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/.github/prompts/prime-client.prompt.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-client)<a href="https://agentmods.dev/commands/coleam00/archon/prime-client"><img src="https://agentmods.dev/badge/commands/coleam00/archon/prime-client.svg" alt="Measured on agentmods" 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 | $0.00008 | $0.00215 |
| Opus 5 | $0.00004 | $0.00108 |
| Sonnet 5 | $0.00002 | $0.00043 |
| Haiku 4.5 | $0.00001 | $0.00021 |
Grade A, and why
prime-client 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 today.
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.
What it actually says
Prime Client: Load Frontend Context
Objective
Build comprehensive understanding of the client codebase by analyzing structure and key files.
Process
- Study the entry points (
client/src/main.tsx,client/src/App.tsx) - Study the components (
client/src/components/) - Study the API layer (
client/src/api/) - Check
client/package.jsonfor dependencies
Output
Produce a scannable summary of what you learned:
- Purpose: What the frontend does
- Tech Stack: Framework, UI library, state management
- Components: Key components and their responsibilities
- Data Flow: How data is fetched and managed
- Patterns: Component patterns, styling approach
Use bullet points. Keep it concise.
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.
- today First seen · 37 lines · 8 tokens per session scan A f6653f9f96e7
prime-client is a command published in the GitHub repository coleam00/Archon (23,398 stars, last pushed today), licensed MIT. It adds 8 tokens to every session and 215 once invoked, about $0.0000 per session on Opus 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 2026-09-08.
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.
cleanup
Autonomous cleanup-loop iteration: discover ONE target → complete execution → verify → report. Runs stateless: derive from current tree; assume prior runs left it consistent.
landing-page-generator-executor.template
This prompt was authored for Claude-style slash workflows. In Codex runtime, adapt tool calls as follows.
ui-fix.template
This prompt was authored for Claude-style slash workflows. In Codex runtime, adapt tool calls as follows.
stripe-backend
Centralized LLM prompt instructions for Copilot and Cursor, including scripts to convert and sync rules for Python, React, Shell, and TypeScript. Designed for rapid reuse and contribution across projects.
explain
System prompt for /explain slash command.