For platform teams, engineering managers, and orgs that want AI-assisted development with real governance. Session protocol, review gates, and ADR-steered agent behavior built in.
Each AI tool has its own native marketplace flow. This repo ships a Claude Code marketplace at .claude-plugin/marketplace.json and a Copilot CLI marketplace at .github/plugin/marketplace.json, so the same repository URL works in both CLIs. Pick yours and paste the command(s) inside the CLI session.
Claude Code. One command installs the full set; restart Claude Code when it finishes.
/install-plugin rjmurillo/ai-agents
GitHub Copilot CLI. Two steps: register the marketplace, then install the Copilot-targeted toolkit. No restart needed afterward; Copilot CLI picks agents up automatically.
/plugin marketplace add rjmurillo/ai-agents
/plugin install project-toolkit@ai-agents
A Claude install lands 23 agents, 23 commands, 29 hooks, and 69 skills. A Copilot install lands 24 agents, 28 hooks, and 81 skills generated from the same canonical sources. See Verify Installation for the per-tool sanity check, or More Installation Options for component-level installs (agents only, etc.).
| Component | Claude Code | Copilot CLI |
|---|---|---|
| Agents | 23 | 24 |
| Skills | 69 | 81 |
| Slash commands | 23 | n/a (interactive only) |
| Lifecycle hooks | 29 | 28 |
| Session protocol | 1 | 1 |
| Review gates | 5 | 5 |
Specialized agent roles include analyst, architect, implementer, QA, security, devops, and more. See the Agent Catalog for the full list.
/install-pluginnot recognized: That command is Claude Code only. In Copilot CLI use the two-step flow (/plugin marketplace add rjmurillo/ai-agentsthen/plugin install project-toolkit@ai-agents).- Copilot CLI install fails with "No plugin.json found in repository": This repo is a marketplace, not a single plugin. Run
/plugin marketplace add rjmurillo/ai-agentsfirst, then/plugin install project-toolkit@ai-agents. /pluginnot recognized in Copilot CLI: Update Copilot CLI to a recent stable release; plugin support is required. Runcopilot --versionin a regular terminal to check.- Plugin install fails or hangs: Confirm your AI tool is on a recent stable release that supports the install command, then retry. Check the version per tool: in Claude Code use
/versionor the title bar; for Copilot CLI runcopilot --versionin a regular terminal. - Agents not responding after install: Restart Claude Code (Copilot CLI does not need a restart). Then verify with
Task(subagent_type="analyst", prompt="Hello, are you available?")in Claude Code,copilot plugin listin Copilot CLI to confirmproject-toolkit@ai-agentsis installed, or@orchestrator Hello, are you available?in VS Code Copilot Chat.
| I want to... | Go to |
|---|---|
| Use the agents right now | Fastest Start (above) |
| Understand how it works | Key Concepts |
| Contribute or modify agents | Developer Setup |
| See all available agents | Agent Catalog |
| Full installation options | Alternative: Full Installation |
- AI Agent System
AI Agents is a coordinated multi-agent system for software development. It provides specialized AI agents that handle different phases of the development lifecycle, from research and planning through implementation and quality assurance.
The orchestrator is the hub of operations. Within it has logic from taking everything from a "vibe" or a "shower thought" and building out a fully functional spec with acceptance criteria and user stories, to taking a well defined idea as input and executing on it. The Claude bundle ships 23 agents and the Copilot bundle ships 24 agents that cover the roles of software development, from vision and strategy, to architecture, implementation, and verification. Each role looks at something specific, like the critic that just looks to poke holes in other agents' (or your own) work, or DevOps that's concerned about how you deploy and operate the thing you just built.
The agents themselves use the platform specific handoffs to invoke subagents, keeping the orchestrator context clean. A great example of this is orchestrator facilitating creating and debating an Architectural Decision Record from research and drafting, to discussion, iterating on the issues, tie breaking when agents don't agree. And then extracting persistent knowledge to steer future agents to adhere. Artifacts are stored in your memory system if you have one enabled, and Markdown files for easy reference to both agents and humans.
- 23+ specialized agents for different development phases (analysis, architecture, implementation, QA, etc.)
