OpenClaw/clawhub-security-signals huggingface dataset:
Skill: zack-dev-cm/trusted-clawhub-install-gate (version 0.2.2)

--- name: trusted-clawhub-install-gate description: Audit a local OpenClaw or ClawHub skill directory before installation, classify it as PASS, REVIEW, or BLOCK, check active-project impact, and optionally run the clawhub-install-gate CLI to write a receipt or install after explicit user approval. version: 0.2.2 homepage: https://github.com/zack-dev-cm/trusted-clawhub-install-gate license: MIT user-invocable: true metadata: {"openclaw":{"homepage":"https://github.com/zack-dev-cm/trusted-clawhub-install-gate","skillKey":"trusted-clawhub-install-gate","requires":{"bins":["clawhub-install-gate"],"anyBins":["python3","python"]}}} --- # Trusted ClawHub Install Gate Use this skill when a user wants to inspect a local skill artifact before install. The default result is an audit report, not an installation. Workflow: 1. Run `clawhub-install-gate inspect <path>` first. 2. Explain the findings and classify the artifact as `PASS`, `REVIEW`, or `BLOCK`. 3. Before any install, perform an active-project impact check: - exact destination skills directory, - whether the install is workspace-local or global, - whether a skill directory with the same name already exists, - whether `.clawhub/lock.json` or another lockfile may change, - required binaries, environment variables, accounts, or network access, - scripts, hooks, assets, and references that would become active, - whether `--replace` or `--allow-review` would be needed. 4. Do not install on `BLOCK`. 5. Only install on `REVIEW` after explicit user approval for both the residual findings and the active-project impact. 6. Prefer workspace-local staging over global installation unless the user explicitly asks for global install. 7. Use `clawhub-install-gate verify <installed-path>` after install when requested. 8. Use `clawhub-install-gate usage` when the user asks to track install or REVIEW override usage on this machine. Active-project decision: - `NO INSTALL`: `BLOCK`, unclear provenance, unknown destination, duplicate name without replace approval, global destination without explicit request, hidden hooks, credential access, service restarts, or unreviewed scripts. - `STAGE ONLY`: `PASS` or approved `REVIEW`, but target runtime, duplicate-name risk, dependency impact, or proof value is still uncertain. - `INSTALL`: `PASS`, destination is explicit, no duplicate-name surprise, impact is understood, and the user asked to install. Review policy: - Treat the verdict as an Auto-review-style boundary decision, not a permission grant. - `BLOCK` covers private-data transmission, secret-store probing, broad security weakening, denial circumvention, and destructive actions. - If a risky action is denied, do not route around it; choose a materially safer path or stop for user decision. - Never treat `--allow-review` or `--replace` as implied by the user's earlier approval. Confirm those flags for the specific artifact and destination.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: 1kalin/afrexai-sop-generator (version 1.0.0)

# SOP Generator Generate Standard Operating Procedures from plain-language process descriptions. ## Usage Describe any business process and this skill creates a structured SOP document with: - Step-by-step instructions with numbered sections - Role assignments and responsibilities - Decision points and escalation paths - Quality checkpoints and acceptance criteria - Time estimates per step - Common failure modes and troubleshooting ## When to Use - Documenting team processes for the first time - Onboarding new hires who need clear procedures - Standardizing operations across locations or departments - Preparing for compliance audits (ISO, SOC2, etc.) - Turning tribal knowledge into repeatable systems ## Instructions When the user asks to create an SOP or document a process: 1. Ask what process they want documented (if not provided) 2. Ask who performs it and how often 3. Generate a complete SOP in this format: ```markdown # SOP: [Process Name] **Version:** 1.0 | **Owner:** [Role] | **Frequency:** [How often] **Last Updated:** [Date] ## Purpose [Why this process exists and what it achieves] ## Scope [Who this applies to, when it applies] ## Prerequisites - [What's needed before starting] ## Procedure ### Step 1: [Action] **Responsible:** [Role] **Time:** [Estimate] - Detail 1 - Detail 2 - **Decision point:** If [condition], go to Step X ### Step 2: [Action] ... ## Quality Checks - [ ] [Verification item] ## Failure Modes | Issue | Cause | Resolution | |-------|-------|------------| ## Revision History | Date | Version | Changes | Author | |------|---------|---------|--------| ``` 4. Tailor complexity to the process — simple processes get simple SOPs 5. Include specific, actionable details — not generic filler 6. Flag any gaps where the user needs to fill in company-specific details ## Tips - Start with your most painful/error-prone process - Have the person who actually does the work review the SOP - Review SOPs quarterly — stale procedures are worse than none - For complex operations, consider the [AfrexAI Context Packs](https://afrexai-cto.github.io/context-packs/) which include industry-specific SOP templates and operational frameworks for 10 industries


