OpenClaw/clawhub-security-signals huggingface dataset:
Skill: hyddd/tencent-ima-skill (version 1.0.1)

--- name: ima-agent-skill description: Control the IMA (ima.copilot) desktop application for AI search and private knowledge retrieval. --- # IMA Skill Control the **IMA (ima.copilot)** desktop application for AI search and private knowledge retrieval. ## Tools ### ima_search Launches IMA and performs a search. Supports "Private Knowledge Base" mode via special tags. - **query** (required): The search query. Prefix with `@个人知识库` or `@knowledge` to search your private knowledge base (requires `config.json`). - **autoclose** (optional): "true" to close the app after searching. Default: "false". **Implementation:** ```bash /usr/bin/python3 /opt/homebrew/lib/node_modules/clawdbot/skills/ima/scripts/ima.py "{query}" --autoclose="{autoclose}" ``` ## Configuration To enable private knowledge base search, you must providing your `knowledge_id`. The script looks for config in: 1. `~/.clawd_ima_config.json` 2. `skills/ima/config.json` **Format:** ```json { "knowledge_id": "your_id_string" } ``` ## Examples - **Public:** `clawdbot ima_search query="DeepSeek analysis"` - **Private:** `clawdbot ima_search query="@knowledge project update"`

path: config.json
content: knowledge_id: input your id
note: My private knowledge base ID for IMA

Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: suspicious | SkillSpector: suspicious (CRITICAL)
Skill: loutai0307-prog/bytesagain-meme-generator (version 1.0.0)

--- version: "2.0.0" name: bytesagain-meme-generator description: "Generate meme captions using trending templates and viral reaction formats. Use when creating meme text, picking templates, crafting reaction captions." author: BytesAgain homepage: https://bytesagain.com source: https://github.com/bytesagain/ai-skills --- # Meme Generator 表情包文案生成。梗图创作、热门模板、反应表情、图片配文、病毒传播。Meme text generator with trending templates. 表情包、梗图、搞笑。 ## 为什么选择这个工具 - ✅ 专为中文用户设计，理解中国市场和文化 - ✅ 多种命令覆盖不同场景需求 - ✅ 输出实用、可直接使用的内容 - ✅ 持续更新，紧跟行业最新趋势 ## 命令列表 | 命令 | 功能 | |------|------| | `create` | create | | `trending` | trending | | `reaction` | reaction | | `caption` | caption | | `template` | template | | `viral` | viral | --- *Meme Generator by BytesAgain* --- 💬 Feedback & Feature Requests: https://bytesagain.com/feedback Powered by BytesAgain | bytesagain.com ## Examples ```bash # Show help meme-generator help # Run meme-generator run ``` - Run `meme-generator help` for commands - No API keys needed ## Commands Run `meme-generator help` to see all available commands. ## Configuration Set `MEME_GENERATOR_DIR` to change data directory. Default: `~/.local/share/meme-generator/`


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: gechengling/finance-digital-avatar (version 3.0.1)