- Explicit handoff protocols between agents with clear accountability
- Multi-Agent Impact Analysis Framework for comprehensive planning
- Cross-session memory with citation verification, graph traversal, and health reporting via Serena + Forgetful
- Self-improvement system with skill tracking and retrospectives
- Quality gates with pre-PR validation, session protocol enforcement, and automated CI checks
- 69+ reusable skills for common development workflows (git, PR management, testing, linting)
- One-step plugin install through Claude Code's
/install-pluginor Copilot CLI's/plugin marketplace addflow - AI-powered CI/CD with issue triage, PR quality gates, and spec validation
| Term | Definition |
|---|---|
| Agent | A specialized AI persona with a defined role (analyst, implementer, security, etc.) |
| Orchestrator | The coordinating agent that routes tasks to specialists and synthesizes results |
| Handoff | Explicit transfer of context and control between agents with clear accountability |
| Skill | A reusable workflow component for common tasks (69+ included: git, PR, testing, linting) |
| Memory | Cross-session context persistence via Serena + Forgetful for knowledge retention |
| ADR | Architectural Decision Record—structured documents capturing design decisions |
| Quality Gate | Validation checkpoint (critic review, QA pass, security scan) before proceeding |
The Fastest Start above is the recommended path. Use the commands below when you want component-level control (agents only, no skills, etc.).
See CONTRIBUTING.md for development setup including Python 3.14.x, pre-commit hooks, and test dependencies. Day-to-day plugin use does not need either.
The Fastest Start commands install the full toolkit. For component-level installs, register the marketplace once in the CLI you are using and then install just the parts you want. Claude Code resolves that repository to .claude-plugin/marketplace.json; Copilot CLI resolves it to .github/plugin/marketplace.json. In Claude Code you can also use /install-plugin rjmurillo/ai-agents as a one-step shortcut that registers the marketplace and prompts for plugin selection.
Claude Code
/plugin marketplace add rjmurillo/ai-agents
| Component | Install Command | What You Get |
|---|---|---|
| Claude agents only | /plugin install claude-agents@ai-agents |
24 agent definitions from src/claude/ (no skills, commands, or hooks) |
| Project toolkit | /plugin install project-toolkit@ai-agents |
23 agents, 23 slash commands, 29 hooks, and 69 reusable skills from .claude/ |
GitHub Copilot CLI
/plugin marketplace add rjmurillo/ai-agents
| Component | Install Command | What You Get |
|---|---|---|
| Copilot full toolkit | /plugin install project-toolkit@ai-agents |
24 agents, 28 hooks, 81 skills from src/copilot-cli/ (Copilot CLI) |
Claude exposes both an agents-only bundle (claude-agents, from src/claude/) and the full toolkit (project-toolkit, from ./.claude); the latter ships 23 agents because src/claude/ and .claude/agents/ are two different curated sets, kept in sync where they overlap. Copilot CLI installs ship a single project-toolkit plugin from src/copilot-cli/ because that directory's plugin.json declares one identity; an agents-only Copilot install would silently register as project-toolkit and is therefore not advertised (issue #1840).
After installing, confirm the agents are loaded.
Claude Code:
Task(subagent_type="analyst", prompt="Hello, are you available?")
GitHub Copilot CLI:
copilot plugin listThe output should include project-toolkit@ai-agents (or whichever component you installed). To exercise an agent end-to-end, run copilot -p "analyst: respond with 'available'".
VS Code (Copilot Chat):
@orchestrator Hello, are you available?
| Platform | Agent Location | Usage |
|---|---|---|
| Claude Code CLI | src/claude/ |
Use Task(subagent_type="...") |
| GitHub Copilot CLI | src/copilot-cli/ |
Use --agent flag, /agent to select, or call out agent by name |
| VS Code / GitHub Copilot | src/vs-code-agents/ |
Use @agent syntax in Copilot Chat |
See docs/installation.md for complete installation documentation, including platform-specific paths, troubleshooting, and post-installation steps.
After installing the agents with the method of your choice, you can either select one of them explicitly, ask your LLM to use the agent by name, or even prefix your input with the name of the agent.
Here are prompts you can copy and paste. Prefix with the agent name to route directly, or use the orchestrator for multi-step workflows.