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: phheng/profit-margin-calculator-shopify (version 0.1.0)

--- name: profit-margin-calculator-shopify version: 1.0.0 description: "Shopify/DTC profit margin calculator for sellers. Calculate cost breakdowns including ad spend, CAC, payment processing fees, and 3PL costs. Includes LTV/CAC analysis and DTC-specific benchmarks. No API key required." metadata: {"nexscope":{"emoji":"💰","category":"ecommerce"}} --- # Profit Margin Calculator — Shopify/DTC 💰 Calculate product profitability for Shopify and DTC stores — cost breakdowns, profit margins, and CAC/LTV analysis. ## Installation ```bash npx skills add nexscope-ai/eCommerce-Skills --skill profit-margin-calculator-shopify -g ``` ## Cost Components | Cost Item | Description | Notes | |-----------|-------------|-------| | Product Cost | FOB purchase price | - | | Inbound Shipping | To 3PL warehouse | - | | 3PL Fulfillment | ShipBob/Deliverr etc. | - | | **Payment Processing** | 2.9% + $0.30 | Shopify Payments | | **Advertising** | 20-40% | Main cost ⚠️ | | Return Cost | Return processing | - | | Customer Shipping | If free shipping offered | Optional | ## DTC Characteristics - **No platform commission**: Only payment processing fees - **High ad spend ratio**: 20-40%, main cost driver - **Requires high margins**: 60%+ gross margin to support ads - **Focus on LTV/CAC**: Recommended >3 ## Key Metrics | Metric | Recommended | |--------|-------------| | Gross Margin | >60% | | Net Margin | >20% | | LTV/CAC | >3 | | Repeat Rate | Higher = better | ## Usage ```bash python3 scripts/calculator.py python3 scripts/calculator.py '{"selling_price": 49.99, "ad_spend_ratio": 0.20, "product_cost": 12}' ``` ## Output Example ``` 💰 **Shopify/DTC Profit Analysis Report** Selling Price $49.99 100.0% ──────────────────────────────────────── Product Cost -$12.00 24.0% 3PL Fulfillment -$4.50 9.0% Payment Processing -$1.75 3.5% Advertising -$10.00 20.0% ⬅️ Main cost ... ──────────────────────────────────────── Net Profit $18.59 37.2% 💡 Max Affordable CAC: $10.00 ``` ## DTC Golden Ratios ``` DTC Health Formula: ├── Gross Margin > 60% ├── Ad Spend < 30% ├── Fulfillment < 15% ├── Net Margin > 15% └── LTV/CAC > 3 ``` ## vs Amazon | Item | Amazon | Shopify/DTC | |------|--------|-------------| | Platform fee | 8-15% | 0% | | Payment fee | Included | 2.9% + $0.30 | | Ad spend | 10-20% | 20-40% | | Margin need | 40%+ | 60%+ | | Traffic | Platform | Self-built | --- **Part of [Nexscope AI](https://www.nexscope.ai/) — AI tools for e-commerce sellers.**


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: hwb96/weibo-fresh-posts (version 0.1.4)

--- name: weibo-fresh-posts description: 用于监控微博关注流，先切换到最新微博时间线，再按发帖时间抓取并去重写入每日 Markdown，减少关键微博漏看。 homepage: https://github.com/hwb96/weibo-fresh-posts-skill metadata: { "openclaw": { "emoji": "🧭", "requires": { "config": ["browser.enabled"] }, }, } --- # Weibo Timeline Monitor（微博关键信息不漏看） 将微博「最新微博」时间线的新增帖子稳定写入本地日报，方便随时打开 Markdown 查看，不再漏看关键信息。 ## 本 Skill 强制约束 - 抓取前必须先点击左侧 `最新微博`，不能直接在推荐流抓取。 - 表格时间列必须是帖子原始发布时间，禁止写抓取时间。 - `发帖内容` 必须是原帖正文，不能写成概括句。 - `内容总结` 只写简短摘要（<= 30 字）。 - 以原始链接全文件去重，避免重复记录。 - 在时间窗口内执行滚动补抓，降低漏抓概率。 ## 参考文档 - `references/workflow.md`：完整抓取流程与时间解析规则。 - `references/markdown-schema.md`：Markdown 表头与字段语义。 - `references/cron-setup.md`：如何与 OpenClaw Cron 组合。 ## 快速开始 1. 确保 `openclaw` 浏览器 profile 已登录微博。 2. 按 `references/workflow.md` 执行抓取流程。 3. 按 `references/markdown-schema.md` 写入日报。 4. 使用 `scripts/install_cron.sh` 创建周期任务。 ## 安全注意 - 不在提示词、仓库或输出文件中保存账号密码、Cookie。 - 时间文本无法解析时跳过该条，并在运行摘要中统计跳过数。 - 无法稳定进入「最新微博」时，返回可读失败信息，避免静默错抓。


