Claude Code Skills · page 37

Roll back to a previous checkpoint via git — use when a change went wrong and you need to revert

URL validation and content sanitization for untrusted sources — use when handling external input safely

Package and finalize completed work for delivery — use when a feature is done and ready to ship

Use when a PR or feature needs both specification and code-quality review

Show where you are in the workflow and what to do next — use for progress checks and orientation

Manage tasks with Claude Code native tools — use to track TODOs, delegate work, and monitor progress

Build features with tests-before-code rigor — use for new features needing test coverage

Brainstorm creatively with pattern spotting and paradox hunting — use for ideation and exploration

Use when about to declare work complete, fixed, passing, or done

Process screenshot-based UI/UX feedback to fix visual issues — use when users share screenshots of bugs

Break a plan or spec into vertical slices that each declare what blocks them — use when work is agreed but not yet cut into fileable pieces

Create zero-context implementation plans with bite-sized tasks — use for multi-step feature planning

Configure Claude Octopus — redirects to /octo:setup interactive wizard

Drive an engine app headlessly in a pty, record a video of the whole verification, and open a summary page (video + timeline + checks) with pixel open.

Operate the Telegram Search CLI through an authorized local profile. Use when an agent needs to discover Telegram chats, read bounded remote messages, explicitly synchronize history with user-approved Telegram Takeout, query/search/contextualize persisted messages, compute statistics, export deterministic JSONL, or run a real CLI end-to-end canary. Never send or modify Telegram messages.

微信公众号文章排版引擎，将 Markdown 转换为可直接粘贴到公众号编辑器的 HTML。主题风格从 references/theme-index.md 注册的自定义主题库中选取，自动章节编号、关键词下划线标记、引言卡片、目录导航、代码块、图片/GIF、作者签名。支持 Markdown / Word(.docx) / PDF / 纯文本输入（非 Markdown 先自动归一化），也支持"一键自动排版"（自动推断结构+选主题），还支持根据用户描述/参考图生成自定义主题组件库并保存本地复用。触发场景：(1) 用户提到"公众号排版""公众号文章""微信排版""gzh"，(2) 用户想把文章（md/docx/pdf/纯文本）转成公众号 HTML，(3) 用户说"自动排版""一键排版"公众号内容，(4) 用户想为公众号排版"生成新主题/自定义风格/按这张图做一套组件库"。不用于生成普通网页/落地页/PPT（用前端或 PPT 类 skill）。

Turn an investment agent into a supply-chain bottleneck hunter. Use this skill for source-backed investment research, live market/theme scans, AI/semi/technology value-chain mapping, A-share/HK/US stock screening, thesis stress tests, and Serenity-inspired research conversations. Trigger on requests like "用 Serenity 的方式看", "深度调研", "产业链/供应链/卡点/瓶颈", "A股 AI 半导体哪个最值得研究", "find unknown bottlenecks", "rank candidates", or "challenge this thesis". Outputs plain-language reasoning, ranked research priorities, evidence chains, risks, and next verification steps. Research support only; no trade execution.

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Use this skill to verify CLAIM-LEVEL grounding of a documentation page (or set of pages) against the source code. Activate when you have specific pages to check for factual accuracy -- not when sweeping a whole corpus (use docs-corpus-audit for that) and not when triaging a PR diff (use docs-sync for that). Trigger nouns: "is this doc accurate", "verify the page against the code", "fact-check this section", "any claims that drifted from source", "fact-checking", "grounding audit", "drift hunt", "claim verification". Returns per-claim verdicts (GROUNDED | PARTIAL | CONTRADICTED | UNSUPPORTED) with file:line evidence citations. Catches paragraph-level inaccuracies that page-level audit averages over -- e.g. a paragraph with 5 claims where 4 are grounded and 1 is fabricated. Does NOT modify files (returns advisory only); does NOT re-architect the docs; does NOT triage PRs.

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Enforces completion discipline for substantial autonomous work by writing acceptance gates before execution, decomposing work with the Depth Tree, running approved checks, and re-verifying evidence before reporting. Use when an agent faces a long or multi-part task, work that has returned half-done, an exhaustive audit or build, parallel leaves or pipelines, or explicit triggers such as /unlazy, $unlazy, "tree N", "gates", and "do not stop until it is done".

