tools/ClearID3v12.cs` - C#源码（如需重新编译） ## 技术细节 - 直接操作MP3二进制文件，移除ID3v1（文件末尾128字节）和ID3v2（文件开头）标签 - 保留MP3音频数据和文件可播放性 - 使用临时目录策略避免百度网盘等文件夹的写保护问题 - 编译命令：`C:\Windows\Microsoft.NET\Framework64\v4.0.30319\csc.exe /nologo /out:tools/id3clear2.exe tools/ClearID3v12.cs` ## 注意事项 - 处理前程序会自动复制文件到临时目录，修改后再移回原位 - 会删除ID3v1标签（可能导致文件末尾128字节的专辑信息消失），但保留音频数据


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: kirkraman/jx-market-research (version 1.0.0)

--- name: "Market Research" description: "Research markets with sizing, segmentation, competitor mapping, pricing checks, and demand validation that turn fuzzy ideas into decision-ready..." homepage: "https://www.skillboss.co/skills/market-research" metadata: {"category":"research-intelligence","subcategory":"market-research","skill_id":"market-research","generated_day":"","seo_keywords":["market research","market research ai","market research automation","research intelligence skill"]} --- # Market Research Research markets with sizing, segmentation, competitor mapping, pricing checks, and demand validation that turn fuzzy ideas into decision-ready... ## Use When Use this skill for research work for analysts, founders, strategy teams. ## Workflow 1. Clarify the audience, business goal, constraints, and deliverable. 2. Produce the strongest first draft for the target use case. 3. Use the relevant SkillBoss capabilities to enrich assets or supporting data. 4. Refine the output for accuracy, readability, and actionability before delivery. ## SEO / GEO - Primary keywords: market research, market research ai, market research automation, research intelligence skill - Search intent: research - Canonical slug: `market-research` - Install query: Install Market Research with SkillBoss ## APIs Used - `chat` - `web_search` ## Suggested Prompt Research markets with sizing, segmentation, competitor mapping, pricing checks, and demand validation that turn fuzzy ideas into... ## Notes - Research markets with sizing, segmentation, competitor mapping, pricing checks, and demand validation that turn fuzzy ideas into decision-ready evidence. Use... - Review outputs before external publication or automated execution. ## SEO Keywords - market research - market research ai - market research automation - research intelligence skill


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: xmanatee/pubblue (version 5.1.2)

--- name: pubblue description: >- Publish and visualize output via the pubblue CLI, with live P2P browser sessions. license: MIT compatibility: Requires Node.js 18+ with npm/pnpm/npx. metadata: author: pub.blue version: "5.1.2" allowed-tools: Bash(pubblue:*) Bash(npx pubblue:*) Bash(node:*) Read Write --- # pubblue Use this skill when the user asks about publishing, showing, or visualizing agent output on pub.blue. ## Required CLI Version Use **pubblue CLI 0.6.9+**. ```bash pubblue --version npm i -g pubblue@latest ``` ## Setup ```bash # One-time auth pubblue configure --api-key pub_KEY # or echo "pub_KEY" | pubblue configure --api-key-stdin ``` Key source: <https://pub.blue/dashboard> By default, config is stored at `~/.openclaw/pubblue/config.json`. Override config directory with `PUBBLUE_CONFIG_DIR` env var (useful in sandboxed environments). For OpenClaw bridge mode, daemon runtime defaults to `OPENCLAW_WORKSPACE=~/.openclaw/workspace`. ## Core Commands ```bash pubblue create page.html pubblue create --slug demo --title "Demo" --public page.html cat notes.md | pubblue create pubblue get <slug> pubblue get <slug> --content pubblue update <slug> --file next.html pubblue update <slug> --title "New title" --public pubblue list pubblue delete <slug> ``` Notes: - Pub is built for agent-driven output sharing and live visualization. - Pubs are **private by default**. - `create` supports `--public/--private`, `--title`, `--slug`, `--expires`. - `update` supports `--file`, `--title`, `--public/--private`, `--slug`. - Content is optional: a pub can be live-only. ## Going Live Live is browser-initiated: the user opens the pub page and clicks **Go Live**; the daemon answers. 1. Start the agent daemon: ```bash pubblue start --agent-name "<agent-name>" # optional explicit mode: pubblue start --agent-name "<agent-name>" --bridge openclaw pubblue start --agent-name "<agent-name>" --bridge claude-code ``` 2. Check runtime status: ```bash pubblue status ``` 3. Send replies: ```bash pubblue write "Hello" pubblue write -c canvas -f /tmp/view.html ``` 4. Read incoming (manual/debug): ```bash pubblue read --follow -c chat pubblue read --all ``` 5. Stop daemon: ```bash pubblue stop ``` 6. Validate end-to-end: ```bash pubblue doctor pubblue doctor --wait-pong --timeout 30 pubblue doctor --skip-chat --skip-canvas ``` Important: - `write` waits for delivery confirmation. - `read` is consumptive; avoid multiple `read --follow` consumers on the same channel. ## Advanced Details (On Demand) Only when needed: - Show effective saved config: `pubblue configure` - Inspect runtime and bridge state: `pubblue status` - See command-specific options: `pubblue <command> --help`


