Claude Skills
The open format is called Agent Skills and works in Claude Code, Codex, Cursor and other agents — most people know it as Claude Skills.
Every Agent Skill we could find on GitHub, deduplicated by content. 79 437 files from 1 744 authors, of which 61 785 are unique — the rest is the same skill repackaged into someone else's repository. For each one: what it weighs in tokens, whether it ships runnable scripts, and which MCP servers it needs.
Statistical significance calculator for A/B test results with sample size requirements, segment breakdowns, and hypothesis generation. Use when feeding test results, checking statistical significance, calculating sample sizes, analyzing experiment outcomes, or generating next test ideas based on results. Platform: Google and Meta.
Multi-channel budget optimization using MER, marginal ROAS, and diminishing returns analysis. Use when pasting multi-channel spend and results data, requesting reallocation recommendations, analyzing budget shift priorities, or optimizing marketing efficiency across Google, Meta, TikTok, and other channels. Platform: Google and Meta.
Analyzes your top performing ads, identifies what's working in the hooks, CTAs, messaging angles, and formats, then generates new variants that follow the same winning patterns while introducing enough variation to test meaningfully. Platform: Google and Meta.
Track how AI assistants describe your brand over time and catch wrong, outdated, or damaging claims. Claude builds your monitoring prompt set, compares runs week over week, and drafts the correction plan when answers drift. Platform: AI visibility.
Analyzes your campaign history, conversion volume, CPA targets, and auction dynamics, then recommends the right bid strategy for each campaign — manual CPC, target CPA, target ROAS, maximize conversions, or maximize conversion value. Not a blanket recommendation, but campaign-by-campaign based on the data. Platform: Google.
Given your total budget, recommends the optimal split across Google Search, PMax, Meta prospecting, Meta retargeting, and any other active channels based on your last 60-90 days of marginal ROAS and CPA by channel. Tells you where each additional dollar produces the best return. Platform: Google and Meta.
Builds a consistent, filterable naming convention across your Google and Meta accounts based on your campaign types, objectives, targeting, and reporting needs. Makes filtering, reporting, and cross-platform analysis actually work instead of guessing what "Campaign_v3_Final_NEW" means. Platform: Google and Meta.
Runs your conversion data through different attribution models side by side — last click, first click, linear, time decay, position based, and data-driven. Shows you how credit shifts between campaigns depending on the model so you can make better budget decisions instead of over-investing in last-touch campaigns. Platform: Google and Meta.
Compares your Meta ad sets and identifies where audiences overlap significantly, causing your ads to compete against each other in the same auctions. Tells you exactly which ad sets are cannibalizing each other and how much it's costing you in inflated CPMs. Platform: Meta.
Find the exact pages AI assistants cite when answering questions in your category, and identify which ones you can get into. Claude clusters the cited sources, scores each by attainability, and outputs an outreach/content plan. Platform: AI visibility.
Models what happens to your CPA, ROAS, conversion volume, and impression share when you increase or decrease budget by any amount. Uses your actual account data and historical diminishing returns patterns, not generic industry assumptions. Platform: Google and Meta.
Pulls competitor ads from Meta Ad Library and Google Ads Transparency Center, categorizes their messaging angles, formats, CTAs, and creative types, then identifies gaps in their approach you can exploit and patterns worth testing in your own campaigns. Platform: Meta.
Takes your raw campaign performance data and writes the executive summary paragraph that goes at the top of the report. The plain English explanation of what happened, why it happened, and what's being done about it. The part every client actually reads. Platform: Google and Meta.
Systematic competitive analysis covering positioning, messaging hierarchy, objection handling, and CTA strategy from landing page URLs or screenshots. Use when pasting a competitor URL, uploading competitor screenshots, requesting positioning analysis, or needing to understand competitive messaging and differentiation strategies. Platform: Google and Meta.
Rewrite existing pages so AI assistants can extract, quote, and cite them. Claude restructures your content into answer-ready blocks — direct answers, comparison tables, stats with sources, schema — without wrecking the human reading experience. Platform: AI visibility.
Maps out how users move through your funnel from first ad click to conversion. Identifies where the biggest drop-offs happen, which campaigns contribute most at each stage, and how long the typical conversion path takes across different audience segments. Platform: Google and Meta.