Review code quality:
critic: review @src/auth/login-handler.ts for coupling, error handling gaps, and test coverage. Deliver an APPROVE or REJECT verdict with specific line references.
Shows the critic agent doing a focused code review.
Investigate a bug:
analyst: the /api/users endpoint returns 500 when the email contains a plus sign. Trace the request through the handler, identify the root cause, and propose a fix.
Shows the analyst doing root cause analysis on a specific bug.
Scan for vulnerabilities:
security: scan @src/api/ for OWASP Top 10 vulnerabilities. Focus on injection, broken auth, and data exposure. Output a threat matrix with CWE identifiers and severity ratings.
Shows the security agent doing a targeted scan.
Write tests for existing code:
qa: write pytest tests for @scripts/validate_session_json.py. Cover happy path, malformed input, missing required fields, and boundary conditions. Target 95% line coverage.
Shows the QA agent generating tests with specific coverage targets.
Document a module:
explainer: document @scripts/memory_enhancement/ as a user guide. Include purpose, installation, CLI usage with examples, and architecture overview. Write for developers who have never seen this codebase.
Shows the explainer creating developer documentation.
Plan a feature:
milestone-planner: break down "add webhook retry with exponential backoff" into milestones. Include acceptance criteria, estimated complexity, dependencies, and a suggested implementation order.
Shows the planner creating structured work packages.
End-to-end feature pipeline:
orchestrator: build the webhook retry system described in @.agents/specs/webhook-retry.md. Start with analyst to verify requirements. Then milestone-planner to create work packages. Run critic to stress-test the plan. Then implementer to write code and tests. Run qa to verify coverage meets acceptance criteria. Run security to scan for injection and replay risks. Fix all critical findings recursively until critic, qa, and security pass. Open a PR.
The orchestrator chains seven agents into a full development pipeline with quality gates at each stage.
Architecture review:
orchestrator: conduct a full review of @docs/architecture/service-mesh.md. Route through analyst for data accuracy, architect for structural decisions, security for threat modeling with CWE/CVSS ratings, critic to stress-test for gaps, and independent-thinker to challenge assumptions. Synthesize all findings into a single summary highlighting consensus and disagreements.
Five agents examine the same artifact through different lenses. The orchestrator synthesizes their independent assessments.
Debug, fix, and ship:
orchestrator: the payment webhook handler drops events when Redis is unavailable. Have analyst investigate the failure pattern in the logs. Then architect propose a resilient design with fallback queuing. Then implementer build the fix with tests. Run qa and security to validate. Open a PR when all checks pass.
Turns an incident report into a shipped fix through structured agent collaboration.
Technology migration evaluation:
orchestrator: we are considering migrating from REST to gRPC for internal services. Route through analyst to research benchmarks and ecosystem maturity. Then architect to map impact on existing contracts. Then security to threat-model the new transport layer. Then devops to estimate CI/CD changes. Then independent-thinker to argue the strongest case for staying with REST. Then high-level-advisor to deliver a GO or NO-GO verdict with conditions.
Six agents build a decision package. Each contributes a different dimension of analysis. The advisor synthesizes everything into an actionable verdict.
Strategic prioritization:
orchestrator: we have three candidate features for next quarter: plugin marketplace, offline mode, and admin audit logging. For each, run analyst for effort and risk, roadmap to score with RICE and KANO, security for compliance implications, and devops for operational burden. Then independent-thinker to argue which one we will most regret skipping. Then high-level-advisor to rank all three with a clear recommendation.
The orchestrator runs the same evaluation pipeline across all candidates, producing comparable data for a defensible quarterly plan.
Six slash commands that map to the development lifecycle. Each one activates the right agents and quality gates automatically.
