agentic-design-patterns: 29 essential agentic design patterns for building intelligent AI systems

by zeljkoavramovic · MCP Server · ★ 126

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

Security audit verdict: SAFE · quality 64/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

agentic-aiagentic-design-patternsagentic-workflowagentsaiai-agentsai-codingclaudeclaude-codecodex

Quick Facts

Stars126
Forks18
LanguageHTML
CategoryMCP Server
Quality Score64/100
Last Updated2026-05-26
Created2025-10-21
Platformsclaude-code, codex, mcp
Est. Tokens~30k

About agentic-design-patterns

Agentic Design Patterns This repository contains an interactive, single-file tutorial on essential agentic design patterns for building intelligent AI systems. Overview The included file is a self-contained interactive tutorial and reference guide to various patterns used in modern AI development.

Compatible Skills

These tools work well together with agentic-design-patterns for enhanced workflows:

  • design-system-ops — semantic(0.32)+complementary+same_lang+similar_pop (56%)
  • modularity — semantic(0.28)+complementary+rare_topics+same_lang+similar_pop (54%)
  • goal-workflow — semantic(0.17)+complementary+rare_topics+same_lang+similar_pop (51%)

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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