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: outbound-calls

英語版ディレクトリ

Pre-indexed code knowledge graph for Claude Code, Codex, Gemini, Cursor, OpenCode, AntiGravity, Kiro, and Hermes Agent — fewer tokens, fewer tool calls, 100% local

54K
Stars
87/100
信頼
カテゴリ: development監査

access to david ondrej's personal agent skills

2.7K
Stars
76/100
信頼
カテゴリ: utility監査

🔥 PlainApp is an open-source app that lets you securely manage your phone from a web browser. Access files, media, contacts, SMS, calls, and more through a simple, easy-to-use interface on your desktop.

5.6K
Stars
84/100
信頼
カテゴリ: productivity-automation監査

[GenAI Application Development Framework] 🚀 Build GenAI application quick and easy 💬 Easy to interact with GenAI agent in code using structure data and chained-calls syntax 🧩 Use Event-Driven Flow *TriggerFlow* to manage complex GenAI working logic 🔀 Switch to any model without rewrite application code

1.6K
Stars
86/100
信頼
カテゴリ: agent-frameworks監査

A comprehensive collection of 30+ Claude Code skills for cold email and outbound sales, covering strategy, infrastructure, lead sourcing, and copywriting, with a guided kickoff flow and signal playbooks.

632
Stars
80/100
信頼
カテゴリ: marketing-growth監査

The missing DevTools for Claude Code — inspect session logs, tool calls, token usage, subagents, and context window in a visual UI. Free, open source.

3.6K
Stars
79/100
信頼
カテゴリ: agent-frameworks監査

A collection of agent skills that inject team-specific context into coding agents at session start, improving collaboration and adherence to conventions.

124
Stars
73/100
信頼
カテゴリ: coding-agents監査

CLI tool to inject stored credentials into curl requests for AI agents interacting with public APIs.

120
Stars
70/100
信頼
カテゴリ: utility監査
API79

Promise and RxJS APIs around Polkadot and Substrate based chains via RPC calls. It is dynamically generated based on what the Substrate runtime provides in terms of metadata.

1.1K
Stars
79/100
信頼
カテゴリ: web3-analytics監査

Core Python library for astronomy and astrophysics workflows that need Astropy APIs, including units/quantities, coordinates, FITS I/O, tables, time systems, WCS, and cosmology. Use when implementing or debugging astronomical data analysis code with Astropy.

34K
Stars
77/100
信頼
カテゴリ: data-analysis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