agent-almanac

agent
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  • License — License: MIT
  • Description — Repository has a description
  • Active repo — Last push 0 days ago
  • Low visibility — Only 8 GitHub stars
Code Pass
  • Code scan — Scanned 12 files during light audit, no dangerous patterns found
Permissions Pass
  • Permissions — No dangerous permissions requested
Purpose
This project is a curated library of executable skills, specialized agents, and pre-built team compositions designed for AI-assisted development tools like Claude Code, Cursor, and Codex. It provides structured, reusable procedures and an interactive visualization interface for managing these AI workflows.

Security Assessment
The codebase presents a low security risk. A scan of 12 files found no dangerous patterns, hardcoded secrets, or requests for dangerous system permissions. Because the tool fundamentally consists of markdown files defining AI behaviors and skills, it relies on the host AI tool (like Claude Code) to execute commands rather than executing arbitrary shell commands or making direct network requests itself. No sensitive data is accessed directly by the package. Overall risk: Low.

Quality Assessment
The project is actively maintained, with its most recent code push happening today. It is released under the standard MIT license, allowing for broad usage and modification. The repository includes clear documentation, continuous integration workflows for validation, and follows an open standard for agent skills. The primary concern is low community visibility; with only 8 GitHub stars, the project has not yet been widely vetted by a large audience, meaning users should rely on their own testing rather than established community trust.

Verdict
Safe to use, though developers should expect an early-stage project with limited community validation.
SUMMARY

Agent Almanac — a curated reference of executable skills, specialist agents, and teams for AI-assisted development, with interactive visualization

README.md

Agent Almanac

Agent Almanac

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License: MIT
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A library of executable skills, specialist agents, and pre-built teams for Claude Code and compatible AI tools. Define repeatable engineering procedures once and have AI agents execute them with built-in validation and error recovery. Compose specialists into review teams that catch issues a single reviewer would miss. Built on the Agent Skills open standard.

At a Glance

  • 340 skills across 61 domains — structured, executable procedures
  • 69 agents — specialized Claude Code personas covering development, review, compliance, and more
  • 16 teams — predefined multi-agent compositions for complex workflows
  • 21 guides — human-readable workflow, infrastructure, and reference documentation
  • Interactive visualization — force-graph explorer with 340 R-generated skill icons and 9 color themes

How It Works

Building Block Location Purpose
Skills skills/<skill-name>/SKILL.md Executable procedures (how)
Agents agents/<name>.md Specialized personas (who)
Teams teams/<name>.md Multi-agent compositions (who works together)
Guides guides/<name>.md Human-readable reference (context)

Ask Claude Code to review your R package, and the r-package-review team activates 4 agents — each following specialized skills for code quality, architecture, security, and best practices — then synthesizes their findings into a single report.

Works with

Skills follow the Agent Skills open standard and work with any tool that reads markdown:

Tool Integration Details
Claude Code Full (skills, agents, teams) Native discovery via .claude/ symlinks
Codex (OpenAI) Skills Symlink into .agents/skills/
Cursor Skills Map to .cursor/rules/*.mdc files
Gemini CLI, Aider, etc. Skills Point context to any SKILL.md file

Agents and teams use Claude Code's subagent architecture. For other tools, skills are the primary integration surface. See skills/README.md for setup instructions.

Quick Start

60-second path

No setup needed — reference any skill by path in Claude Code:

> "Follow skills/commit-changes/SKILL.md to stage and commit my changes"

Install the CLI

npm install -g agent-almanac

Browse campfires (teams), install skills and agents, and manage content across 12+ frameworks. See cli/README.md for full usage.

Full setup

Prerequisites: Claude Code CLI installed, Node.js (for README generation and the visualization).

git clone https://github.com/pjt222/agent-almanac.git
cd agent-almanac

Then in Claude Code:

> "Use the code-reviewer agent to review my latest changes"
> "Follow the commit-changes skill to stage and commit"
> "Activate the r-package-review team to review this package"

Make skills available as slash commands

# From the repository root:
ln -s ../../skills/commit-changes .claude/skills/commit-changes
# Then invoke with /commit-changes in Claude Code

See Symlink Architecture for details. All 328 skills are already symlinked in this repository.

Explore visually

cd viz && npm install && npm run dev
# Open http://localhost:5173 for the interactive force-graph explorer

See viz/README.md for full build instructions.

Directory Map

agent-almanac/
  skills/      328 executable procedures across 58 domains
  agents/       66 specialist personas
  teams/        15 multi-agent compositions with 8 coordination patterns
  guides/       19 human-readable reference docs
  viz/          Interactive force-graph explorer with R-generated icons
  tests/        30 test scenarios for validation
  i18n/         Translations (4 locales: de, zh-CN, ja, es)
  cli/          Universal installer CLI (npm install -g agent-almanac)
  scripts/      Build and CI automation
  sessions/     Tending session archives

Guides

New here? Start with Understanding the System. See all guides for the full categorized list.

Workflow

  • Understanding the System — Entry point: what skills, agents, and teams are, how they compose, and how to invoke them
  • Creating Skills — Authoring, evolving, and reviewing skills following the agentskills.io standard
  • Creating Agents and Teams — Designing agent personas, composing teams, and choosing coordination patterns
  • Running a Code Review — Multi-agent code review using review teams for R packages and web projects
  • Managing a Scrum Sprint — Running Scrum sprints with the scrum-team: planning, dailies, review, and retro
  • Visualizing Workflows with putior — End-to-end putior workflow visualization from annotation to themed Mermaid diagrams
  • Running Tending — AI meta-cognitive tending sessions with the tending team
  • Running a Translation Campaign — End-to-end guide for translating all skills, agents, teams, and guides into supported locales using the translation-campaign team
  • Unleash the Agents — Structured multi-agent consultation at three tiers for open-ended hypothesis generation
  • Team Assembly Prompt Patterns — How to phrase requests to Claude Code for multi-agent team work at every level of specificity
  • Production Coordination Patterns — Real-world multi-agent orchestration patterns: barrier synchronization, silence budgets, health checks, degraded-wave policies, and cost-aware scheduling
  • AgentSkills Alignment — Standards compliance audits using the agentskills-alignment team for format validation, spec drift detection, and registry integrity

Infrastructure

  • Setting Up Your Environment — WSL2 setup, shell config, MCP server integration, and Claude Code configuration
  • Symlink Architecture — How symlinks enable multi-project discovery of skills, agents, and teams through Claude Code
  • R Package Development — Package structure, testing, CRAN submission, pkgdown deployment, and renv management

Reference

  • Quick Reference — Command cheat sheet for agents, skills, teams, Git, R, and shell operations
  • Agent Best Practices — Design principles, quality assurance, and maintenance guidelines for writing effective agents
  • Agent Configuration Schema — YAML frontmatter field definitions, validation rules, and JSON Schema for agent files

Design

Translations

Locale Language Skills Agents Teams Guides Total
de Deutsch 320/340 3/69 1/16 1/21 325/446 (72.9%)
zh-CN 简体中文 320/340 3/69 1/16 1/21 325/446 (72.9%)
ja 日本語 320/340 3/69 1/16 1/21 325/446 (72.9%)
es Español 320/340 3/69 1/16 1/21 325/446 (72.9%)

See i18n/README.md for the translation contributor guide.

Contributing

Contributions welcome! Each content type has its own guide:

Update the relevant _registry.yml when adding content, then run npm run update-readmes.

Support

If Agent Almanac makes your AI tools more capable, consider sponsoring its development.

Reliable AI assistance requires structured knowledge — and maintaining that structure is work that the models themselves cannot do.

License

MIT License. See LICENSE for details.

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