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Manage Google Ads — performance, keywords, bids, budgets, negatives, campaigns, ads, search terms, QS, location targeting, bulk operations, experiments, asset management, portfolio bidding, offline conversions. Use for any mention of Google Ads, CPA, ROAS, ad spend, or campaign settings.

Plan, validate, and safely publish Google Ads assets, including sitelinks, callouts, structured snippets, image assets, and Performance Max asset briefs. Use when asked for Google Ads assets, ad extensions, sitelinks, callouts, snippets, image assets, Performance Max assets, PMax creative, or an asset audit.

Google Ads account audit and business context setup. Run this first — it gathers business information, analyzes account health, and saves context that all other ads skills reuse. Trigger on "audit my ads", "ads audit", "set up my ads", "onboard", "account overview", "how's my account", "ads health check", "what should I fix in my ads", or when the user is new to NotFair and hasn't run an audit before. Also trigger proactively when other ads skills detect that business-context.json is missing.

Generate and A/B test Google Ads copy. Use when asked to write ad copy, headlines, descriptions, create ad variants, test ad messaging, improve CTR, or generate RSA (Responsive Search Ad) components. Trigger on "ad copy", "write ads", "headlines", "descriptions", "RSA", "responsive search ad", "ad text", "ad creative", "improve CTR", "ad A/B test", "ad variants", "write me an ad", "ad variation experiment", or when the user wants to improve click-through rate on existing ads.

Score and diagnose Google Ads landing pages. Use when asked to audit a landing page, check landing page quality, diagnose high-CTR but low-conversion-rate ad groups, improve Quality Score's Landing Page Experience component, or compare an ad group's messaging against its landing page. Trigger on "landing page audit", "landing page score", "landing page quality", "why is my conversion rate low", "LPX", "landing page experience", "ad to page match", or when `/google-ads-audit` surfaces a high-CTR / low-CVR ad group.

Analyze connected Google Analytics 4 traffic, acquisition, engagement, landing pages, ecommerce, events, and conversions, and safely manage supported GA4 key events or custom dimensions through NotFair MCP. Use for GA4, Google Analytics, traffic or conversion drops, channel attribution, realtime activity, report requests, measurement configuration, or Analytics MCP setup.

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Manage Meta Ads (Facebook + Instagram) — performance, ROAS, CPM, frequency, audience overlap, learning phase, creative fatigue, budgets, ad sets, campaigns, ads. Use for any mention of Meta Ads, Facebook Ads, Instagram Ads, ROAS, CPM, ad spend, or campaign settings on Meta.

Meta Ads (Facebook + Instagram) account audit and business context setup. Run this first — it gathers business information, analyzes account health, and saves context that all other Meta ads skills reuse. Trigger on "audit my Meta ads", "audit my Facebook ads", "Meta ads audit", "set up my Meta ads", "onboard Meta", "Meta account overview", "how's my Meta account", "Meta health check", "what should I fix in my Facebook ads", or when the user is new to NotFair Meta and hasn't run an audit before. Also trigger proactively when other Meta ads skills detect that meta business-context.json is missing.

Create evidence-based Meta ad creative briefs, copy angles, and testable asset concepts for Facebook and Instagram. Use when asked for Meta ad creative, Facebook ads copy, Instagram ad assets, UGC concepts, creative briefs, new ad concepts, or creative refreshes.

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Coordinate safe, evidence-based paid-media work across Google Ads, Meta Ads, X Ads, LinkedIn Ads, TikTok, Amazon, and ChatGPT Ads. Use for broad ads questions, multi-channel strategy, budgets, CPA or ROAS, campaign requests, spend, ad performance, or when routing to the right NotFair paid-ads skill.

Plan and review Amazon Ads with margin-aware ACoS, product, and search-term guardrails. Use for Amazon advertising, Sponsored Products, Sponsored Brands, Sponsored Display, ASIN targeting, Amazon ACoS, or Amazon Ads performance exports.