Transform one long-form piece into multiple platform-specific content derivatives including LinkedIn posts, tweet threads, email snippets, ad hooks, and video scripts while maintaining voice consistency. Use when given a blog post, article, or pillar content to atomize across channels. Platform: Google and Meta.
When your CPA spikes, Claude breaks down exactly what caused it. It looks across your campaign data and isolates the contributing factors — audience fatigue, bid landscape shifts, creative decay, landing page conversion drops, budget distribution changes, or new competitor activity. Platform: Google and Meta.
Monitors your ads for early signs of fatigue before performance fully collapses. Tracks frequency buildup, CTR decay, CPM increases, and engagement drops across all active creatives and tells you which ones need rotation now vs next week. Platform: Meta.
Analyzes performance by day of week and hour of day across your campaigns. Identifies when your ads perform best and worst, recommends ad schedule adjustments with estimated savings, and tells you exactly what you'd give up by restricting hours. Platform: Google and Meta.
Analyzes how your campaigns perform across mobile, desktop, and tablet. Identifies where device performance diverges significantly and recommends bid adjustments, campaign splits, or creative/landing page changes to capture the gap. Platform: Google and Meta.
Full SEO workflow covering technical audits, content gaps, backlink opportunities, on-page fixes, and content briefs. Use when given a site and target keywords to get complete SEO analysis and actionable content plans. End-to-end SEO in one skill. Platform: Google.
Analyzes frequency data across your Meta campaigns, identifies where you're overserving ads to the same people, and recommends frequency caps by campaign objective. Tells you the point where additional impressions stop driving conversions and start burning money. Platform: Meta.
Breaks down campaign performance by geographic location at whatever level matters — country, state, city, DMA, zip code. Flags underperforming geos that are quietly eating budget and high-performing ones that deserve more spend. Recommends geo bid adjustments or campaign splits. Platform: Google and Meta.
Write complete nurture email sequences with subject lines, preview text, and body copy using proven copywriting formulas. Use when given ICP, offer, and objections to generate full email flows, creating welcome sequences, writing promotional emails, or maintaining voice consistency throughout email campaigns. Platform: Google and Meta.
Comprehensive Google Ads account health analysis detecting wasted spend, search term leaks, negative keyword gaps, bid strategy issues, and Quality Score problems. Use when analyzing campaign data, pasting Google Ads exports, reviewing account performance, or requesting a full diagnostic of advertising spend efficiency. Platform: Google.
Build detailed B2B buyer personas with pain points, objections, buying triggers, and messaging angles. Use when given a product and market to research ideal customer profiles, creating buyer personas, or needing to understand who you're selling to before launching campaigns. Platform: Google and Meta.
Identifies where your own keywords and campaigns are competing against each other in Google Ads auctions. Finds duplicate keywords across campaigns, overlapping match types that trigger the same queries, and ad groups stealing traffic from each other — all of which inflate your CPCs and mess up your data. Platform: Google.
CRO analysis for landing pages evaluating headline clarity, CTA placement, trust signals, mobile friction, and conversion killers. Use when uploading a landing page screenshot, pasting a URL for review, requesting conversion rate optimization feedback, or auditing page effectiveness prioritized by impact. Platform: Google and Meta.
Reviews your landing pages against the ads driving traffic to them. Checks for message match between ad copy and page content, CTA clarity, above-the-fold alignment, form friction, and flags any disconnects between what the ad promises and what the page delivers. Platform: Google and Meta.
Meta/Facebook/Instagram Ads campaign structure analysis detecting creative fatigue, audience overlap, scaling opportunities, and iOS tracking verification issues. Use when pasting Meta account data, analyzing Facebook ad performance, reviewing Instagram campaigns, or requesting audit of social advertising spend. Platform: Meta.
Create scalable programmatic SEO page templates with title patterns, internal linking logic, schema markup, and thin content avoidance strategies. Use when given a niche and data source to build page templates, establishing programmatic SEO structure, or scaling content production with templates. Platform: Google.
Compares your key metrics against industry benchmarks for your specific vertical, campaign type, and platform. Tells you where you're ahead, where you're behind, and where there's room to improve — adjusted for your account size and spend level, because a $10K/month account and a $500K/month account have different benchmark realities. Platform: Google and Meta.
LinkedIn Ads campaign analysis for B2B marketers detecting CTR issues, audience quality problems, lead gen form friction, and budget inefficiencies. Use when pasting LinkedIn campaign exports, analyzing B2B ad performance, or auditing LinkedIn advertising spend. Platform: LinkedIn.