--- name: Financial Digital Avatar Creator slug: finance-digital-avatar description: AI-powered financial digital avatar creator — covers avatar design, voice cloning, personality settings, and brand integration for financial institutions' digital presence. Built for fintech and digital banking teams. Keywords: digital avatar, virtual spokesperson, brand persona, AI character, 数字人形象, 虚拟代言人, 品牌人设, AI角色, 数字人, AI主播, 虚拟主播, 虚拟形象, 品牌数字人. version: "3.0.1" --- # Financial Digital Avatar Creator / 金融数字人形象设计师 > **English:** AI-powered digital avatar creator — covers design, voice, personality, brand integration. > > **中文:** 数字人形象设计——覆盖形象、声音、人设、品牌整合。 --- ### 金融监管最新动态 [2026-05-25更新] | 动态类型 | 内容摘要 | 影响范围 | |---------|---------|---------| | 金融监管 | 2026年Q1：数字人金融应用合规要求提升 | 数字人运营合规标准需更新 | | 金融监管 | 数字人营销内容需满足合规审查和消费者保护要求 | 数字人运营合规标准需更新 | | 金融监管 | AI治理框架演进，数字人需关注可解释性和公平性 | 数字人运营合规标准需更新 | > **数据截止**: 2026-05-25 | 来源：证监会、NFRA、中证协、安永Q1分析 > **声明**: 以上动态供参考，具体以官方最新发布为准 ## Industry Pain Points / 行业痛点 | Pain Point / 痛点 | Impact / 影响 | Solution / 本Skill解决方案 | |------------------|-------------|------------------------| | **形象定位难** | 不知道要什么样的数字人 | 专业形象模板 | | **人设单薄** | 数字人缺乏个性 | 深度人设设计 | | **品牌不统一** | 各业务线数字人不一致 | 统一品牌规范 | | **交互不自然** | 对话太生硬 | 个性化对话设计 | --- ## Trigger Keywords / 触发关键词 **English Triggers:** digital avatar, virtual spokesperson, brand persona, AI character **中文触发词（优先）：** 数字人 / 虚拟形象 / 品牌人设 / AI角色 / 虚拟代言人 / 品牌IP --- ## Core Capabilities / 核心能力 ### 1. Avatar Design Templates / 形象模板 ```python AVATAR_TEMPLATES = { "专业顾问型": { "外观": "职业装，正式，专业可信", "声音": "沉稳，专业，语速适中", "人设": "金融专家，知识渊博，值得信赖", "适用场景": "产品讲解，理财建议" }, "亲和小姐姐型": { "外观": "休闲时尚，亲切友好", "声音": "活泼，温暖，有感染力", "人设": "贴心助手，懂你需求，帮你省心", "适用场景": "客服互动，科普讲解" }, "科技未来型": { "外观": "科技感，酷炫，前沿", "声音": "智能感，清晰，略带未来感", "人设": "科技先锋，引领创新", "适用场景": "创新产品，科技展示" } } ``` ### 2. Voice & Personality Settings / 声音与人设 ```python PERSONALITY_SETTINGS = { "语气": ["专业严谨", "亲切温和", "活泼俏皮", "沉稳大气"], "口头禅设计": { "专业型": "数据说话，理性决策", "亲和型": "为您服务，我很用心", "活泼型": "冲冲冲！安排！", "沉稳型": "稳中求进，行稳致远" } } ``` --- ## Disclaimer This skill provides digital avatar design tools for educational purposes.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: exeandino/moodle-ws (version 1.3.1)

--- name: moodle-ws description: > Integrar con Moodle 4.x usando Web Services REST. Usar esta skill cuando el usuario pida crear cursos, inscribir o desinscribir usuarios, crear o actualizar actividades (quiz, assignment, forum), enviar calificaciones, listar cursos/estudiantes, o enviar mensajes internos a alumnos. --- # Moodle Web Services (REST) – Skill ## 1. Requisitos - URL base de Moodle (ejemplo: https://moodle.ejemplo.com) - Token de Web Service con permisos adecuados - Credenciales guardadas en: ~/.openclaw/workspace/secrets/moodle-ws.json ## 2. Funciones habilitadas necesarias - core_user_get_users_by_field - core_course_create_courses / get_courses / get_courses_by_field - enrol_manual_enrol_users / unenrol_users - core_enrol_get_enrolled_users - mod_assign_create_assignments - mod_forum_add_instance - mod_quiz_add_instance - core_message_send_instant_messages - core_grades_update_grades ## 3. Ejemplos de uso natural - "Crea un curso llamado Introducción a Python" - "Inscribe a [REDACTED_SECRET] en el curso Matemáticas 1" - "Mandales un mensaje a todos los alumnos del curso Python" - "Mostrame todos los estudiantes del curso Inglés I" - "Ponle un 8 a [REDACTED_SECRET] en el quiz Parcial 1" ## 4. Seguridad - Nunca mostrar el token en el chat - Guardar URL + token fuera de Git - Regenerar token si fue expuesto ## 5. Autoría Skill moodle-ws diseñada por Exe Andino.


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: nikita-holban/gitignore-sync (version 0.1.3)

