agency-agents vs awesome-claude-agents

Role-specific AI instructions compared

agency-agents offers a broad, editable collection of role-specific instructions that can be installed into supported coding tools. awesome-claude-agents focuses on coordinating specialized agents within Claude Code, including recommendations tailored to a project's detected technologies.

agency-agentsawesome-claude-agents
LanguageShellnot specified
LicenseMITMIT
Stars156k4.4k
Forks25.2k531
Last analyzedOct 3, 2026Oct 3, 2026

Key differences

  • agency-agents spans professional areas such as engineering, design, marketing, security, and finance, while awesome-claude-agents focuses on software development roles and selected frameworks.
  • agency-agents provides Markdown instruction files and installer scripts; awesome-claude-agents configures agent recommendations in CLAUDE.md based on project files.
  • agency-agents supports installation into compatible tools, while awesome-claude-agents requires the Claude Code CLI and an authenticated Claude subscription.
  • awesome-claude-agents describes a 24-agent collection; agency-agents presents a broad roster organized by professional division and individual agent.
  • awesome-claude-agents labels itself experimental and warns that orchestration can consume substantial tokens; agency-agents notes that results depend on the host tool and model.
  • Both projects use the MIT license; agency-agents lists Shell as its language, while awesome-claude-agents is described through its Claude Code setup.

Choose agency-agents if you…

  • want to browse, adapt, or install role-specific instructions across a range of professional fields.
  • need reusable specialist workflows in compatible coding tools beyond a Claude Code-only setup.
  • prefer selecting agents by tool, division, or individual role, with installer options such as interactive selection and dry runs.
Read the agency-agents analysis →

Choose awesome-claude-agents if you…

  • already use Claude Code and want agent recommendations based on a project's detected technologies.
  • want to delegate software tasks to orchestrators and framework specialists for supported stacks such as Laravel, Django, Rails, React, or Vue.
  • are prepared to evaluate an experimental multi-agent workflow and its potential token use.
Read the awesome-claude-agents analysis →

This comparison is generated with AI from the OSRepos analyses of both projects. Always check each project's repository and documentation before choosing.

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