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: suspicious | SkillSpector: clean (LOW)
Skill: austindixson/docs-bot (version 1.0.0)

--- name: docs-bot displayName: Docs Bot description: Scans and fetches the most up-to-date documentation for coding tasks. Use when building integrations (e.g. OpenRouter), implementing third-party APIs, or when the user asks for current docs, model lists, or API reference for a service. --- # Docs Bot — Up-to-Date Docs Scanner When working on integrations or any coding task that depends on external APIs or services, **fetch current documentation** instead of relying on training data. Docs and model lists change frequently. ## When to Apply - Building or debugging **OpenRouter** (or similar) integrations - Implementing or updating **third-party API** usage - User asks for "latest docs", "current API", "model list", or "official reference" - Choosing models, parameters, or SDK usage for a service ## Scan Workflow 1. **Identify the canonical doc base** for the task (e.g. `https://openrouter.ai/docs` for OpenRouter). 2. **Fetch the relevant URLs** using the web fetch tool: - Main docs/quickstart - API reference - Models/list page when model IDs, pricing, or capabilities matter 3. **Use the fetched content** to implement or correct code (endpoints, headers, request/response shapes, model IDs). 4. **Cite the URLs** you used so the user can verify or read more. ## OpenRouter — Canonical URLs When the task involves OpenRouter, fetch these for current behavior: | Purpose | URL | |--------|-----| | Quickstart & SDK | https://openrouter.ai/docs | | API reference (request/response, params) | https://openrouter.ai/docs/api/reference | | Models (IDs, pricing, context, filters) | https://openrouter.ai/models | | OpenAPI spec | https://openrouter.ai/openapi.json | **Integration checklist (OpenRouter):** - Base URL: `https://openrouter.ai/api/v1` - Chat completions: `POST .../chat/completions` - Auth header: `Authorization: Bearer <OPENROUTER_API_KEY>` - Optional headers: `HTTP-Referer`, `X-Title` for attribution - Model IDs include provider prefix (e.g. `openai/gpt-4o`, `anthropic/claude-sonnet-4`) - Confirm model ID and parameters from the **current** models page; names and availability change. ## Other Services For other APIs or SDKs: 1. Find the official docs root (e.g. `https://<service>.com/docs` or `/developer`). 2. Fetch quickstart + API reference (and models/catalog if applicable). 3. Prefer official docs over blog posts or third-party tutorials for correctness and recency. ## Output - Base implementation on **fetched** docs, not memory. - If a URL returns an error or empty content, say so and fall back to a web search or alternative URL. - Keep answers concise; link to the exact pages used for details.


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