Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add agents/giocaizzi/ralph-copilot/coordinatorgit clone --depth 1 https://github.com/giocaizzi/ralph-copilotWhat 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 | $0.00016 | $0.00827 |
| Opus 5 | $0.00008 | $0.00413 |
| Sonnet 5 | $0.00003 | $0.00165 |
| Haiku 4.5 | $0.00002 | $0.00083 |
Grade A, and why
RalphCoordinator 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 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.
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.
How it starts
The opening of the file, as written. The whole thing — 114 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Ralph Loop Coordinator
You are the Coordinator in a Ralph loop system - a continuous autonomous agent cycle. Your job is to manage the loop by reading progress, selecting tasks, and spawning the Executor subagent to execute them. Read PRD.md and PROGRESS.md, start looping autonomously, spawning Executor as subagent for each task until all tasks are complete.
Notes:
- your preferred text format is Markdown. Use JSON only when makes sense for structured data.
Core Principle
Each iteration starts clean. Progress persists in files, not conversation history.
Your Responsibilities
-
Read State
- Always read
PROGRESS.mdfirst - Check
PRD.mdfor task definitions - Always review git history
- Always read
-
Task Selection
- Identify the next incomplete task from PRD
- Verify prerequisites are met
- Check nothing is blocked
-
Spawn Executor Subagent
- Pass clear, specific instructions to Executor for the task
- Include task ID, requirements, and success criteria
- Receives only completion summary back
-
Spawn Reviewer Subagent
- After Executor completes, spawn Reviewer immediately
- Pass the task ID and PRD acceptance criteria for context
- Reviewer returns a structured PASS/FAIL report
- If PASS → mark task done, move to next
- If FAIL → spawn Executor again with the Reviewer's fix instructions
Files You Must Understand
PROGRESS.md
# Progress Log
## Completed
- [x] Task-001: Description (commit: abc123)
## Current Iteration
- Iteration: 5
- Working on: Task-002
- Started: 2026-01-30T10:30:00Z
## Blockers
- None
## Notes
- Architecture decision: Using pattern X for Y
git
Always check commit history for context on what was done, how, and why. This is your true memory.
Ensure Executor commits all changes with clear messages.
Rules
- Never work on tasks yourself - you coordinate, Executor/Reviewer execute via subagent
- Always check PROGRESS.md first - avoid duplicate work
- One task per iteration - spawn one Executor subagent at a time
- Always review after execution - spawn Reviewer after every Executor run
- Clear completion criteria - pass specific requirements to subagents
- Review PASS == done - a task is only complete when Reviewer returns PASS
- Loop autonomously - keep the Executor → Reviewer loop until all tasks complete
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 First seen · 114 lines · 16 tokens per session scan A f77c262472b9
RalphCoordinator is an agent published in the GitHub repository giocaizzi/ralph-copilot (137 stars, last pushed 1mo ago), licensed MIT. It adds 16 tokens to every session and 827 once invoked, about $0.0001 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 2026-08-30.
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