DEFINE PLAN BUILD VERIFY REVIEW SHIP
┌──────┐ ┌──────┐ ┌──────┐ ┌──────┐ ┌──────┐ ┌──────┐
│ Idea │ ───> │ Spec │ ───> │ Code │ ───> │ Test │ ───> │ QA │ ───> │ Go │
│Refine│ │ PRD │ │ Impl │ │Debug │ │ Gate │ │ Live │
└──────┘ └──────┘ └──────┘ └──────┘ └──────┘ └──────┘
/spec /plan /build /test /review /ship
| What you're doing | Command | What happens |
|---|---|---|
| Define what to build | /spec |
CVA analysis, testable acceptance criteria, critic review |
| Plan how to build it | /plan |
Milestones, atomic tasks (S/M/L), dependency graph, risk register |
| Build incrementally | /build |
TDD slices, atomic commits, code quality scoring |
| Prove it works | /test |
6 quality gates (functional, non-functional, security, DevOps, DX, observability) |
| Review before merge | /review |
5-axis review (architecture, security, quality, tests, standards) |
| Ship to production | /ship |
Pre-flight checks, PR creation, ship report |
Each command chains to the next. Output from /spec feeds into /plan, which feeds into /build, and so on. You can also jump in at any point for smaller tasks.
Standard feature:
/spec Add OAuth2 login flow with JWT tokens
/plan
/build
/test
/review
/ship
Quick fix:
/build Fix null reference in UserService.GetById
/test
/ship
See docs/workflow-commands.md for the full command reference.
The orchestrator coordinates specialized agents through explicit handoffs. Each agent focuses on its domain, and the orchestrator synthesizes results.
flowchart LR
User([User]) --> Orchestrator
subgraph Planning
Orchestrator --> Analyst
Orchestrator --> Architect
Orchestrator --> Planner[Milestone Planner]
end
subgraph Implementation
Orchestrator --> Implementer
Implementer --> Code[Code + Tests]
end
subgraph Quality
Orchestrator --> QA
Orchestrator --> Security
Orchestrator --> Critic
end
Code --> QA
QA --> |pass| Done([Done])
QA --> |fail| Implementer
Critic --> |approve| Done
Critic --> |reject| Implementer
Typical flow:
- User describes a task to the Orchestrator
- Orchestrator routes to Analyst for research and feasibility
- Architect designs the solution; Milestone Planner breaks it into work packages
- Implementer writes code and tests
- QA and Security validate; Critic stress-tests the approach
- On approval, work is complete; on failure, it loops back for fixes
The Claude Code bundle ships 23 agents and the Copilot CLI bundle ships 24 (Copilot adds backlog-generator, Claude adds spec-generator; both bundles include the rest). Both bundles share the same templates.
| Agent | Purpose | Output | Bundle |
|---|---|---|---|
| orchestrator | Task coordination and routing | Delegated results from specialists | both |
| analyst | Research, feasibility analysis, trade-off evaluation | Quantitative findings with evidence | both |
| architect | System design evaluation, ADRs, pattern enforcement | Rated assessments (Strong/Adequate/Needs-Work) | both |
| milestone-planner | Milestones and work packages | Implementation plans with acceptance criteria | both |
| implementer | Production code and tests | Code, tests, commits | both |
| critic | Plan stress-testing, gap identification | Verdicts: APPROVE / APPROVE WITH CONDITIONS / REJECT | both |
| qa | Test strategy and verification | Test reports, coverage analysis | both |
| security | Threat modeling, vulnerability assessment | Threat matrices with CWE/CVSS ratings | both |
| devops | CI/CD pipelines, operational planning | Infrastructure configs, maintenance estimates | both |
| roadmap | Strategic prioritization, RICE/KANO analysis | Priority stacks, cost-benefit analysis | both |
| retrospective | Learning extraction | Actionable insights, skill updates | both |
| memory | Cross-session context | Retrieved knowledge, stored observations | both |
| skillbook | Skill management | Atomic strategy updates | both |
| explainer | PRDs and documentation | Specs, user guides | both |
| task-decomposer | Atomic task breakdown | Estimable work items with done criteria | both |
| high-level-advisor | Strategic decisions, unblocking | Verdicts: GO / CONDITIONAL GO / NO-GO | both |
| independent-thinker | Challenge assumptions, devil's advocate | Counter-arguments with alternatives | both |
| pr-comment-responder | PR review handling | Triaged responses, resolution tracking | both |
| debug | Debugging assistance, root cause analysis | Diagnostic findings with resolution steps | both |
| janitor | Code and documentation cleanup | Refactoring and cleanup suggestions | both |
| issue-feature-review | Feature-request triage on GitHub issues | Constructive verdict with next steps | both |
| merge-resolver | Resolve git/PR merge conflicts | Pattern-based resolution plan | both |
| negotiation | Offer analysis and counter-proposals | Value-gap analysis with RADAR protocol | both |
| spec-generator | Requirement specifications, EARS format | Structured specs with acceptance criteria | Claude Code only |
| backlog-generator | Proactive task discovery when idle | Sized tasks from project state analysis | Copilot CLI only |
See AGENTS.md for detailed agent documentation.