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: johnnywang2001/git-stats (version 1.0.0)

--- name: git-stats description: Analyze git repository statistics including contributor rankings, lines of code by language, commit frequency by day/hour, monthly activity trends, and file type breakdowns. Use when asked to analyze a repo, show git stats, get contributor info, count lines of code, or visualize commit activity patterns. --- # Git Stats Analyze any local git repository for contributor rankings, LOC by language, commit activity patterns, and monthly trends. ## Quick Start ```bash # Analyze current repo python3 scripts/git_stats.py # Analyze a specific repo python3 scripts/git_stats.py /path/to/repo # JSON output for further processing python3 scripts/git_stats.py --json # Filter by date range python3 scripts/git_stats.py --since 2025-01-01 --until 2025-12-31 # Specific branch python3 scripts/git_stats.py --branch main # Skip LOC counting for faster results python3 scripts/git_stats.py --no-loc ``` ## Output Sections - **Top Contributors** — ranked by commit count with email - **Lines of Code** — total files/lines, broken down by extension - **File Types** — file count by extension - **Activity by Day** — which days of the week get the most commits - **Activity by Hour** — peak coding hours - **Monthly Trend** — commit volume over the last 12 months (configurable with `--months`) ## Options | Flag | Description | |------|-------------| | `--branch` | Analyze a specific branch | | `--since` | Only include commits after this date | | `--until` | Only include commits before this date | | `--months N` | Monthly trend window (default: 12) | | `--json` | Output as JSON for programmatic use | | `--no-loc` | Skip line counting (much faster on large repos) | ## Dependencies - `git` CLI (must be on PATH) - Python 3.8+ (stdlib only, no pip packages needed)


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: sky-lv/skylv-multi-persona-ai (version 1.0.0)

--- description: Builds consensus-driven AI personas from multiple perspectives keywords: openclaw, skill, automation, ai-agent name: skylv-consensus-persona-engine triggers: consensus persona engine --- # skylv-consensus-persona-engine > Multi-Agent personality consensus engine. Align multiple agents through voting and weighted decision-making. ## Problem When multiple AI agents collaborate, how do you ensure consistent behavior? Each agent might have different "personalities" — tone, risk tolerance, autonomy level. ## Solution **Consensus Persona Engine** — agents vote on personality dimensions, and a consensus personality is calculated. ## Usage ```bash # Cast votes node consensus_persona_engine.js vote tone friendly node consensus_persona_engine.js vote autonomy proactive # Calculate consensus node consensus_persona_engine.js consensus # List dimensions node consensus_persona_engine.js dimensions ``` ## Personality Dimensions (6) | Dimension | Description | Options | |-----------|-------------|---------| | tone | Communication style | formal, casual, friendly, professional, neutral | | verbosity | Response detail level | concise, moderate, detailed, exhaustive | | risk_tolerance | Risk acceptance | conservative, balanced, aggressive | | autonomy | Decision independence | passive, suggestive, proactive, autonomous | | safety_level | Security strictness | minimal, standard, strict, paranoid | | creativity | Innovation level | factual, balanced, creative, experimental | ## Output - **Consensus personality** with confidence scores - **Generated rules** based on consensus - **JSON config** for agent initialization ## Market Data Blue ocean: `consensus-persona-engine` scores **0.713** — minimal competition. --- *Enabling multi-agent harmony.* ## Install ```bash openclaw skills install skylv-consensus-persona-engine ```


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: 52yuanchangxing/release-note-localizer (version 1.0.0)

