Total 51,469 skills
Showing 12 of 51469 skills
Develop, test, build, and deploy Godot 4.x games. Use when working with Godot Engine, GDScript, GdUnit4 testing, PlayGodot automation, or exporting games to web/desktop. Covers CI/CD pipelines and deployment to Vercel/GitHub Pages/itch.io.
Generate a ready-to-send FAQ document that anticipates and answers the most common creator questions about a campaign brief, reducing back-and-forth messages and delays. This skill should be used when creating a campaign brief FAQ, writing answers to common creator questions about a brief, building an FAQ attachment for an influencer brief, reducing back-and-forth with creators after sending a brief, anticipating creator questions before launch, preempting influencer confusion about deliverables or timelines, generating a brief companion FAQ, writing a creator-facing Q&A for a campaign, drafting briefing clarifications for influencers, or creating a FAQ sheet to send alongside a content brief. For writing the campaign brief itself, see campaign-brief-generator. For writing individual content briefs, see content-brief-builder. For chasing creators who have not responded to a brief, see universal-creator-follow-up-chaser.
Analyze an influencer's audience demographics to determine whether their followers match your target customer, with a clear pass/fail verdict. This skill should be used when evaluating audience fit, checking influencer demographics, analyzing audience data, reviewing an audience breakdown, assessing demographic alignment, vetting an influencer's audience, determining if a creator's followers match your target demo, reviewing a platform export or stats screenshot, pasting influencer stats, grading audience quality, deciding whether an influencer's audience is a good fit, checking if this creator is worth it, running an audience report, comparing creator audiences, or evaluating audience overlap with target demo. For overall creator vetting beyond demographics, see creator-vetting-scorecard. For finding new creators, see creator-discovery.
Compound Engineering workflow for AI-assisted development. Use when planning features, executing work, reviewing code, or codifying learnings. Follows the Plan → Work → Review → Compound loop where each unit of engineering makes subsequent work easier. Triggers on: plan this feature, implement this, review this code, compound learnings, create implementation plan, systematic development.
Structures the human review experience for factory-mode builds. Audit trail summaries, PR digests, retrospective synthesis, quality trend tracking, and autonomy tuning interface. Activate during Phase 3 human review.
Generate and edit images using AI. Use when the user asks to "generate an image," "create an image," "make a picture," "edit this image," "modify this image," or when building UI that needs visual assets like hero images, icons, or illustrations.
Breaks epics into developer stories.
Activate autonomous Ralph Wiggum loop mode for iterative task completion. Use when you have a well-defined task with clear completion criteria that benefits from persistent, autonomous execution.
Use AliCloud Milvus (serverless) with PyMilvus to create collections, insert vectors, and run filtered similarity search. Optimized for Claude Code/Codex vector retrieval flows.
Summarize database schema design from requirement inputs and produce implementation-ready outputs for Go + Ent in this repository. Use when the input may be a prompt, Markdown requirement document, repository folder, or runnable demo behavior and you need entity extraction, field/constraint design, weak-relation ID strategy, index planning, Ent schema guidance, and concrete bind/render/service integration impacts.
Technology-agnostic blueprint generator for creating comprehensive copilot-instructions.md files that guide GitHub Copilot to produce code consistent with project standards, architecture patterns, and exact technology versions by analyzing existing codebase patterns and avoiding assumptions.
Suggest relevant GitHub Copilot skills from the awesome-copilot repository based on current repository context and chat history, avoiding duplicates with existing skills in this repository, and identifying outdated skills that need updates.