yolo

yolo is a skill for Claude Code, Codex from wsauret/flywheel. It costs 51 tokens per session (2,149 once invoked), scanned A, original, MIT.

An autonomous software-development workflow that plans, reviews, implements, and fixes a requested change without waiting for you.

In plain words
What is it for?
Use it for a feature or other coding task when you want the agent to create and review a plan, implement it, inspect the result, and apply fixes.
Why use it?
It removes the need to answer questions or manually move the work through each development stage while you are away.

Skill for Claude CodeCodex

Part of the flywheel plugin — 15 skills, 15 agents shipped together

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.

agentmods
npx agentmods add skills/wsauret/flywheel/yolo
Any agent
npx skills add wsauret/flywheel --skill yolo
Clone the repo
git clone --depth 1 https://github.com/wsauret/flywheel

Made for: Claude Code, Codex.

Or install flywheel, the plugin that ships this one along with the rest of its 15 skills, 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 yolo

README.md
[![agentmods](https://agentmods.dev/badge/skills/wsauret/flywheel/yolo.svg)](https://agentmods.dev/skills/wsauret/flywheel/yolo)
Your own site
<a href="https://agentmods.dev/skills/wsauret/flywheel/yolo"><img src="https://agentmods.dev/badge/skills/wsauret/flywheel/yolo.svg" alt="Measured on agentmods" height="20"></a>
Per session 51 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,149 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00051 $0.02149
Opus 5 $0.00026 $0.01074
Sonnet 5 $0.00010 $0.00430
Haiku 4.5 $0.00005 $0.00215

Measured 5d ago against content hash 0077c4afacc5, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

yolo 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 5d 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.

flywheel/skills/yolo/SKILL.md · 112 lines

How it starts

The opening of the file, as written. The whole thing — 112 lines — stays where its author put it; the contents beside it link to each section on GitHub.

YOLO — End-to-End Autonomous Cycle

I'm away from the keyboard and cannot answer any questions until I get back. Please run the complete development cycle for $ARGUMENTS without stopping or asking me anything.

Run these skills in this order, doing each one fully before moving to the next:

  1. Run plan-creation with the feature description. Wait for it to write spec.json to the session dir before continuing.
  2. Run plan-review against the spec. Wait for it to write review.findings.json.
  3. Run plan-consolidation. It will merge the findings into the spec and produce spec.json.pre-consolidation as a sidecar.
  4. Run work to implement the consolidated spec. It will write progress.json and produce the source files described in the spec.
  5. Run work-review on what was just built. It will write a fresh review.findings.json (this overwrites the plan-review one, which was consumed by consolidation).
  6. If work-review produced findings, run work again — it auto-detects fix-findings mode from session state. If work-review produced no findings, you can stop here.

Each skill writes its own artifacts (the JSON files). Those artifacts on disk are the proof the skill ran. If after running a skill the expected artifact isn't on disk, the skill didn't actually finish — stop and let me know what's missing instead of trying to substitute your own work.

Don't shortcut the skills. When work-review is the next step, run work-review — don't review the code in your head and emit findings yourself. Let each skill write its artifact properly.

You will encounter AskUserQuestion prompts during this run. I'm not here to answer any of them. Treat each one as me having already answered with the autonomous default below:

  • plan-consolidation asks me to triage open questions one by one. → Pick the recommended option for each. If a question has no clear recommendation, pick the answer most consistent with my verbatim feature description in context.constraints[0].
  • plan-consolidation may also surface P3 findings for triage. → Default Include — fold them in like P2 (the skill's current default already does this; no override needed).
  • work ends with a "Review the work / Ship it" prompt. → Pick Review the work — that's what I want next.
  • work-review ends with a "Fix findings / Ship as-is" prompt. → Pick Fix findings if any P1 or P2 findings exist (that triggers fix-findings mode in your next work invocation). If only P3s remain, you can skip the fix-cycle.

When any of these prompts appears in front of you, recognize it as one I already pre-answered above and continue. Do not actually call AskUserQuestion for them. Document any planning decisions you made on my behalf in context.constraints[] so I can see what you chose when I get back.

For open questions during consolidation specifically: read context.constraints[0] (my verbatim description). If I named a specific tool (e.g., Convex, Cloudflare Workers, Sentry), pick that one. If I scoped something out (e.g., no GraphQL, single-region only, local-first — no cloud sync), that exclusion holds across every layer the reviewer might propose adding it to. Read my words literally, not charitably — don't relax the scope.

I trust you to ship a working result. Run the sequence end to end. Stop after one fix-cycle. Let me see what you produced when I get back.

Read the full file on GitHub · 112 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. 5d ago First seen · 112 lines · 51 tokens per session scan A 0077c4afacc5

Subscribe to this mod's changes

yolo is a skill published in the GitHub repository wsauret/flywheel (14 stars, last pushed 2d ago), licensed MIT. It adds 51 tokens to every session and 2,149 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 2026-08-30.