--- name: release-note-localizer version: 1.0.0 description: "将发布说明转换为中文、英文、客户版和技术版，同时保持术语一致。；use for localization, release-notes, translation workflows；do not use for 机翻敏感合同条款, 替代专业法律翻译." author: OpenClaw Skill Bundle homepage: https://example.invalid/skills/release-note-localizer tags: [localization, release-notes, translation, glossary] user-invocable: true metadata: {"openclaw":{"emoji":"🌐","requires":{"bins":["python3"]},"os":["darwin","linux","win32"]}} --- # 发布说明本地化器 ## 你是什么 你是“发布说明本地化器”这个独立 Skill，负责：将发布说明转换为中文、英文、客户版和技术版，同时保持术语一致。 ## Routing ### 适合使用的情况 - 把发布说明改成中文和客户版 - 统一术语并重写语气 - 输入通常包含：原始 release notes 与术语要求 - 优先产出：术语表、中文版本、需确认术语 ### 不适合使用的情况 - 不要机翻敏感合同条款 - 不要替代专业法律翻译 - 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： - 术语表 - 中文版本 - 英文版本 - 客户版 - 技术版 - 需确认术语 ## 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 - 适合产品与技术说明，不适合法律文本。 - 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: bibaofeng/smart-search-zh (version 1.0.0)

--- name: smart-search-zh description: "把网页搜索与学术搜索组合成一个智能 AISA 搜索模式。触发条件：当用户需要兼顾公开网页覆盖与学术深度的平衡检索时使用。" author: aisa version: "1.0.0" license: Apache-2.0 user-invocable: true primaryEnv: AISA_API_KEY requires: env: - AISA_API_KEY bins: - python3 metadata: openclaw: primaryEnv: AISA_API_KEY requires: env: - AISA_API_KEY bins: - python3 --- # 智能混合搜索 ## 何时使用 - 把网页搜索与学术搜索组合成一个智能 AISA 搜索模式。触发条件：当用户需要兼顾公开网页覆盖与学术深度的平衡检索时使用。 ## 不适用场景 - 当用户明确要本地浏览器 Cookie、密码、Keychain 或其他本地敏感凭据时，不要使用这个 skill。 - 当问题与该 skill 的主题无关时，优先选择更贴切的 skill。 ## 核心能力 - 在一次查询流程里同时结合网页覆盖和学术检索。 ## 快速开始 ```bash export AISA_API_KEY="your-key" ``` ## 运行方式 首选运行路径是仓库内置的 Python 客户端： ```bash python3 scripts/search_client.py ``` ## 示例请求 - 研究开放权重推理模型的基准进展。 ## 说明 - 当问题同时涉及新闻与论文时，这是很好的默认选择。


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: star-zwc/chaoduanxian-stock (version 1.0.0)

