yolo

Resolves ambiguity with evidence and executes tasks autonomously without asking clarifying questions.

Updated Jun 15, 2026
One-click install
npx skills add https://github.com/nsollazzo/ship-kit --skill yolo-nsollazzo
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: yolo
Source: https://github.com/nsollazzo/ship-kit/tree/main/.agents/skills/yolo
Command: npx skills add https://github.com/nsollazzo/ship-kit --skill yolo-nsollazzo

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? AI agents often stall by bouncing decisions back to the user with clarifying questions, breaking flow on tasks the user wants done hands-off. This Skill replaces question-asking with evidence-based decision-making so work proceeds to a verifiable end state without interruption. ## Core Features & Use Cases - Two activation modes: FULL mode for session-wide hands-off execution ("yolo", "just do it", the --yolo flag) and DECISION mode for resolving a single delegated fork ("your call", "you decide"). - Resolve-don't-ask protocol: Classifies ambiguity as intent, approach, or fact, then answers it by reading code, running commands, checking git history, or searching the web instead of asking. - Multi-agent fan-out: Spawns parallel sub-agents (explorers, researchers, skeptics) for tasks with real breadth, then reconciles their outputs. - Safety floor: Still stops for confirmation on irreversible, outward-facing, or money-spending actions like force-pushes, unrequested PRs, or external messages. - Use Case: A user says "fix the flaky login test, yolo" — the agent investigates the failure, picks the most defensible fix, verifies it by running the test suite, and reports assumptions made, all without a single question. ## Quick Start Tell the agent "yolo, refactor the auth module and make the tests pass" to have it work autonomously to a verified end state.

Frequently Asked Questions about yolo

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I make an AI agent work autonomously without asking questions?▼

Invoke autonomous mode with a trigger phrase like "yolo", "just do it", or "figure it out". The agent then resolves every ambiguity by reading code, running commands, or researching docs, states its assumptions in one line, and proceeds to a verified end state.

What is the difference between FULL mode and DECISION mode?▼

FULL mode runs the entire task hands-off for the rest of the session, triggered by phrases like "yolo" or the --yolo flag. DECISION mode resolves only the decision currently on the table after phrases like "your call", without becoming a session-wide mode or spawning sub-agents.

Does autonomous mode still ask before destructive actions?▼

Yes. A narrow safety floor remains: irreversible, outward-facing, or money-spending actions such as force-pushes, deleting production data, unrequested PRs, or sending external messages still require confirmation. Everything reversible is decided and executed directly.

When does the agent use parallel sub-agents in autonomous mode?▼

Sub-agents are spawned only for tasks with real breadth, uncertainty, or multiple defensible approaches, such as audits, migrations, or broad reviews. Trivial work like typo fixes or single-file reads is handled in a single linear pass.

Can project rules override autonomous mode?▼

Yes. Specific standing constraints like "schema migrations require approval" or "never deploy on Friday" stay in force exactly as written. Only generic propose-versus-decide etiquette is overridden, and any conflict is surfaced rather than silently averaged.