Tracks daily spend against monthly budget targets across all campaigns and accounts. Tells you exactly where you'll land at current pace, flags campaigns that are over or underspending, and calculates the daily budget adjustments needed to hit your target by month end. Platform: Google and Meta.
Breaks down Quality Score components for your Google Ads keywords — expected CTR, ad relevance, and landing page experience — and tells you exactly which component is dragging each keyword down, with specific fixes ranked by potential CPC impact. Platform: Google.
Reddit Ads campaign analysis detecting community targeting issues, creative fatigue, bid inefficiencies, and subreddit performance problems. Use when pasting Reddit Ads data, analyzing subreddit targeting, or auditing Reddit advertising spend for B2B or B2C campaigns. Platform: Reddit.
Analyzes your conversion lag data to determine the optimal retargeting window for each audience segment. Tells you whether your 30-day retargeting window should actually be 7 days, 14 days, or 60 days based on when people actually convert after their first visit. Platform: Meta.
Projects your ROAS for the next 30, 60, and 90 days based on current performance trends, seasonality patterns from your historical data, and planned budget or campaign changes. Gives you a range with confidence intervals, not a single number pretending to be precise. Platform: Google and Meta.
Analyzes your search term reports across all campaigns and surfaces high-intent terms you're not bidding on yet. Groups them by theme, estimates their potential volume and CPA, and recommends match types and starting bids for each. Platform: Google.
Generate consistent UTM parameters, GA4 event naming, and conversion tracking specs following taxonomy best practices. Use when describing campaign structure, requesting UTM links, needing GA4 event names, or wanting to standardize tracking nomenclature across marketing channels. Platform: Google and Meta.
Scans your Google and Meta accounts for money being spent on search terms, placements, audiences, and ads that produce zero or near-zero conversions. Delivers clean exclusion lists you can upload directly. Platform: Google and Meta.
Generates a plain English summary of everything that happened across all your accounts this week. What improved, what declined, what needs immediate attention, and what to prioritize next week. The Monday morning briefing that saves you an hour of pulling reports and context-switching between platforms. Platform: Google and Meta.
Help users build functional product prototypes from natural language or visual mocks using AI coding tools. This skill enables product leaders to bypass engineering bottlenecks and validate ideas through hands-on building.
Help users identify unique distribution advantages and master the lifecycle of acquisition channels to build a sustainable engine for growth and retention.
Help users convert massive volumes of qualitative and quantitative feedback into high-confidence product decisions through rigorous synthesis and internal immersion.
Help users systematically document their impact, identify skill gaps, and collaborate with their managers to secure a promotion by proving they are already operating at the next level.
Help users build robust infrastructure for measuring, monitoring, and iterating on AI product performance using human, code-based, and LLM-as-a-judge methodologies.
Help users identify the most viable path into product management, assess their role fit, and execute a transition strategy through internal mobility, APM programs, or startup roles.
Help users interact with probabilistic models by designing interfaces that manage fluidity, intent, and agency while maintaining trust and control.
Help users decide where to apply AI effectively, manage the transition from deterministic to probabilistic software, and build long-term defensibility through verticalization and proprietary data.
Help users determine when to hire growth talent, which profiles to prioritize, and how to structure the team for maximum leverage across the user journey.
Help users evaluate new opportunities, manage professional identity shifts, and transition into roles that maximize both impact and personal fulfillment.
Help users build a sustainable habit of regular customer interaction to ensure product development is driven by real-world needs rather than internal assumptions.
Help users transition from individual execution to a coaching-centric leadership style that scales through the growth of their team. It focuses on identifying skill deficits, providing reflection space, and leveraging frameworks to accelerate professional maturity.
Help users identify their most high-value customers by defining a hyper-specific ICP that maximizes product-market fit and acquisition efficiency.
Help users identify sources of durable competitive power, evaluate market threats, and design products that are uniquely differentiated rather than just better versions of existing tools.
Help users conduct high-impact customer interviews that move beyond surface-level feature requests to identify root emotional frustrations and specific causal triggers.
Help users master the transition from manual coding to managing AI-driven development workflows by focusing on high-level direction, parallel tasking, and rigorous automated review.
Help users move beyond ambitious goal-setting to create a rigorous diagnosis of challenges and a clear, actionable plan for winning in their specific market.
Claude Skills — questions
Answers built from the skills we actually parsed.