RalphSAFE
Ralph is an autonomous AI agent loop that runs repeatedly until all PRD items are complete.
Overview
Ralph is an autonomous AI agent loop that runs repeatedly until all PRD items are complete.
9ca619ae0987OBSERVED · 2026-10-21What it tells the agent
The instruction file, verbatim from the audited commit — this is the text the model reads, and the surface the audit's instruction layer examines. Quoted here so you can judge it without cloning anything.
---
name: ralph
description: "Convert PRDs to prd.json format for the Ralph autonomous agent system. Use when you have an existing PRD and need to convert it to Ralph's JSON format. Triggers on: convert this prd, turn this into ralph format, create prd.json from this, ralph json."
user-invocable: true
---
# Ralph PRD Converter
Converts existing PRDs to the prd.json format that Ralph uses for autonomous execution.
---
## The Job
Take a PRD (markdown file or text) and convert it to `prd.json` in your ralph directory.
---
## Output Format
```json
{
"project": "[Project Name]",
"branchName": "ralph/[feature-name-kebab-case]",
"description": "[Feature description from PRD title/intro]",
"userStories": [
{
"id": "US-001",
"title": "[Story title]",
"description": "As a [user], I want [feature] so that [benefit]",
"acceptanceCriteria": [
"Criterion 1",
"Criterion 2",
"Typecheck passes"
],
"priority": 1,
"passes": false,
"notes": ""
}
]
}
```
---
## Story Size: The Number One Rule
**Each story must be completable in ONE Ralph iteration (one context window).**
Ralph spawns a fresh Amp instance per iteration with no memory of previous work. If a story is too big, the LLM runs out of context before finishing and produces broken code.
### Right-sized stories:
- Add a database column and migration
- Add a UI component to an existing page
- Update a server action with new logic
- Add a filter dropdown to a list
### Too big (split these):
- "Build the entire dashboard" - Split into: schema, queries, UI components, filters
- "Add authentication" - Split into: schema, middleware, login UI, session handling
- "Refactor the API" - Split into one story per endpoint or pattern
**Rule of thumb:** If you cannot describe the change in 2-3 sentences, it is too big.
---
## Story Ordering: Dependencies First
Stories execute in priority order. Earlier stories must not depend on later ones.
**Correct order:**
1. Schema/database changes (migrations)
2. Server actions / backend logic
3. UI components that use the backend
4. Dashboard/summary views that aggregate data
**Wrong order:**
1. UI component (depends on schema that does not exist yet)
2. Schema change
---
## Acceptance Criteria: Must Be Verifiable
Each criterion must be something Ralph can CHECK, not something vague.
### Good criteria (verifiable):
- "Add `status` column to tasks table with default 'pending'"
- "Filter dropdown has options: All, Active, Completed"
- "Clicking delete shows confirmation dialog"
- "Typecheck passes"
- "Tests pass"
### Bad criteria (vague):
- "Works correctly"
- "User can do X easily"
- "Good UX"
- "Handles edge cases"
### Always include as final criterion:
```
"Typecheck passes"
```
For stories with testable logic, also include:
```
"Tests pass"
```
### For stories that change UI, also include:
```
"Verify in browser using dev-browser skill"
```
Frontend stories are NOT complete until visually verified. Ralph will use the dev-browser skill to navigate to the page, interact with the UI, and confirm changes work.
---
## Conversion Rules
1. **Each user story becomes one JSON entry**
2. **IDs**: Sequential (US-001, US-002, etc.)
3. **Priority**: Based on dependency order, then document order
4. **All stories**: `passes: false` and empty `notes`
5. **branchName**: Derive from feature name, kebab-case, prefixed with `ralph/`
6. **Always add**: "Typecheck passes" to every story's acceptance criteria
---
## Splitting Large PRDs
If a PRD has big features, split them:
**Original:**
> "Add user notification system"
**Split into:**
1. US-001: Add notifications table to database
2. US-002: Create notification service for sending notifications
3. US-003: Add notification bell icon to header
4. US-004: Create notification dropdown panel
5. US-005: Add mark-as-read functionality
6. US-006: Add notification preferences page
Each is one focused change that can be completed and verified independently.
---
## Example
**Input PRD:**
```markdown
# Task Status Feature
Add ability to mark tasks with different statuses.
## Requirements
- Toggle between pending/in-progress/done on task list
- Filter list by status
- Show status badge on each task
- Persist status in database
```
**Output prd.json:**
```json
{
"project": "TaskApp",
"branchName": "ralph/task-status",
"description": "Task Status Feature - Track task progress with status indicators",
"userStories": [
{
"id": "US-001",
"title": "Add status field to tasks table",
"description": "As a developer, I need to store task status in the database.",
"acceptanceCriteria": [
"Add status column: 'pending' | 'in_progress' | 'done' (default 'pending')",
"Generate and run migration successfully",
"Typecheck passes"
],
"priority": 1,
"passes": false,
"notes": ""
},
{
"id": "US-002",
"title": "Display status badge on task cards",
"description": "As a user, I want to see task status at a glance.",
"acceptanceCriteria": [
"Each task card shows colored status badge",
"Badge colors: gray=pending, blue=in_progress, green=done",
"Typecheck passes",
"Verify in browser using dev-browser skill"
],
"priority": 2,
"passes": false,
"notes": ""
},
{
"id": "US-003",
"title": "Add status toggle to task list rows",
"description": "As a user, I want to change task status directly from the list.",
"acceptanceCriteria": [
"Each row has status dropdown or toggle",
"Changing status saves immediately",
"UI updates without page refresh",
"Typecheck passes",
"Verify in browser using dev-browser skill"
],
"priority": 3,
"passes": false,
"notes": ""
},
{
"id": "US-004",
"title": "Filter tasks by status",
"description"Trust audit
SAFEgrade B · trust 89/100 Nothing in the source contradicts what it says it does. Grade A is reserved for packages that have also passed the behavioural sandbox.
| Layer | What it checks | Result |
|---|---|---|
| L0 | Provenance & inventory | PASS |
| L1 | Static analysis of the code | NA |
| L2 | Instruction surface (what it tells the agent) | PASS |
| L3 | Class-specific surface | PASS |
| L4 | Behavioural (sandbox) | SKIPPED |
What the source does
- Filesystem
- none-observed
- Network
- none-observed
- Shell
- none-observed
- Dependencies
- pinned
- Secrets in source
- none-found
Findings (0)
No findings outside the package's declared scope.
Gates applied: no_behavioural_pass.
9ca619ae0987full audit observations/trust-audit/skill/snarktank__ralph.json · Report an issue / request a re-scanAudit history
Every audit this skill has had.
| Date | Source | Verdict | Grade | Score | Change |
|---|---|---|---|---|---|
| 2026-10-21 | 9ca619ae0987 | SAFE | B | 89 | first audit |
Questions
What does the ralph — snarktank/ralph skill do?
Ralph is an autonomous AI agent loop that runs repeatedly until all PRD items are complete.
Is ralph — snarktank/ralph safe to install?
The audit found nothing in the source that contradicts what it says it does, and graded it B (89/100). Grade A is held back for packages that have also passed a sandboxed behavioural run, which is why a clean skill reads B.
What can ralph — snarktank/ralph access on my machine?
The audit observed no filesystem, network or shell use at all in its source.
How current is this page?
The grade is for one exact copy of the source (9ca619ae0987), read on 2026-10-21. The repository is watched, and a new audit runs when it changes — this is the first audit.
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