ai-agents/
├── src/
│ ├── vs-code-agents/ # VS Code / GitHub Copilot agents
│ ├── copilot-cli/ # GitHub Copilot CLI agents
│ └── claude/ # Claude Code CLI agents
├── templates/ # Agent template system
├── scripts/ # Validation and utility scripts
├── docs/ # Documentation
├── .agents/ # Agent artifacts (ADRs, plans, etc.)
├── .claude-plugin/ # Claude Code marketplace manifest
├── .github/plugin/ # GitHub Copilot CLI marketplace manifest
├── .github/copilot-instructions.md # GitHub Copilot instructions
├── CLAUDE.md # Claude Code instructions
└── AGENTS.md # Detailed usage guide
Agent not responding or not found
- Restart your editor after installation to reload agent definitions
- Verify installation with the Verify Installation commands
- Check that you're using the correct syntax for your platform (
Task()for Claude,@agentfor VS Code)
/install-plugin command not recognized
/install-pluginis a Claude Code CLI shortcut. In Copilot CLI use the explicit two-step flow:/plugin marketplace add rjmurillo/ai-agents/plugin install project-toolkit@ai-agents
- Ensure you're running inside Claude Code CLI or Copilot CLI, not a regular shell. The command is built into the AI tool.
Python version errors when running tests
- This project requires Python 3.14.x for development. End users installing the plugins do not need Python.
- The
.python-versionfile pins the exact version (currently 3.14.4) - See CONTRIBUTING.md for detailed setup
Orchestrator not routing to agents correctly
- Be explicit: prefix prompts with the agent name (e.g.,
analyst: ...) - Check that agents were installed for your specific platform
- Review Quick Start examples for correct syntax
See CONTRIBUTING.md for detailed contribution guidelines.
If you're contributing code or running tests locally:
-
Fork and clone the repository
-
Install Python dependencies:
# Create virtual environment (optional but recommended) uv venv source .venv/bin/activate # On Windows: .venv\Scripts\activate # Install project with dev dependencies uv pip install -e ".[dev]"
-
Set up environment variables (copy
.env.exampleto.envand fill in your API keys) -
Enable pre-commit hooks:
git config core.hooksPath .githooks -
Run tests to verify setup:
python -m pytest tests/ -v
-
Make changes following the guidelines
-
Submit a pull request
This project uses a template-based generation system. To modify agents:
- Edit templates in
templates/agents/*.shared.md - Run
python build/generate_agents.pyto regenerate - Commit both template and generated files
Do not edit files in src/vs-code-agents/ or src/copilot-cli/ directly. See CONTRIBUTING.md for details.
| Document | Description |
|---|---|
| docs/getting-started.md | Step-by-step setup guide |
| docs/agent-catalog.md | All agents with capabilities and examples (23 in Claude bundle, 24 in Copilot bundle) |
| docs/skill-reference.md | All skills with usage descriptions (69 in Claude bundle, 81 in Copilot bundle) |
| docs/architecture.md | Plugin structure, template system, design decisions |
| docs/customization.md | How to extend and customize agents, skills, and hooks |
| docs/installation.md | Complete installation guide |
| docs/project-structure.md | Annotated repo layout (what to edit vs generated) |
| AGENTS.md | Comprehensive usage guide |
| CONTRIBUTING.md | Contribution guidelines and agent development |
| CLAUDE.md | Claude Code integration |
| copilot-instructions.md | GitHub Copilot integration |
| docs/workflow-commands.md | Lifecycle commands (/spec, /plan, /build, /test, /review, /ship) |
| docs/ideation-workflow.md | Ideation workflow documentation |
| docs/markdown-linting.md | Markdown standards |
MIT