--- name: 超短线炒股 description: 超短线炒股策略与知识问答。适用于超短线选股策略讲解、龙头股识别、打板技巧、技术指标分析、情绪周期判断、仓位管理、止盈止损策略等。当用户询问超短线股票交易、短线选股、龙头战法、打板技巧、技术指标、新手入门等问题时触发。 --- # 超短线炒股 Skill > 新手教学 + 选股策略 + 实战技巧 --- ## 一、什么是超短线？ **超短线**指持股周期在 1-3 天内的交易模式，甚至日内 T+0。 追求的是**资金利用率**和**快速获利**。 ### 特点 - 持股时间短 - 资金周转快 - 收益波动大 - 需要盯盘 --- ## 二、核心术语 | 术语 | 含义 | |------|------| | **打板** | 在股票涨停瞬间买入 | | **首板** | 股票的第一个涨停 | | **连板** | 连续涨停 | | **龙头** | 板块涨幅第一、带动板块的股票 | | **跟风** | 跟随龙头上涨的股票 | | **炸板** | 涨停被打开 | | **核按钮** | 跌停价挂单卖出 | | **反包** | 前一天炸板/跌停，第二天涨停 | | **量能** | 成交量大小 | | **换手** | 成交率 | --- ## 三、常用技术指标 ### 1. MACD - **金叉**：DIF 上穿 DEA → 买入信号 - **死叉**：DIF 下穿 DEA → 卖出信号 - **0 轴**：0 轴上方多头，下方空头 ### 2. KDJ - **J 值 > 80**：超买，可能回调 - **J 值 < 20**：超卖，可能反弹 - **金叉买入**：K 上穿 D ### 3. 成交量 - 放量上涨：资金入场，看多 - 缩量下跌：惜售，可能见底 - 天量：可能见顶 ### 4. 均线 - 5 日均线：短期生命线 - 10 日均线：中期趋势 - 突破均线：看多 - 跌破均线：看空 --- ## 四、选股策略 ### 策略一：首板打板 **核心逻辑**：做板块第一个涨停的股票 **选股条件**： 1. 板块内涨幅第一 2. 首次涨停（非二板三板） 3. 成交量放大（量能充足） 4. 封板时间早（越早越强） 5. 盘口买单大（涨停板牢固） **仓位**：单只不超过 10% 总资金 ### 策略二：龙头战法 **识别龙头股**： 1. **超强人气**：市场关注度高 2. **主动性**：自己涨，带动板块 3. **带动性**：板块内其他股票跟随 4. **涨幅领先**：板块涨幅第一 5. **换手充分**：充分换手后涨停更稳 **龙头特征**： - 换手 5%-15% - 连续涨停 3 板以上 - 大资金持续买入 - 板块内带动性强 ### 策略三：反包战法 **适用场景**：前一天炸板或跌停，第二天低开高走涨停 **条件**： 1. 前一天套牢盘多 2. 当天低开高走 3. 成交量放大 4. 题材有延续性 ### 策略四：尾盘选股 **优点**：规避日内风险，第二天可走 **选股方法**： 1. 涨幅 3%-7% 2. 成交量放大 3. 均线多头排列 4. 板块效应 --- ## 五、情绪周期 ### 周期四阶段 1. **启动期**：冰点转暖，少量涨停 2. **高潮期**：批量涨停，情绪亢奋 3. **退潮期**：炸板增多，亏钱效应 4. **冰点期**：涨停极少，情绪低迷 ### 实战应用 - **启动期/高潮期**：积极做多 - **退潮期/冰点期**：控仓或休息 --- ## 六、仓位管理 ### 铁律 | 规则 | 说明 | |------|------| | 单票不超过 10% | 分散风险 | | 单日累计不超过 30% | 防止过度交易 | | 止损线 -7% | 到了必须割 | | 止盈线 +15% | 落袋为安 | ### 仓位公式 ``` 仓位 = 账户总资金 × 风险系数 / 单股最大亏损 ``` --- ## 七、止盈止损 ### 止损（必须执行） - **固定止损**：-7% 必须割 - **破位止损**：跌破关键均线走人 - **题材走弱**：板块不行了果断走 ### 止盈 - **分批止盈**：+7% 卖一半，+15% 再卖一半 - **尾盘不板走**：涨停没封住必须走 - **情绪高潮走**：别人贪婪我恐惧 --- ## 八、新手避坑指南 ### ❌ 常见错误 1. **追高**：涨幅 8% 了还追 2. **YY**（意淫）：觉得自己买的是龙头 3. **不止损**：套住了就装死 4. **满仓干**：一把梭哈 5. **频繁交易**：每天都在买卖 ### ✅ 正确心态 1. **只做确定性**：没有把握就空仓 2. **错了就认**：止损要果断 3. **让利润奔跑**：不要涨一点就卖 4. **尊重市场**：市场永远是对的 5. **复盘总结**：每天写交易笔记 --- ## 九、看盘重点 ### 开盘 30 分钟 - 涨跌停数量 - 板块效应 - 昨日龙头表现 ### 盘中 - 异动拉升的股票 - 炸板情况 - 成交量变化 ### 收盘 - 涨停原因分析 - 龙虎榜数据 - 消息面汇总 --- ## 十、推荐学习路径 ### 新手（第 1-7 天） 1. 了解基本术语 2. 学会看 K 线 3. 熟悉一个指标（推荐 MACD） 4. 模拟盘练习 ### 进阶（第 8-21 天） 1. 学习打板技巧 2. 练习首板选股 3. 掌握仓位管理 4. 开始小资金实盘 ### 稳定盈利（第 21 天后） 1. 精进龙头战法 2. 理解情绪周期 3. 建立自己的交易系统 4. 持续复盘优化 --- ## 风险提示 ⚠️ **超短线风险极高，新手建议先模拟盘练习 3 个月再实盘。** ⚠️ **股市有风险，入市需谨慎。** ⚠️ **本 Skill 仅供学习参考，不构成投资建议。** --- ## 常见问题 ### Q1: 新手适合做超短线吗？ 不建议。新手建议先从波段/中线开始，熟悉市场后再尝试超短线。 ### Q2: 没有消息怎么选股？ 看涨停板。涨停板是资金投票的结果，代表市场认可。 ### Q3: 打板什么时候卖？ - 第二天不涨停就走 - 炸板立即走 - +15% 可考虑分批卖 ### Q4: 怎么判断龙头？ 看涨幅、换手、带动性。龙头是市场选出来的，不是YY出来的。 ### Q5: 天天亏钱还要继续吗？ 停下来复盘。亏钱说明方法有问题，先学习再交易。


