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/jmstar85/oh-my-githubcopilot/ralphnpx skills add jmstar85/oh-my-githubcopilot --skill ralphgit clone --depth 1 https://github.com/jmstar85/oh-my-githubcopilotWhat 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 | $0.00036 | $0.00688 |
| Opus 5 | $0.00018 | $0.00344 |
| Sonnet 5 | $0.00007 | $0.00138 |
| Haiku 4.5 | $0.00004 | $0.00069 |
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 3d 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.
This is a copy
92% identical to ralph — 2 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 86 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Ralph
Ralph is a PRD-driven persistence loop that keeps working on a task until ALL user stories have passes: true and are reviewer-verified.
When to Use
- Task requires guaranteed completion with verification
- Work may span multiple iterations and needs persistence
- Task benefits from structured PRD-driven execution
When NOT to Use
- Full autonomous pipeline → use
/omg-autopilot - Explore or plan before committing → use
/plan - Quick one-shot fix → delegate to @executor
Flags
--no-prd: Skip PRD generation, work in legacy mode (for trivial fixes)--no-deslop: Skip the mandatory post-review cleanup pass
Steps
1. PRD Setup (first iteration)
- Check if
.omg/prd.jsonexists viaomg_read_prd - If none exists, generate a PRD scaffold with task-specific acceptance criteria
- CRITICAL: Replace generic criteria with specific, testable ones
- Initialize progress tracking
2. Pick Next Story
- Read PRD via
omg_read_prd - Select highest-priority story with
passes: false
3. Implement Current Story
- Delegate to @executor at appropriate complexity level
- If sub-tasks are discovered, add as new stories to PRD
4. Verify Acceptance Criteria
- For EACH criterion, verify with fresh evidence
- Run relevant checks (test, build, lint, typecheck)
- If any criterion NOT met, continue working
5. Mark Story Complete
- Set
passes: trueviaomg_update_story - Record progress in
progress.txt
6. Check PRD Completion
- Call
omg_check_completion - If NOT all complete, loop to Step 2
- If ALL complete, proceed to verification
7. Reviewer Verification
- @verifier checks against specific acceptance criteria from PRD
- @architect reviews for architectural soundness
7.5 Mandatory Cleanup Pass
- Unless
--no-deslop, run/ai-slop-cleaneron changed files only
7.6 Regression Re-verification
- Re-run all tests after cleanup pass
- Only proceed after regression tests pass
8. Completion
- On approval: run
/cancelfor clean exit - On rejection: fix issues, re-verify, loop back
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.
- 3d ago First seen · 86 lines · 36 tokens per session scan A d9b5cc54d8bc
ralph is a skill published in the GitHub repository jmstar85/oh-my-githubcopilot (153 stars, last pushed 3mo ago), licensed MIT. It adds 36 tokens to every session and 688 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 92% identical to ralph, differing in 2 lines, and is treated as a copy.
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