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/plan-feature.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/plan-feature)<a href="https://agentmods.dev/commands/coleam00/archon/plan-feature"><img src="https://agentmods.dev/badge/commands/coleam00/archon/plan-feature/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/plan-feature"><img src="https://agentmods.dev/badge/commands/coleam00/archon/plan-feature.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 | $0.00010 | $0.01275 |
| Opus 5.5 | $0.00004 | $0.00510 |
| Sonnet 5.5 | $0.00002 | $0.00255 |
| Haiku 4.5 | $0.00001 | $0.00128 |
Grade A, and why
plan-feature scanned grade A with 1 finding 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 2d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
5. Manual test: {specific curl command or UI steps to verify the feature} Copies of this mod
1 near-identical copy found in the catalogue:
- plan-feature — 94% identical, 14 lines differ
How it starts
The opening of the file, as written. The whole thing — 169 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Plan Feature: Comprehensive Archon Implementation Planning
Objective
Produce a detailed, actionable implementation plan for: $ARGUMENTS
The plan will be saved to .claude/archon/plans/{kebab-case-name}.md and is designed to be
consumed by the /execute command.
Phase 1: Feature Understanding
Restate the feature request in your own words. Identify:
- Problem being solved — What user pain point or capability gap does this address?
- Success criteria — What does "done" look like? How will we verify it works?
- Scope boundaries — What is explicitly in scope vs. out of scope?
- Package impact — Which workspace packages are affected? Read the root
package.jsonand.archon/architecture.mdfor the current package map and boundaries. - Interface changes — Does this touch
IPlatformAdapter,IAgentProvider,IDatabase, orIWorkflowStore? New interfaces needed?
Phase 2: Codebase Intelligence
Use subagents to perform targeted codebase research in parallel. Spawn separate subagents for:
Subagent A — Affected package deep-dive: Read all relevant source files in the affected packages. Map the current data flow. Identify every file that will need to change.
Subagent B — Interface and type contracts:
Read packages/core/src/types/ and relevant index.ts exports. Understand what interfaces
exist and how they're consumed across packages.
Subagent C — Test patterns: Find existing test files similar to the area of change:
find packages/ -name "*.test.ts" | head -30
Read 2-3 representative test files to understand mocking patterns, assertion style, and
mock.module() isolation requirements per package.
Subagent D — Related prior work:
git log --oneline --all | head -20
Read recent commits touching relevant files to understand change patterns.
Synthesize findings: current state, gaps, constraints.
Phase 3: External Research (if needed)
If the feature involves external APIs, new libraries, or unfamiliar patterns, use web search to research:
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.
- 2d ago Changed · -1 lines 7ae1a7cd5864
- 4d ago Changed · -1 lines 21010c22029c
- 1mo ago First seen · 171 lines · 10 tokens per session scan A 2d824ce16c7f
plan-feature is a command published in the GitHub repository coleam00/Archon (23,704 stars, last pushed today), licensed MIT. It adds 10 tokens to every session and 1,275 once invoked, about $0.0000 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). 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.