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Found 1,944 Skills
Resolve PR review feedback by evaluating validity and fixing issues in parallel. Use when addressing PR review comments, resolving review threads, or fixing code review feedback.
Solidroad platform help — AI-powered QA and training for CX teams. Use when reps ramping too slowly and need AI practice simulations, QA only covers 2% of conversations and you want 100% automated scoring, training and QA are disconnected and insights don't turn into coaching, setting up Solidroad scorecards or custom quality rubrics, connecting Solidroad to Salesforce Service Cloud or Zendesk or Intercom, or evaluating Solidroad vs Observe.AI vs Balto vs Cresta for contact center QA. Do NOT use for general coaching strategy without a specific platform (use /sales-coaching).
Arrfounder platform help — founder revenue directory by @Folyd (2024) that auto-extracts MRR/ARR + products from Twitter/X bios via AI, lists 1000+ founders on sortable leaderboards (ARR / followers / products / recently added), free Airtable submission with 24-48h manual approval, auto-syncs within hours of bio changes. Social-proof verification only (no Stripe / Lemon Squeezy / Polar API integration) — built for peer discovery and community browsing, not acquisition-grade proof. Use when getting listed on Arrfounder, writing a Twitter/X bio that passes the MRR/ARR extractor, fixing a profile that didn't get approved or stopped updating after a bio edit, deciding Arrfounder vs TrustMRR or StartuPage for verified-revenue display, benchmarking against peers in the $1K-$10M+ ARR tiers, or using Arrfounder as a comp-check tool before pricing a sale or fundraise. Do NOT use for selling/buying a project or cross-marketplace valuation (use /sales-side-project-valuation).
Writing style guide for the Singapore Government Design System (SGDS). Use when writing or reviewing UI copy, documentation, labels, error messages, tooltips, or any content that accompanies SGDS components. Covers tone, grammar, spelling, casing, punctuation, and plain language principles.
Curate Claude Code's auto-memory into durable project knowledge. Analyze MEMORY.md for patterns, promote proven learnings to CLAUDE.md and .claude/rules/, extract recurring solutions into reusable skills. Use when: (1) reviewing what Claude has learned about your project, (2) graduating a pattern from notes to enforced rules, (3) turning a debugging solution into a skill, (4) checking memory health and capacity.
Resolves experiment references from natural language to concrete experiment IDs. Handles name lookups, fuzzy descriptions ('the signup experiment', 'my latest experiment'), status filtering, and disambiguation when multiple experiments match. TRIGGER when: user refers to an experiment by name, description, or relative reference ('latest', 'most recent', 'the one I created yesterday') and you don't already have the experiment ID. DO NOT TRIGGER when: user provides an experiment ID directly, or you already resolved the experiment earlier in the conversation.
Evaluate test coverage and fill real gaps with high-value tests.
Novel chapter content creation, suitable for user requests such as "Write a chapter of a novel for me", "Continue the following content", "Generate XX plot", "Batch write web novel chapters", "Expand/rewrite this content", "Write me an XX plot", "Continue the novel", "Expand this content", "Rewrite this chapter", "Batch generate novel chapters", "Write an opening chapter", "Write a climax plot", "Novel content generation", "Help me write novel content", etc. It supports multiple modes such as single-chapter/multi-chapter batch generation, continuation, rewriting, and expansion. It automatically adapts to the rhythm of web novels, maintains consistency of characters and plot, and **automatically uses sub-Agents for parallel processing during batch generation, with each Agent responsible for a maximum of 3 chapters**
Online Novel Topic Planning, suitable for user needs such as "I don't know what to write for a novel", "Help me come up with a novel genre", "Find online novel ideas", "Analyze which genres are popular", "Novel topic evaluation", "Which online novel genres are profitable now", "Give me some novel ideas", "Come up with a golden finger for a novel", "Help me find a popular genre", "Which novel genre is easy to become popular", "Online novel market trend analysis", "Help me plan novel topics", etc. It generates multiple sets of topic proposals and market analysis, including golden finger design, core selling points, cool point patterns, and feasibility evaluation.
Turn research findings into a polished paper-style draft with sections, equations, and citations. Use when the user asks to write a paper, draft a report, write up findings, or produce a technical document from collected research.
Proofread and correct text for grammar, spelling, punctuation, style, clarity, and consistency, with support for multiple style guides and readability analysis.
Buffett-style single-stock moat diagnostic — "Would Buffett buy this stock?" Five dimensions: business & moat / financial health / management & capital allocation / valuation & margin of safety / long-term visibility. Data from Longbridge CLI first, MCP fallback, WebSearch only for gaps. Runs cross-statement reconciliation (勾稽校验) BEFORE scoring; data-source appendix closes with a one-line reconciliation summary. Output: star-rated radar card, dimension detail, Buffett-voice narrative, mandatory holding-period education block. Triggers: "巴菲特", "护城河", "巴菲特会买吗", "价值投资", "好生意", "宽护城河", "定价权", "诊股", "巴菲特诊股", "巴菲特视角", "长期持有", "護城河", "巴菲特會買嗎", "價值投資", "寬護城河", "定價權", "診股", "巴菲特診股", "巴菲特視角", "長期持有", "Buffett", "Warren Buffett", "moat", "economic moat", "wide moat", "pricing power", "value investing", "owner earnings", "would Buffett buy", "Berkshire-style", "quality compounder".