--- name: gitignore-sync description: Context-aware .gitignore generation backed by gitignore.io, not vibes. Make it boring again: accurate, idempotent, context-aware. --- # Gitignore Sync Generate high-confidence `.gitignore` rules from real repo signals and gitignore.io, then update safely via a managed block so manual rules stay untouched. ## Execution Rule Use `scripts/update_gitignore.py` as the only execution path. Do not fetch from the API directly in ad-hoc commands. Do not manually compose or rewrite `.gitignore` when this skill is selected. ## Workflow 1. Infer requested templates from the user prompt. 2. Detect likely templates from repository files and folders. 3. Run `scripts/update_gitignore.py` with `--prompt-text` and/or `--services`. 4. Let the script fetch combined template rules from `https://www.toptal.com/developers/gitignore/api/<templates>`. 5. Let the script write or update a managed block in `.gitignore`. 6. Preserve non-managed user sections in `.gitignore`. ## Run From the target repository root, run: ```bash python3 <skill-path>/scripts/update_gitignore.py \ --prompt-text "create .gitignore for flutter firebase vscode" \ --repo . ``` Use explicit templates when the user names exact services: ```bash python3 <skill-path>/scripts/update_gitignore.py \ --services flutter,firebase,visualstudiocode \ --repo . ``` ## Notes - Prefer passing both `--prompt-text` and `--services` when available. - Keep manual custom rules outside the managed block markers. - Re-run safely; the script replaces only the managed block. - Use `--rules-file` for offline/local testing when network access is blocked.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: suspicious | SkillSpector: clean (LOW)
Skill: julianengel/premium-domains (version 1.1.0)

--- name: premium-domains description: Search for premium domains for sale across Afternic, Sedo, Atom, Dynadot, Namecheap, NameSilo, and Unstoppable Domains. metadata: {"clawdbot":{"emoji":"💎","requires":{"bins":["curl"]}}} --- # Premium Domain Search Find domains for sale across major marketplaces. Free API, just curl. ## Usage ```bash curl -s "https://api.domaindetails.com/api/marketplace/search?domain=example.com" | jq ``` ## Marketplaces Checked - **Afternic** — GoDaddy's premium marketplace - **Sedo** — Global domain trading platform - **Atom** — Premium domain marketplace - **Dynadot** — Auctions & buy-now listings - **Namecheap** — Integrated registrar marketplace - **NameSilo** — Budget-friendly marketplace - **Unstoppable Domains** — Web3 domains ## Response Fields - `found` — whether any listings exist - `marketplaces.<name>.listing.price` — price in cents or dollars - `marketplaces.<name>.listing.currency` — USD, EUR, etc. - `marketplaces.<name>.listing.url` — direct link to listing - `marketplaces.<name>.listing.listingType` — buy_now, auction, make_offer ## Rate Limits - 100 requests/minute (no auth needed)


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: santidev95/scryfall-card (version 1.0.0)

--- name: scryfall-mtg description: "Search and retrieve Magic: The Gathering card data using the Scryfall API. Use this skill when the user asks about MTG cards, wants to search for cards by name, type, color, mana cost, oracle text, set, or any other card attribute. Also use for getting card images, prices, rulings, legality information, or random cards. Triggers include mentions of MTG, Magic, Magic: The Gathering, card names, deck building questions, or requests for card information." --- # Scryfall MTG Card Search Search for Magic: The Gathering cards using the Scryfall API. ## API Overview Base URL: `https://api.scryfall.com` **Required Headers:** ```python headers = { "User-Agent": "OpenClawMTGSkill/1.0", "Accept": "application/json" } ``` **Rate Limiting:** Insert 50-100ms delay between requests (max 10 req/sec). ## Core Endpoints ### Search Cards ``` GET /cards/search?q={query} ``` Parameters: - `q` (required): Fulltext search query - `unique`: cards|art|prints (default: cards) - `order`: name|set|released|rarity|color|usd|tix|eur|cmc|power|toughness|edhrec|penny|artist|review - `dir`: auto|asc|desc - `page`: Page number for pagination ### Named Card Lookup ``` GET /cards/named?exact={name} GET /cards/named?fuzzy={name} ``` Use `fuzzy` for partial matches (e.g., "jac bele" → "Jace Beleren"). Add `&set={code}` to limit to specific set. ### Random Card ``` GET /cards/random GET /cards/random?q={query} ``` ### Card by ID ``` GET /cards/{id} GET /cards/{set_code}/{collector_number} ``` ### Autocomplete ``` GET /cards/autocomplete?q={partial_name} ``` Returns up to 20 card name suggestions. ## Search Syntax Reference See `references/search_syntax.md` for the complete search syntax guide. **Quick examples:** - `c:red pow=3` - Red cards with power 3 - `t:merfolk t:legend` - Legendary merfolk - `o:"draw a card"` - Cards with "draw a card" in text - `cmc=3 r:rare` - 3-mana rares - `e:dom` - Cards from Dominaria - `f:standard` - Standard legal cards - `usd<1` - Cards under $1 ## Implementation Use the provided script for common operations: ```bash python3 scripts/scryfall_search.py search "lightning bolt" python3 scripts/scryfall_search.py named --exact "Black Lotus" python3 scripts/scryfall_search.py random python3 scripts/scryfall_search.py random --query "t:dragon" ``` Or make direct API calls with proper headers and rate limiting. ## Card Object Key Fields When displaying card info, prioritize these fields: - `name`, `mana_cost`, `type_line` - `oracle_text`, `power`, `toughness` - `image_uris.normal` (for card image) - `prices.usd`, `prices.usd_foil` - `legalities` (format legality) - `set_name`, `rarity` For double-faced cards, check `card_faces` array. ## Error Handling - 404: Card not found - 422: Invalid search query - 429: Rate limited (wait and retry) Always validate responses have `object` field; if `object: "error"`, check `details` for message.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: tiktokmanagerhere889-coder/tutorclaw-shim (version 1.0.0)