Plan and review ChatGPT Ads experiments without assuming ad inventory, account access, or platform capabilities. Use for ChatGPT advertising, OpenAI ads, conversational ad concepts, ChatGPT campaign plans, or performance reviews from a verified export.

Create grounded paid-media creative concepts, copy angles, refresh hypotheses, and measurable test briefs across advertising platforms. Use for ad copy, creative briefs, UGC concepts, headlines, creative fatigue, asset ideas, or a creative refresh.

Explain NotFair's paid-ads skills, installation, platform boundaries, account connections, and current product capabilities. Use for questions about how NotFair works, what it supports, how to install or connect it, plans or limits, or paid-media troubleshooting that is not an account-performance request.

Discover, connect, and verify NotFair paid-ad integrations and their actual capabilities. Use when asked to connect an ad account, configure an ads MCP, check available tools, troubleshoot access, or determine whether NotFair can read or change a platform.

Plan and prepare a new paid-media campaign or cross-channel test before it can spend. Use when asked to create, launch, start, set up, or allocate budget to an advertising campaign on any supported platform.

Audit, diagnose, plan, and safely operate connected LinkedIn Ads accounts through the NotFair MCP, with an export-based fallback. Use for LinkedIn advertising, sponsored content, lead-generation forms, job-title or company targeting, campaign groups, creatives, conversions, lead quality, budgets, bids, or approved LinkedIn campaign changes.

Diagnose wasted paid-ad spend, pacing, and allocation, then propose safe evidence-backed optimizations. Use for waste, negatives, budgets, bid changes, poor CPA or ROAS, underpacing, overspend, or scaling decisions.

Produce a read-only, evidence-based paid-media performance review across connected platforms or supplied exports. Use for weekly or monthly reports, scorecards, performance, CPA, ROAS, CTR, spend trends, pacing, or conversion-tracking health.

Connect NotFair paid-ad accounts and establish reusable campaign context. Use when setting up paid media in a new workspace, connecting Google, Meta, X, or LinkedIn Ads, refreshing brand context, or preparing an agent to work on ads safely.

Plan and review TikTok Ads creative experiments with measurement, rights, and conversion guardrails. Use for TikTok advertising, Spark Ads, short-form video ads, creator briefs, TikTok campaign setup, or TikTok performance exports.

Audit, diagnose, and safely operate connected X Ads (Twitter Ads) accounts through the NotFair MCP. Use for X Ads performance, campaign or line-item analysis, spend, conversions, targeting, promoted posts, audiences, budgets, bids, creative, campaign setup, or approved X Ads changes.

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Query and operate connected Google Search Console properties through NotFair MCP. Use for live GSC query or page performance, clicks, impressions, CTR, position, traffic changes, indexing status, URL inspection, sitemap reads or approved sitemap submission/removal, and Search Console MCP setup. Route full-site SEO audits to seo-analysis.

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Fetches articles from 92 Karpathy-curated RSS feeds, scores them with an LLM, selects the top 3, and delivers a formatted digest to Telegram every morning.

Extract and analyze writing improvements from GitHub PR review comments. Use when asked to show review feedback, style changes, or editorial improvements from a GitHub pull request URL. Handles both explicit suggestions and plain text feedback. Produces structured output comparing original phrasing with reviewer suggestions to help refine future writing.

Investigate fast-agent session and history files to diagnose issues. Use when a session ended unexpectedly, when debugging tool loops, when correlating sub-agent traces with main sessions, or when analyzing conversation flow and timing. Covers session.json metadata, history JSON format, message structure, tool call/result correlation, and common failure patterns.

Agent Context Isolation

Agent Orchestration Rules

Agentic Workflow Pattern

Guide for integrating Agentica SDK with Claude Code CLI proxy

Reference guide for Agentica multi-agent infrastructure APIs

Write reliable prompts for Agentica/REPL agents that avoid LLM instruction ambiguity

Build Python agents with Agentica SDK - @agentic decorator, spawn(), persistence, MCP integration

Agentica server + Claude proxy setup - architecture, startup sequence, debugging

Spawn Agentica multi-agent patterns