Skill ディレクトリ

AI Agent のための再利用可能な Skill を見つける。

タスクで実際の GitHub Skill を検索し、利用前に Stars、Trust、監査、カテゴリ、インストール経路を確認できます。

すべての推奨は、リポジトリ、監査、インストール経路に明確につながっています。

検索結果: brand-improvement

英語版ディレクトリ

Apply Anthropic official brand colors, typography, and visual standards to appropriate Anthropic-related artifacts.

171K
Stars
82/100
信頼
カテゴリ: design-creative監査

A portable AI agent skill that enhances AI-generated user interfaces with better layout, typography, motion, and spacing to avoid generic outputs.

65K
Stars
87/100
信頼
カテゴリ: development監査

Generate draw.io diagrams from natural language — 6 presets, vision self-check + up to 5-round refinement, codebase-to-diagram, 10,000+ official shapes & 321 AI/LLM brand logos. Exports PNG/SVG/PDF/JPG.

7.4K
Stars
86/100
信頼
カテゴリ: agent-skills監査

GEO-first SEO skill for Claude Code. Comprehensive AI search optimization for any website — citability scoring, AI crawler analysis, brand authority, schema markup, platform-specific optimization, and PDF reports. If you want learn how to sell this to real businesses, check out the skool community

8.1K
Stars
85/100
信頼
カテゴリ: development監査

A curated list of autonomous improvement loops, research agents, and autoresearch-style systems inspired by Karpathy's autoresearch.

2.5K
Stars
77/100
信頼
カテゴリ: agent-frameworks監査

6,100+ brand SVG icons for developers. Tree-shakeable, typed, open source. npm i thesvg

2.4K
Stars
84/100
信頼
カテゴリ: agent-skills監査

A geospatial analytics skill for AI agents like Claude, Codex, and Copilot, enabling map-based queries on PostGIS, BigQuery, Snowflake.

571
Stars
84/100
信頼
カテゴリ: data監査

Admin / analytics dashboard in a single HTML file. Fixed left sidebar, top bar with user/search, main grid of KPI cards and one or two charts. Use when the brief asks for a "dashboard", "admin", "analytics", or "control panel" screen.

90K
Stars
72/100
信頼
カテゴリ: research監査

A Claude Code plugin providing 16 visual content workflows with AI image generation, aesthetic routing, and brand customization.

109
Stars
77/100
信頼
カテゴリ: design-creative監査

Autonomously improve a real artifact (code, training recipe, agent harness, data pipeline, prompt) against an objective and an evaluator, using Hypothesis Tree Refinement (HTR) from the Arbor paper. Use this whenever someone wants to iteratively optimize something over many experiments without overfitting — e.g. "get my model's eval score up", "improve this agent/harness", "tune this pipeline", "beat the baseline on this benchmark", "run a search over approaches and keep the best", "do an MLE-bench / Kaggle-style optimization", or any long-horizon "make this artifact better and don't just memorize the dev set" task. Trigger it even when the user doesn't say "Arbor" or "hypothesis tree" but describes repeated experiment-and-evaluate loops, branching exploration of competing ideas, or worries about a dev/test gap. Runs Claude itself as the coordinator with subagent executors in isolated git worktrees; for the standalone `arbor` CLI tool see references/arbor-upstream.md.

34K
Stars
77/100
信頼
カテゴリ: research監査

Create original editorial technology covers with a controlled layout, custom diagram generation, and editable SVG or PNG output.

1.3K
Stars
66/100
信頼
カテゴリ: Video Creation監査

When the user needs to generate, iterate, or scale ad creative for paid advertising. Use when they say 'write ad copy,' 'generate headlines,' 'create ad variations,' 'bulk creative,' 'iterate on ads,' 'ad copy validation,' 'RSA headlines,' 'Meta ad copy,' 'LinkedIn ad,' or 'creative testing.' This is pure creative production — distinct from paid-ads (campaign strategy). Use ad-creative when you need the copy, not the campaign plan.

25K
Stars
77/100
信頼
カテゴリ: design-creative監査