Annuaire de skills

Découvrez des skills réutilisables pour les AI agents.

Recherchez de vrais skills GitHub par tâche et vérifiez Stars, confiance, audit, catégorie et chemin d’installation avant de les utiliser.

Chaque recommandation reste clairement reliée à son dépôt, son audit et son chemin d’installation.

Résultats de recherche: rate-limiter

Annuaire en anglais

Integration platform for AI agents with 250+ app connectors

29K
Stars
80/100
Confiance
Catégorie: integrationsAudit

Like htop, but for AI coding agents. Monitor Claude Code & Codex CLI sessions, tokens, context window, rate limits, and ports in real-time.

2.8K
Stars
79/100
Confiance
Catégorie: agent-frameworksAudit

Full-stack .Net 10 Clean Architecture (Microservices, Modular Monolith, Monolith), Blazor, Angular 21, React 19, Vue 3.5, BFF with YARP, NextJs 16, Domain-Driven Design, CQRS, SOLID, Asp.Net Core Identity Custom Storage, OpenID Connect, EF Core, OpenTelemetry, SignalR, Background Services, Health Checks, Rate Limiting, Clouds (Azure, AWS, GCP), ...

2.4K
Stars
83/100
Confiance
Catégorie: devopsAudit

可能是最深度的 AI 投研报告 Skill:九章个股深研 + 九章财报深度分析,脚本化 DCF/EPV 与可复算估值

234
Stars
75/100
Confiance
Catégorie: utilityAudit

A self-learning skill layer for Claude Code that automatically distills, merges, updates, and prunes skills from real sessions.

413
Stars
75/100
Confiance
Catégorie: coding-agentsAudit

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
Confiance
Catégorie: researchAudit

A Claude Code custom skill for generating structured Chinese prompts for ByteDance's Seedance 2.0 AI video generation platform.

2.2K
Stars
72/100
Confiance
Catégorie: mediaAudit

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
Confiance
Catégorie: design-creativeAudit

Use when the user asks to design a multi-agent system, pick an orchestration pattern (supervisor/swarm/pipeline), generate tool schemas for agents, or evaluate agent execution logs for cost, latency, and failure bottlenecks. Examples: 'design an agent architecture for research automation', 'generate Anthropic tool schemas from these tool descriptions', 'analyze these agent run logs for bottlenecks'. NOT for Claude Code workflow files (use workflow-builder) or single-agent prompt design (use agent-workflow-designer).

25K
Stars
83/100
Confiance
Catégorie: researchAudit

When the user wants to plan, design, or implement an A/B test or experiment. Also use when the user mentions "A/B test," "split test," "experiment," "test this change," "variant copy," "multivariate test," "hypothesis," "conversion experiment," "statistical significance," or "test this." For tracking implementation, see analytics-tracking.

25K
Stars
77/100
Confiance
Catégorie: design-creativeAudit

Distilled variant of Whisper for speech recognition. 6x faster, 50% smaller, within 1% word error rate.

4.1K
Stars
74/100
Confiance
Catégorie: media-automationAudit

The fastest PDF library for Python and Rust. Text extraction, image extraction, markdown conversion, PDF creation & editing. 0.8ms mean, 5× faster than industry leaders, 100% pass rate on 3,830 PDFs. MIT/Apache-2.0.

825
Stars
72/100
Confiance
Catégorie: rag-knowledgeAudit