ralph

ralph is a skill for Claude Code from hg-pyun/claude-code-marketplace. It costs 100 tokens per session (6,537 once invoked), scanned A, original, MIT.

A workflow for carrying out every part of an approved product requirements document (PRD), a written list of features and acceptance checks. It follows test-driven development (TDD): write or use a failing test, make it pass, then clean up the code.

In plain words
What is it for?
Use it for multi-step development work with several independently checkable stories, including resuming an unfinished plan and rechecking the final result.
Why use it?
It reduces the risk of stopping after a partial implementation, skipping tests, or claiming completion without fresh evidence.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: mentions CLAUDE.md; names the TodoWrite tool.

Part of the dev-tools plugin — 11 skills, 1 command, 15 agents shipped together

Good fit Use it for multi-step development work with several independently checkable stories, including resuming an unfinished plan and rechecking the final result.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/hg-pyun/claude-code-marketplace/ralph
Install

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.

Any agent
npx skills add hg-pyun/claude-code-marketplace --skill ralph
Clone the repo
git clone --depth 1 https://github.com/hg-pyun/claude-code-marketplace

Made for: Claude Code.

Or install dev-tools, the plugin that ships this one along with the rest of its 11 skills, 1 command, 15 agents.

Wrote 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.

agentmods badge for ralph

README.md
[![agentmods](https://agentmods.dev/badge/skills/hg-pyun/claude-code-marketplace/ralph/github.svg)](https://agentmods.dev/skills/hg-pyun/claude-code-marketplace/ralph)
Your own site
<a href="https://agentmods.dev/skills/hg-pyun/claude-code-marketplace/ralph"><img src="https://agentmods.dev/badge/skills/hg-pyun/claude-code-marketplace/ralph/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for ralph

Your own site · 80×15
<a href="https://agentmods.dev/skills/hg-pyun/claude-code-marketplace/ralph"><img src="https://agentmods.dev/badge/skills/hg-pyun/claude-code-marketplace/ralph.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 100 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 6,537 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00100 $0.06537
Opus 5 $0.00050 $0.03268
Sonnet 5 $0.00020 $0.01307
Haiku 4.5 $0.00010 $0.00654

Measured 8d ago against content hash 9050303441b3, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

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 8d 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.

plugins/dev-tools/skills/ralph/SKILL.md · 267 lines

How it starts

The opening of the file, as written. The whole thing — 267 lines — stays where its author put it; the contents beside it link to each section on GitHub.

<Use_When>

  • A plan (.dt-handoff/<slug>/plan.md) is approved and execution must complete every story before stopping.
  • User says "ralph", "/ralph", "keep going until done", "끝까지 가줘", "finish this".
  • The task suits PRD-driven progress (multiple independently verifiable stories).
  • autopilot Phase 3 (Execution) invokes this skill as a sub-step.
  • A prior run left an incomplete .dt-handoff/<slug>/prd.json to resume. </Use_When>

<Do_Not_Use_When>

  • The user wants requirements capture (WHAT, not HOW), not execution → establish a spec first; ralph runs an existing plan/PRD.
  • The user wants consensus planning → ralplan.
  • The user wants parallel multi-agent decomposition → team.
  • The user wants a one-shot / trivial change → delegate to executor directly, no PRD overhead.
  • The user wants automatic commit/PR → refuse; ralph stops at "ready for commit".
  • No spec / plan exists and the task is vague → route to ralplan first to scope the work. </Do_Not_Use_When>

<Why_This_Exists> Complex tasks fail silently when an agent declares "done" on a partial implementation, skips tests, or forgets an edge case. The PRD loop structures work into stories with testable acceptance criteria and refuses to mark a story complete without fresh per-criterion evidence from the verifier agent — not inline self-verification. The reviewer pass adds an independent second opinion before declaring the batch ready.

The TDD Iron Law (failing test before production code) is enforced inside every story so tests encode intent rather than mirror implementation. The code-simplifier cleanup (Step 7.5) removes slop introduced during the loop, scoped to changed files; the post-cleanup regression re-verify exists because even small cleanup edits can regress. The 3-failure escalation branches by failure type — root cause unclear → debugger, design fundamentally wrong → architect — to avoid grinding on the wrong specialist.

Auto commit/PR is prohibited because this marketplace's git-commit / github-pr skills are user-triggered by design; chaining them would skip review opportunities the user expects.

The loop stays thin: handoff mechanics (@handoff-in/@handoff-out, descriptors, events.jsonl) are defined once in the handoff protocol; this skill references them rather than re-spelling them per step. </Why_This_Exists>

<Execution_Policy> Output language: status reports, story descriptions, and progress.txt use $LANGUAGE. prd.json field VALUES (descriptions, AC text) use $LANGUAGE; field NAMES stay English.

TDD Iron Law (non-negotiable): for each story, the test-engineer pass MUST produce a Red test that runs and fails for the expected reason BEFORE executor writes production code. Skipping Red is forbidden. Exception: pure-refactor stories tagged refactor may proceed without a new Red test if existing tests cover the behavior — note the exception in the story's progress entry.

Verdict routing (single source — steps reference this, never re-describe): verifier and the approver (reviewer or critic) return a machine-readable @handoff-out block with a verdict field. Route on the enum, NEVER on prose keyword matching:

  • APPROVE / ACCEPT_WITH_RESERVATIONS → proceed (note reservations in the report).
  • REVISE / ITERATE → mark affected stories passes: false, dispatch executor to fix, re-invoke the same agent; loop to Step 2. Do NOT self-verify.
  • REJECT (3rd consecutive from the approver) → stop REVIEW_BLOCKED.

Read the full file on GitHub · 267 lines

Changes

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.

  1. 8d ago First seen · 267 lines · 100 tokens per session scan A 9050303441b3

Subscribe to this mod's changes

ralph is a skill published in the GitHub repository hg-pyun/claude-code-marketplace (2 stars, last pushed 2mo ago), licensed MIT. It adds 100 tokens to every session and 6,537 once invoked, about $0.0005 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.