Archon is a workflow engine for AI coding agents that turns development processes into YAML-defined sequences with phases, validation gates, and artifacts. Developers use it to run repeatable processes such as planning, implementation, testing, code review, and pull-request creation across projects. The catalogue entries provide commands, agents, skills, hooks, instructions, and settings for working with Archon.
Borrowing it
Nothing to install: this file belongs to coleam00/Archon. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/coleam00/Archon/dev/.claude/commands/prime.mdgit clone --depth 1 https://github.com/coleam00/ArchonWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/commands/coleam00/archon/prime)<a href="https://agentmods.dev/commands/coleam00/archon/prime"><img src="https://agentmods.dev/badge/commands/coleam00/archon/prime/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/commands/coleam00/archon/prime"><img src="https://agentmods.dev/badge/commands/coleam00/archon/prime.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00009 | $0.00533 |
| Opus 5.5 | $0.00004 | $0.00213 |
| Sonnet 5.5 | $0.00002 | $0.00107 |
| Haiku 4.5 | $0.00001 | $0.00053 |
Grade A, and why
prime scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
1 near-identical copy found in the catalogue:
- prime — 89% identical, 25 lines differ
How it starts
The opening of the file, as written. The whole thing — 73 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Prime: Load Archon Project Context
Objective
Build comprehensive understanding of the Archon monorepo before beginning any work. This orients you on structure, active state, and key architectural conventions.
Process
1. Analyze Project Structure
List the monorepo packages:
!ls packages/
Show workspace scripts:
!cat package.json | head -35
2. Read Core Documentation
Read AGENTS.md in full for project rules and development guidelines. Follow its links to
.archon/direction.md, .archon/engineering.md, and the docs for focused project context.
3. Identify Key Entry Points
Read these files to understand the primary message and execution flow:
packages/core/src/orchestrator/orchestrator-agent.ts— single entry point for all platformspackages/core/src/handlers/command-handler.ts— slash command routing (no AI)packages/server/src/index.ts— server startup, adapter wiring, port allocationpackages/workflows/src/executor.ts— run setup; every workflow executes as a DAG indag-executor.ts
4. Understand Package Dependency Layers
Inspect the relevant packages/*/package.json manifests for workspace dependencies
before reporting dependency order. Read each package's entry points to understand
its responsibility.
5. Understand Current State
Check recent commits:
!git log -10 --oneline
Check current branch and working tree status:
!git status
List any active worktrees:
!git worktree list
Output Report
Provide a concise summary (under 300 words) covering:
Project Overview
- Archon: Self-hostable, governed agentic automation engine
- Bun + TypeScript monorepo; use
packages/and the rootpackage.jsonfor the current workspace structure - SQLite (default, zero-setup) or PostgreSQL (optional via DATABASE_URL)
Architecture
- Package dependency order and each package's responsibility
- Key interfaces:
IPlatformAdapter,IAgentProvider,IDatabase,IWorkflowStore - Message flow: platform adapter → orchestrator-agent → command handler OR AI provider
- Workflow execution:
discoverWorkflows→ router →executeWorkflow→executeDagWorkflow
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 8d ago Changed · -3 lines 1c279371c6da
- 17d ago Changed 817b283eb435
- 1mo ago First seen · 76 lines · 9 tokens per session scan A 4824e9bff1ea
prime is a command published in the GitHub repository coleam00/Archon (23,752 stars, last pushed today), licensed MIT. It adds 9 tokens to every session and 533 once invoked, about $0.0000 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other commands, from other repositories
fix-issues
Diagnose, reproduce, then fix reproducible open GitHub issues in parallel: one clean worktree/issue; symlink build artifacts to avoid rebuilds.
review-prs
Parallel PR triage: decide merge-worthiness, prepare rebased worktrees, fix blockers, return them for human merge.
triage
Classify/label newly opened GitHub issues missing labels.
release
Release all packages at specified version.
cleanup
Autonomous cleanup-loop iteration: discover ONE target → complete execution → verify → report. Runs stateless: derive from current tree; assume prior runs left it consistent.
hatch3r-workflow
Guided development lifecycle with 4 phases (Analyze, Plan, Implement, Review) and scale-adaptive Quick Mode for small tasks; --plan-file executes an approved plan document without re-deriving it.