--- name: tutorclaw-shim version: 1.0.0 description: "Offline fallback for TutorClaw. When the TutorClaw MCP server is unreachable, follow these PRIMM-Lite teaching instructions for Chapters 1-5 of the beginner programming course." --- # TutorClaw Shim: Offline Fallback ## Teaching Method: PRIMM-Lite 1. **Predict**: Show code snippet, ask learner to predict output BEFORE running, wait for answer 2. **Run**: Show actual output, compare to prediction 3. **Investigate**: Ask learner to modify code, explain what changed and why **Rule**: Never skip the predict step ## Chapter Coverage - **Chapter 1**: Variables, assignment, basic types (int, float, str, bool) - **Chapter 2**: Conditionals (if, elif, else), comparison operators - **Chapter 3**: Loops (for, while), range, loop control (break, continue) - **Chapter 4**: Functions (def, parameters, return values, scope) - **Chapter 5**: Data structures (lists, dictionaries, tuples, basic operations) ## Limitations (Tell the Learner) At START of each conversation tell learner: offline mode, limited capabilities **Cannot do**: track progress, personalized exercises, execute code, access Chapter 6+ **If asked about Chapter 6+**: say advanced content needs full TutorClaw service ## Response Style - Short explanations, prefer code over paragraphs - Encouraging language - Wrong predictions = learning opportunity not mistake - End each interaction by suggesting next concept


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: shine8592/zh-novel-writer (version 1.0.3)

--- name: zh-novel-writer description: > 批量生成网络小说章节。通过环境变读取 API keys 并调用外部 LLM API (ModelScope, Fyra, Ph8) 生成中文小说内容。 使用场景：用户给出大纲并要求"批量生成章节"、"写第X章到第Y章"、"后台静默写作"。 前置要求：需设置环境变量 NOVEL_MODELSCOPE_KEY 或 NOVEL_FYRA_KEY 或 NOVEL_PH8_KEY 至少一个。 外部依赖：Python 3, pip install httpx。 NOT for: 单章精修、人工审稿、出版级校对。 --- # Novel Writer — 网络小说批量生成 ## 前置要求 - Python 3 + `pip install httpx` - 至少设置一个 API key 环境变量： ```bash export NOVEL_MODELSCOPE_KEY="your_modelscope_key" export NOVEL_FYRA_KEY="your_fyra_key" export NOVEL_PH8_KEY="your_ph8_key" ``` ## External API Endpoints | 服务 | URL | 环境变量 | |------|-----|---------| | ModelScope | https://api-inference.modelscope.cn/v1/chat/completions | NOVEL_MODELSCOPE_KEY | | Fyra | https://Fyra.im/v1/chat/completions | NOVEL_FYRA_KEY | | Ph8 | https://ph8.co/v1/chat/completions | NOVEL_PH8_KEY | 用户文本会发送到以上 API 端点以生成小说内容。 ## Quick Start 1. 确认大纲文件和章节范围 2. 读 `references/api-config.md` 获取 API 配置说明 3. 运行 `scripts/batch_generate.py` ## Workflow ``` 大纲 → 逐章prompt → 逐个调用外部 LLM API → 分段生成 → 保存文件 ``` ## 脚本说明 `scripts/batch_generate.py`: - 分段生成章节（单次 API 输出有限制时自动分段追加） - 多 API 容错：按 ModelScope → Fyra → Ph8 顺序尝试 - 429 限流自动等 30 秒重试 - 未配置 API key 的 API 会被自动跳过 ## References - API 配置 → `references/api-config.md` - Prompt 模板 → `references/prompt-template.md`