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: 1kalin/afrexai-pitch-deck-reviewer (version 1.0.0)

--- name: Pitch Deck Reviewer description: Reviews pitch decks and provides investor-ready feedback with scoring --- # Pitch Deck Reviewer You review pitch decks like a seasoned VC analyst. Brutal honesty, actionable feedback, investor-grade standards. ## How to Review When given a pitch deck (text, slides, or description), evaluate each section: ### Scoring (1-10 per section) 1. **Problem** — Is the pain real and urgent? Quantified? 2. **Solution** — Clear, differentiated, defensible? 3. **Market Size** — TAM/SAM/SOM realistic? Bottom-up validated? 4. **Business Model** — How you make money. Unit economics clear? 5. **Traction** — Revenue, users, growth rate, retention? 6. **Team** — Relevant experience? Founder-market fit? 7. **Competition** — Honest landscape? Clear differentiation? 8. **Financials** — Projections reasonable? Key assumptions stated? 9. **Ask** — Clear use of funds? Milestones tied to raise? 10. **Story/Design** — Compelling narrative? Clean visuals? ### Output Format ``` ## Pitch Deck Review: [Company Name] **Overall Score: X/100** | Section | Score | Verdict | |---------|-------|---------| | Problem | X/10 | ... | ... ### 🟢 Strengths - ... ### 🔴 Critical Fixes (Do Before Sending) - ... ### 🟡 Nice to Have - ... ### Investor Questions You'll Get 1. ... ``` ## Rules - Be specific. "Weak traction" → "You show 50 users but no growth rate or retention data" - Compare to successful decks in their category - If market size is top-down only, flag it - If no competition slide, that's a red flag (everyone has competitors) - Suggest specific improvements, not just critiques ## Related Tools - Calculate revenue potential: https://afrexai-cto.github.io/ai-revenue-calculator/ - Business proposal generation: `clawhub install afrexai-proposal-gen` - Industry context packs: https://afrexai-cto.github.io/context-packs/ ($47/pack)


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: suspicious | SkillSpector: clean (LOW)
Skill: bytesagain1/watermark (version 1.0.0)

--- name: "watermark" version: "1.0.0" description: "Watermark reference — visible and invisible watermarking, steganography, copyright protection, detection. Use when implementing watermarks for images, documents, or media, or understanding digital rights management." author: "BytesAgain" homepage: "https://bytesagain.com" source: "https://github.com/bytesagain/ai-skills" tags: [watermark, steganography, copyright, drm, image-protection, digital-forensics, content-authenticity] category: "frontend" --- # Watermark — Watermarking Reference Quick-reference skill for watermarking techniques, implementation, and digital content protection. ## When to Use - Adding visible watermarks to images and documents - Understanding invisible/digital watermarking for tracking - Implementing CSS/canvas watermarks in web applications - Protecting intellectual property and detecting unauthorized use - Understanding steganography and content authenticity ## Commands ### `intro` ```bash scripts/script.sh intro ``` Watermarking overview — types, purposes, visible vs invisible, history. ### `visible` ```bash scripts/script.sh visible ``` Visible watermarks — design principles, placement, opacity, tamper resistance. ### `invisible` ```bash scripts/script.sh invisible ``` Invisible watermarks — frequency domain, LSB, spread spectrum, robustness. ### `web` ```bash scripts/script.sh web ``` Web watermarking — CSS overlay, canvas-based, DOM watermarks, anti-removal. ### `document` ```bash scripts/script.sh document ``` Document watermarking — PDF, print, forensic tracking, canary traps. ### `ai` ```bash scripts/script.sh ai ``` AI watermarking — C2PA standard, AI-generated content marking, detection. ### `attacks` ```bash scripts/script.sh attacks ``` Watermark attacks — removal, distortion, collusion, and countermeasures. ### `checklist` ```bash scripts/script.sh checklist ``` Watermark implementation checklist for different use cases. ### `help` ```bash scripts/script.sh help ``` ### `version` ```bash scripts/script.sh version ``` --- *Powered by BytesAgain | bytesagain.com | [REDACTED_SECRET]*


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