Q00/ouroboros is an Agent OS for running coding agents through interviews, staged evaluation, and repeated improvement cycles. It helps developers turn vague requests into tested code across multiple agent runtimes. Its catalogue add-ons provide workflows, agents, hooks, instructions, and integrations for operating those processes.
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 skills/q00/ouroboros/ralphnpx skills add Q00/ouroboros --skill ralphgit clone --depth 1 https://github.com/Q00/ouroborosWrote 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/skills/q00/ouroboros/ralph)<a href="https://agentmods.dev/skills/q00/ouroboros/ralph"><img src="https://agentmods.dev/badge/skills/q00/ouroboros/ralph.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 | $0.00013 | $0.03178 |
| Opus 5 | $0.00006 | $0.01589 |
| Sonnet 5 | $0.00003 | $0.00636 |
| Haiku 4.5 | $0.00001 | $0.00318 |
Grade A, and why
ralph 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 — 262 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/ouroboros:ralph
MCP-owned Ralph loop around background evolve_step jobs. "The boulder never stops."
Usage
ooo ralph --lineage-id <lineage_id>
/ouroboros:ralph --lineage-id <lineage_id>
# For a plain natural-language request, run `ooo interview` + `ooo seed` first,
# then call the MCP tool with a fresh lineage_id and the validated Seed YAML.
Trigger keywords: "ralph", "don't stop", "must complete", "until it works", "keep going"
How It Works
Ralph is owned by the ouroboros_ralph MCP tool. In non-plugin runtimes, the
tool starts one background Ralph job, runs repeated evolve_step generations
inside that job, and stops only when QA passes, convergence is reached, a
terminal evolution action occurs, cancellation is requested, or
max_generations is reached. In OpenCode plugin mode, the MCP tool returns a
delegated_to_plugin envelope with job_id=None; the bridge plugin dispatches
a child Task session that owns the loop instead of creating a local JobManager
job.
The client skill should not reimplement the loop. Deterministic frontmatter
dispatch is limited to the router's named --lineage-id option so raw trailing
text is never treated as lineage identity. Raw natural-language
ooo ralph "<request>" input must flow through the validated Seed path before
any mutating Ralph loop starts. Until a lineage id and optional Seed YAML are
prepared, ouroboros_ralph returns structured input guidance instead of
starting a job. Once the inputs are prepared, start the MCP-owned Ralph surface
once, then follow either the returned job tools path or the OpenCode Task widget
path.
Instructions
When the user invokes this skill:
Load MCP Tools (Required first)
The Ouroboros MCP tools are often registered as deferred tools that must be explicitly loaded before use. Do this before preparing input or calling Ralph:
- Use the active runtime's tool-discovery capability to find and load the Ralph/job MCP tools:
tool discovery query: "+ouroboros ralph job" - The loaded tools may be exposed under plugin-prefixed names such as
mcp__plugin_ouroboros_ouroboros__ouroboros_ralph. Use the actual tool names returned by runtime tool discovery; the bare names below are the canonical MCP tool names for documentation. - Confirm that
ouroboros_ralphand the job tools (ouroboros_job_wait,ouroboros_job_status,ouroboros_job_result, andouroboros_cancel_job) are callable. If the tools are unavailable, stop and tell the user that Ralph requires the Ouroboros MCP runtime.
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 · +35 lines c44e47021a8d
- 5d ago First seen · 227 lines · 13 tokens per session scan A 05fcdd108089
ralph is a skill published in the GitHub repository Q00/ouroboros (5,765 stars, last pushed yesterday), licensed MIT. It adds 13 tokens to every session and 3,178 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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Session wrap-up. Update memories, check plans, review git state, check inbox, flag loose ends. Use before closing a session or compacting context.
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GitHub operations via gh CLI: issues, PRs, CI runs, code review, API queries.
system_status
Check system health -- disk usage, memory, running processes, uptime.
branch_health
Quick health check -- test counts and file stats for AIPass branches.