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

--- name: skill-preflight-bootstrap description: 为新仓库一键初始化“任务前先查技能”的工作流。适用于初始化技能预检新仓库、给新仓库装技能工作流、迁移 skill preflight、把当前流程封装到另一个仓库，或把技能预检、项目级 hooks、`.learnings/` 和团队使用说明快速落到目标仓库时。 --- # 新仓库技能预检初始化 把“先查技能，再执行任务”的仓库级能力一键落到目标目录。 ## 什么时候用 在下面这些场景触发： - 你想把当前仓库的技能预检流程迁移到另一个新仓库 - 你希望新仓库默认带上 `skill-preflight.py` - 你需要同时生成项目级 `.codex/settings.json` / `.claude/settings.json` - 你希望顺手创建 `.learnings/` 和团队说明文档 ## 快速使用 ### 1. 先决定目标目录 目标目录通常是一个新的或尚未配置这套流程的仓库。 ### 2. 执行 bootstrap 脚本 从本 skill 根目录运行： ```bash python3 scripts/bootstrap-skill-preflight.py /path/to/target-repo ``` 如果只想先看将要写入什么： ```bash python3 scripts/bootstrap-skill-preflight.py /path/to/target-repo --dry-run ``` 如果目标仓库里已有同名模板文件，且你确认要覆盖： ```bash python3 scripts/bootstrap-skill-preflight.py /path/to/target-repo --force ``` ## 它会写什么 - `scripts/skill-preflight.py` - `scripts/hooks/skill-preflight-reminder.sh` - `scripts/hooks/error-learning-reminder.sh` - `.codex/settings.json` - `.claude/settings.json` - `.learnings/LEARNINGS.md` - `.learnings/ERRORS.md` - `.learnings/FEATURE_REQUESTS.md` - `docs/skill-preflight-usage.md` - `AGENTS.md` 中的技能预检片段 ## 使用原则 - 默认只写项目级配置，不碰用户全局环境 - 已存在的 `AGENTS.md` 只追加片段，不整文件覆盖 - 已存在的设置文件会合并 hooks，而不是粗暴覆盖 - 默认跳过已存在的模板文件；只有 `--force` 才覆盖 ## 验证 落地后建议至少做三步检查： 1. 验证 JSON： - `python3 -m json.tool /path/to/target-repo/.codex/settings.json` - `python3 -m json.tool /path/to/target-repo/.claude/settings.json` 2. 验证预检脚本： - `python3 /path/to/target-repo/scripts/skill-preflight.py "react performance"` 3. 检查 `AGENTS.md` 是否只追加一次技能预检片段 ## 参考 - 示例和验收方式见 `references/examples.md` ## 注意 如果目标仓库的 `AGENTS.md` 或设置文件有强烈的项目定制逻辑，先用 `--dry-run` 看计划，再决定是否执行。


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: chenxundaozu/murasame-feishu-voice (version 0.1.0)

--- name: murasame-feishu-voice description: Feishu 语音气泡技能：使用丛雨（Murasame）语音包发送语音；若可表达则按标签发送语音并同步发送中文文本；支持开关控制、标签映射与关键词回退。 --- # Murasame Feishu Voice ## 能做什么 - 当回复适合用丛雨语音表达时，给文本加上标签（如 `[agree]` / `[thanks]` / `[greet_night]`） - 发送 **飞书语音气泡**，并**同步发送原本的中文回复**（文字先到，语音异步） - 若未匹配合适标签，输出 `NO_VOICE`，由上层改为仅发文本 - 支持手动开关语音：`/murasame on` 或 `/murasame off` ## 适用场景（触发建议） - 飞书对话里希望用丛雨语音气泡表达情绪（称赞/问候/道歉/同意等） - 想在语音之外保留可读的中文文本 - 需要可控开关，随时暂停语音发送 ## 运行流程 1. 解析标签/关键词 → 选取对应语音文件 2. 先发送中文文本 3. 异步发送语音气泡 ## 开关控制 - 发送 `/murasame off` 关闭语音（写入状态文件） - 发送 `/murasame on` 开启语音 - 环境变量也可覆盖：`MURASAME_VOICE=off` ## 环境与依赖 - Feishu 凭证：`FEISHU_APP_ID` / `FEISHU_APP_SECRET` - 接收者 OpenID：`FEISHU_RECEIVER`（**仅环境变量**） - `ffmpeg` + `ffprobe` - 丛雨语音包路径：`C:\Users\chenxun\.nanobot\workspace\murasame-voice\audios` ## 使用方式 ### 发送带标签的回复 ``` python scripts/send_murasame_voice.py "[thanks] 谢谢你" ``` ### 返回值 - `OK: sent text+voice (async) for <category>` → 已发送文字，语音异步发送中 - `NO_VOICE` → 未匹配，改用纯文本 - `VOICE_DISABLED` → 被开关关闭 ## 标签与映射 - 标签与音频文件在 `references/mapping.json` - 默认标签： - greetings: greet_morning / greet_noon / greet_evening / greet_night - basic: agree / thanks / apology / refuse / wait / rest - care: encourage / care / compliment / explain ## 备注 - 若你想新增标签或替换音频文件，只需编辑 `mapping.json` - 建议由上层对话逻辑判断是否加标签（即“能用丛雨语音表达就发语音”）

