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/patelr3/agents/ralph-loopnpx skills add patelr3/agents --skill ralph-loopgit clone --depth 1 https://github.com/patelr3/agentsWhat 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 | $0.00057 | $0.00945 |
| Opus 5 | $0.00028 | $0.00473 |
| Sonnet 5 | $0.00011 | $0.00189 |
| Haiku 4.5 | $0.00006 | $0.00094 |
Grade A, and why
ralph-loop 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 — 102 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Ralph Loop
Runs the Ralph execution loop (ralph.sh) that iterates through PRD user stories, spawning a fresh AI coding session per iteration.
The Job
Execute the ralph.sh script from this skill's scripts/ directory. The script reads a PRD JSON file and iterates through its user stories, invoking an AI tool (Copilot, Claude, or AMP) once per story.
Usage
${CLAUDE_PLUGIN_ROOT}/skills/ralph-loop/scripts/ralph.sh --prd <path-to-prd.json> [--tool copilot|claude|amp] [--port-offset N] [max_iterations]
Parameters
| Parameter | Required | Default | Description |
|---|---|---|---|
--prd <file> |
Yes | — | Path to the PRD JSON file (e.g., docs/prds/prd-2026-03-15-task-status.json) |
--tool <name> |
No | copilot |
AI backend: copilot, claude, or amp |
--port-offset N |
No | — | Port offset for parallel isolation (API=3001+N, Web=3000+N) |
max_iterations |
No | 10 |
Maximum loop iterations before aborting |
Example
# Run with Copilot (default), 12 iterations max
${CLAUDE_PLUGIN_ROOT}/skills/ralph-loop/scripts/ralph.sh \
--prd docs/prds/prd-2026-03-15-task-status.json \
--port-offset 10 \
12
What the Loop Does
Each iteration spawns a fresh AI session that:
- Reads the PRD JSON file
- Reads the progress log for context from prior iterations
- Picks the highest-priority story where
passes: false - Implements that one story
- Runs quality checks (typecheck, lint, tests)
- Commits with message:
feat: [US-XXX] - Story Title - Marks the story as
passes: truein the PRD JSON - Appends learnings to the progress file
- Checks if all stories pass — if so, updates PRD status to
complete, creates PR, enables auto-merge, and outputs<promise>PRD-COMPLETE</promise>
File Expectations
The script expects:
- PRD JSON: The file passed via
--prd(e.g.,docs/prds/prd-2026-03-15-task-status.json) - Progress file: Derived from the PRD filename —
prd-prefix replaced withprogress-,.jsonreplaced with.txt(e.g.,docs/prds/progress-2026-03-15-task-status.txt) - CLAUDE.md prompt: Located at
${CLAUDE_PLUGIN_ROOT}/skills/ralph-loop/scripts/CLAUDE.md(same directory asralph.sh)
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 102 lines · 57 tokens per session scan A aa3fc11103e6
ralph-loop is a skill published in the GitHub repository patelr3/agents (2 stars, last pushed 4mo ago), licensed MIT. It adds 57 tokens to every session and 945 once invoked, about $0.0003 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 2026-08-31.
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