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Found 5,122 Skills
Amazon keyword research and market opportunity analysis for sellers. Retrieve autocomplete suggestions (long-tail keywords), analyze competitor landscape, and assess market opportunity for any keyword on 12 Amazon marketplaces (US/UK/DE/FR/IT/ES/JP/CA/AU/IN/MX/BR). No API key required. Make sure to use this skill whenever the user mentions Amazon product research, finding products to sell on Amazon, Amazon keyword ideas, niche analysis, competition analysis for Amazon, market opportunity on Amazon, comparing Amazon keywords, evaluating whether a product is worth selling, Amazon autocomplete data, seasonal demand for Amazon products, or anything related to researching what to sell on Amazon — even if they don't explicitly say 'keyword research'. Also trigger when the user asks vague questions like 'is this a good product to sell?', 'what's the competition like for X on Amazon?', 'should I sell X or Y?', or 'what are people searching for on Amazon?'.
Ultra-lightweight channel for feature workflows: No need to write design docs, checklists, or conduct phased reviews. Let AI write code directly as it normally would, but before it starts, tell it where the CodeStable knowledge base in the project is and how to search it. This way, the code it writes will have fewer pitfalls and be more consistent with project conventions. Trigger scenarios: Users say "fast mode", "fastforward", "skip all those steps", "just start coding", "help me make xxx" and the requirement is too small to go through the design process.
Discussion entry when ideas are still vague — first conduct triage through 1-2 rounds of dialogue to determine which downstream process this discussion should eventually go to: if the idea is clear enough, proceed directly to feature-design; if the direction of a small requirement is set, continue the discussion within the feature and document it in `{slug}-brainstorm.md`; if a large requirement cannot fit into a single feature, hand it over to roadmap for decomposition. The role of AI is a thinking partner, not a recorder — dig out the real problem the user wants to solve, proactively evaluate when the user brings a solution, and propose alternative directions when necessary. Trigger scenarios: when the user says "I have an idea that's not clear yet", "Let's brainstorm first", "I want to do something but it's still vague", "Let's talk about this area", "The function direction is still undecided", or when the user comes with a specific solution but wants to hear other ideas first. Bugs (go to issue) and refactoring (go to refactor) are not handled here.
Ultra-lightweight channel for refactor processes - used when changes are clearly too small to go through the full scan → design → apply three-stage workflow. AI directly identifies 1-3 low-risk optimization points, confirms with the user once, modifies in-place using classic methods, and validates itself by running tests. No scan checklist, no design documentation, no multi-step human verification required. Trigger scenarios: User says "quick refactor", "small refactor", "simply optimize XX function", "modify directly", "skip the extra steps", and the scope of changes is clearly localized to a single function / single component with test coverage for self-validation.
Document the pitfalls encountered or good practices discovered during this work into searchable learning documents, which can be accessed by both AI and humans when similar tasks arise in the future. Two tracks: The pitfall track records experiences where "things should have worked but didn't" — including bugs, configuration traps, environment issues, and integration failures; The knowledge track records findings that "should be the default approach going forward" — including best practices, workflow improvements, and reusable patterns. Trigger scenarios: Proactively prompt at the end of feature-acceptance or issue-fix workflows, or when the user mentions phrases like "document knowledge", "learning", "document learnings", or "record this experience". Spec documents record what was done, while learning documents record what pitfalls were encountered / what was learned — they complement each other and are not interchangeable.
Creates or updates software localizations/translations. Use when the user wants to translate a project to a new language, add a new locale, create translations, localize strings, or work with i18n/l10n files. Handles any project type (React, Vue, iOS, Android, Rails, Django, .NET, etc.) by auto-detecting the localization framework.
Vulcan C# Agent — sviluppo C# moderno, cloud-native (AWS/Azure) e provider-agnostic con Serilog, LiteDB, MongoDB e pattern architetturali puliti
AI rules for writing tests with Stably Playwright SDK. Use this skill when writing or modifying Playwright tests with Stably AI features. Covers when to use Playwright vs Stably methods, plus minimal patterns for aiAssert, extract, getLocatorsByAI, agent.act, Inbox, and Google auth.
Peter Thiel's Monopoly Creation framework applied to a business idea. Spawns a team of specialist agents — Monopoly Anatomist, Secret Hunter, Market Framer, Last Mover Analyst, Girardian — who each apply a distinct lens from Thiel's framework to evaluate whether a venture has genuine monopoly potential. The lead synthesizes into a verdict: does this company have a secret, a 10x advantage, a tiny domination-ready market, and a path to becoming the last mover in its category? Use when the user says "thiel this", "monopoly test", "zero to one analysis", "does this have monopoly potential", or proposes a venture and wants Thiel-style evaluation. Works standalone or after /office-hours and /munger.
Enthu.AI platform help — contact center conversation intelligence with auto QA scorecards, agent coaching, compliance monitoring, and speech analytics. Use when setting up Enthu.AI QA scorecards for call center agents, calls not being scored or transcribed correctly, agents not seeing coaching insights from their calls, Enthu.AI integration with Aircall or RingCentral not syncing, comparing Enthu.AI vs Gong or CallMiner for contact center QA, or configuring sentiment analysis and keyword tracking. Do NOT use for building a general coaching program (use /sales-coaching) or reviewing a specific call transcript (use /sales-call-review).
Fireflies.ai platform help — AI meeting note-taker with GraphQL API, webhooks (V1 + V2), AskFred AI, real-time events, and Fred bot that joins Zoom/Meet/Teams to transcribe. Use when Fireflies transcripts not syncing to CRM, webhooks not firing or signatures failing HMAC verification, hitting 50 req/day or 60 req/min rate limits on the GraphQL API, building a transcript pipeline from Fireflies to Snowflake/BigQuery/warehouse, migrating from Webhooks V1 to V2, the Fireflies bot not joining calls or users wanting to disable auto-join, deciding between Free, Pro ($10), Business ($19), or Enterprise ($39) tier, or wiring AskFred or Real-time API into an internal app. Do NOT use for comparing Fireflies vs Fathom/Avoma/Gong or selecting a note-taker (use /sales-note-taker) or reviewing a single sales call for coaching (use /sales-call-review).
Cialdini's seven principles of compliance (reciprocation, commitment-consistency, social proof, liking, authority, scarcity) plus Unity (added 2016) and Pre-Suasion. Use when crafting ethical persuasion (marketing, sales, negotiation), defending against manipulation, or designing systems that need cooperation. Includes replication-crisis caveats and known factual corrections (Bickman parking-meter numbers, Hofling modern replication, Drive Carefully condition disambiguation, Genovese myth).