path: references/mapping.json
content: {
  "agree": ["mur314_016.mp3", "mur312_012.mp3"],
  "thanks": ["mur313_093.mp3"],
  "apology": ["mur302_032.mp3"],
  "refuse": ["mur307_066.mp3"],
  "wait": ["mur303_080.mp3", "mur306_055.mp3", "mur311_023.mp3"],
  "rest": ["mur313_037.mp3", "mur312_031.mp3", "mur311_058.mp3"],
  "encourage": ["mur312_045.mp3", "mur313_041.mp3"],
  "care": ["mur312_027.mp3", "mur313_041.mp3"],
  "compliment": ["mur313_049.mp3"],
  "explain": ["mur302_097.mp3"],
  "greet_morning": ["mur002_001.mp3", "mur315_023.mp3", "mur302_001.mp3"],
  "greet_noon": ["mur310_058.mp3"],
  "greet_evening": ["mur107_015.mp3"],
  "greet_night": ["mur305_166.mp3", "mur314_019.mp3", "mur314_213.mp3"]
}


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: riprsa/grepwrapper (version 0.3.0)

--- name: grepwrapper description: Search exact code matches across public GitHub repos using grep.app via the grepwrapper CLI. metadata: {"openclaw":{"emoji":"🔎","requires":{"bins":["grepwrapper"],"env":[]},"install":[{"id":"npm","kind":"node","package":"git+https://github.com/riprsa/grepwrapper.git","bins":["grepwrapper"],"label":"Install grepwrapper CLI"}]}} --- # grepwrapper Use this skill when the user asks to: - find exact code matches on GitHub - locate repo/file/path occurrences for a snippet - run grep.app code search from CLI ## Install ```bash npm i -g git+https://github.com/riprsa/grepwrapper.git ``` ## Standard usage ```bash grepwrapper search --q "PendingBalanceAt(ctx context.Context, account common.Address) (*big.Int, error)" ``` Options: - `--q <query>` required - `--case` case-sensitive - `--words` whole-word (mutually exclusive with `--regexp`) - `--regexp` regex mode (mutually exclusive with `--words`) - `--page <n>` page number Examples: ```bash grepwrapper search --q "QMD" --case --regexp grepwrapper search --q "QMD" --case --words --page 2 ``` ## Expected output CLI returns summary lines: - `time=<ms> total=<n> returned=<n>` - one line per hit: `- <repo>:<path> (matches=<count>)` ## Agent behavior - Return top matches with direct GitHub links when possible. - If many matches exist, summarize and ask whether user wants next page / narrower filters. - Prefer exact query first, then widen with `--regexp` only when needed.


Security scan verdicts — ClawScan: clean | static analysis:  | VirusTotal: suspicious | SkillSpector: clean (LOW)
Skill: zvirb/google-docs-read-document (version 1.0.2)

--- name: Google Docs Read Document description: Atomic node skill to read a Google Doc using the gog CLI. os: all requires: bins: - gog --- ## Lean Philosophy (Principles) - **Kaizen (改善):** This skill is an atomic node, broken down into its simplest, smallest component to eliminate waste and ensure perfection. - **Standardized Work (Hyojun Sagyo):** This node represents the most efficient, standardized path for this specific task before automation. - **Jidoka (自働化):** This node includes autonomous defect detection. It relies on the CLI's self-healing loop and will report errors if reading fails. # Google Docs Read Document This skill allows the agent to read the plain text contents of a Google Document using the native CLI. ## Cognitive Directives WHEN [The contents of a Google Doc need to be read] THEN [Execute the native terminal command `gog docs cat <docId>`] ## Schema Example ```json { "command": "gog docs cat doc_id_123" } ``` ## Expected Output The plain text content of the Google Doc.


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