ralph-router
- Repo stars 1
- Author updated Live
- Author repo Ralph-Anti-loop-Bundle-Skill
- Domain
- Other
- Compatible agents
-
- Claude Code
- Cursor
- Cline
- Codex
- Windsurf
- Gemini CLI
- +20
- Trust score
- 92 / 100 · audit passed
- Author / version / license
- @00Blacksheep00 · v1.0 · no license declared
- Token usage
- Lean
- Setup complexity
- Plug-and-play
- External API key
- Not required
- Operating systems
- Linux
- Runtime requirements
- No special requirements
- Permissions
-
- Read-only
- Write / modify
- Network behavior
- Local-only
- Install commands
- 26 variants
Profile is derived at build time from SKILL.md and install vectors. Subject to drift from author intent.
Heads up: 未限定 allowed-tools,默认拥有全部工具权限。
---
name: ralph-router
description: > I receive a task. ├─ How many steps do I expect? │ ├─ 1–3 steps / single operation / lookup /…
category: other
runtime: no special runtime
---
# ralph-router output preview
## PART A: Task fit
- Use case: > I receive a task. ├─ How many steps do I expect? │ ├─ 1–3 steps / single operation / lookup / quick edit │ │ └─ → Load ralph-small │ │ Path: /home/ubuntu/.openclaw/skills/ralph-small/SKILL.md runs entirely locally. Works with Claude Code, Cursor, Cline and 23 more..
- Inputs: target material, constraints, expected output, and acceptance criteria.
- Evidence boundary: follow “Decision tree / Automatic escalation rule / After success (self-improvement)” and do not present inference as author intent.
## PART B: Execution result
- **01** The card summarizes the use case; runtime output centers on “> I receive a task. ├─ How many steps do I expect? │ ├─ 1–3 steps / single operation / lookup / quick edit │ │ └─ → Load ralph-small │ │ Path: /home/ubuntu/.openclaw/skills/ralph-small/SKILL.md runs entirely locally. Works with Claude Code, Cursor, Cline and 23 more.”.
- **02** When the source has headings, the agent prioritizes “Decision tree / Automatic escalation rule / After success (self-improvement)” so the result follows the author’s structure.
- **03** Typical output includes task judgment, concrete steps, required commands or file edits, validation, and follow-up options.
- **04** Risk context follows the fingerprint: read files, write/modify files; mostly runs locally; usually needs no extra API key.
## Running Rules
- read files, write/modify files; mostly runs locally; usually needs no extra API key.
- Validate with a small sample before expanding scope.
- Return the result, validation criteria, and next iteration options. The source mentions slash commands such as `/home`; use them first when your agent supports command triggers.
Name target files or source material, expected output, forbidden changes, and whether network or shell access is allowed. Permission fingerprint: read files, write/modify files.
Start with a small task and check whether the result follows “Decision tree / Automatic escalation rule / After success (self-improvement)”. Inspect diffs, logs, previews, or tests before expanding scope.
Confirm the final output includes a concrete result, evidence, and next action. If it stays generic, tighten inputs, boundaries, and acceptance criteria.
---
name: ralph-router
description: > I receive a task. ├─ How many steps do I expect? │ ├─ 1–3 steps / single operation / lookup /…
category: other
source: 00Blacksheep00/Ralph-Anti-loop-Bundle-Skill
---
# ralph-router
## When to use
- > I receive a task. ├─ How many steps do I expect? │ ├─ 1–3 steps / single operation / lookup / quick edit │ │ └─ → Lo…
- Use it when the task has clear inputs, repeatable steps, and validation criteria.
## What to provide
- Target material, scope, expected result, and forbidden changes.
- Whether network, commands, file writes, or external services are allowed.
## Execution rules
- Organize steps around “Decision tree / Automatic escalation rule / After success (self-improvement)” and keep inference separate from source facts.
- read files, write/modify files; mostly runs locally; usually needs no extra API key.
- Validate with a small sample before expanding the task.
## Output requirements
- Return the deliverable, key evidence, validation method, and next action.
- Mark missing information as unknown; do not invent commands, platforms, or dependencies. The author source anchors workflow facts; repository files anchor sources and commands; Fluxly only adds fit, limitations, and quality judgment.
skill "ralph-router" {
input -> user goal + target files + boundaries + acceptance criteria
context -> Decision tree / Automatic escalation rule / After success (self-improvement)
rules -> SKILL.md triggers / order / output contract
runtime -> no special runtime | read files, write/modify files | mostly runs locally
guardrails -> usually needs no extra API key + small-sample validation + diff/log review
output -> copyable result + checklist + next iteration
} Ralph Router — Automatic level selection
Before you act, pick the right level. Never start a task without loading the correct skill.
Decision tree
I receive a task.
│
├─ How many steps do I expect?
│ │
│ ├─ 1–3 steps / single operation / lookup / quick edit
│ │ └─ → Load ralph-small
│ │ Path: /home/ubuntu/.openclaw/skills/ralph-small/SKILL.md
│ │
│ ├─ 4–10 steps / sequential workflow / moderate dependencies
│ │ └─ → Load ralph-medium
│ │ Path: /home/ubuntu/.openclaw/skills/ralph-medium/SKILL.md
│ │
│ └─ 10+ steps / debugging / refactor / architecture / high complexity
│ └─ → Load ralph-huge
│ Path: /home/ubuntu/.openclaw/skills/ralph-huge/SKILL.md
│
├─ Unsure about complexity?
│ └─ → Err on the side of more discipline. Prefer ralph-medium on a simple task
│ over ralph-small on a task that turns out complex.
│
└─ Already using ralph-small or ralph-medium and exhausted attempts?
└─ → Escalate to the next level immediately.
Do not wait. Do not retry the same tier. Escalate.
Automatic escalation rule
ralph-small → 2 failed attempts → ralph-medium
ralph-medium → 3 failed attempts → ralph-huge
ralph-huge → 4 failed attempts → Circuit breaker + wait for user
There is no escalation beyond ralph-huge. After four failed unique attempts, stop, emit the diagnostic, and wait for human input.
After success (self-improvement)
When the task was run under ralph-small, ralph-medium, or ralph-huge and you have verified success (evidence in the same turn):
- Follow the Closure: self-improvement section at the end of whichever Ralph level you used — it links to
self-improvementand.learnings/without blocking the user reply. - Skill path (OpenClaw):
/home/ubuntu/.openclaw/skills/self-improvement/SKILL.md
This is optional but high-value for recurring patterns, non-obvious fixes, and tool/gateway gotchas.
Note for the agent
Never tell the user “I’m using ralph-[level]” — that is internal operations detail. Select, load, act. The user wants outcomes, not narration of your selection process.
Decide Fit First
Design Intent
How To Use It
Boundaries And Review