Refine Flywheel Agent Skill

Stands up the post-launch loop for a shipped AI product — ship behind sign-off → observe tweak-time (how much the customer edits before…

Context cost
11.4k tokensestimated from the bundle, loaded when it triggers
Bundle
13 files · 45.7 kBtext throughout, nothing executable
Licence
Apache-2.0the author’s own terms
Last change
—no release on file
Servers it uses
Noneruns standalone

What it does

Stands up the post-launch loop for a shipped AI product — ship behind sign-off → observe tweak-time (how much the customer edits before accepting) → learn by re-running the WHOLE eval set on every model release → refine by promoting autonomy only as a scored eval result, never by feel. Fires on "what happens after launch", "improve the product", "set up the loop", "a new model dropped, should we upgrade", "can we raise the autonomy / drop the sign-off yet". Returns a filled flywheel cadence doc.

What this skill changes about the agent has not been set out here as a list. Its SKILL.md, shown below, says it in the author’s own words.

data science

The skill itself

A skill is instructions the model reads, so you can see what you are getting: below is the start of its SKILL.md. The front matter loads with every session, the body loads when the skill triggers, and the whole file comes with the install.

SKILL.md14.4 kB · preview
--- name: refine-flywheel type: generator supersedes: none ---
8## What it does
9
10Turns a shipped product into a loop that compounds. It takes a v1 that is live behind a human sign-off gate and stands up four stations: ship (the current autonomy level and its gate), observe (instrument tweak-time — the edit distance between what the system proposed and what the human committed), learn (re-run the entire golden set from eval-first-spec on every model release and on a fixed floor cadence), and refine (move autonomy up or down strictly on the scored eval result). The artefact is the filled template.md: a cadence doc that names what runs, how often, who owns it, and the exact numbers that move autonomy. A loop that raises autonomy on a hunch is not this skill; it is the failure this skill exists to stop.
11
12## The Icarus reframe
13
14The generic post-launch loop is build-measure-learn with an engagement dashboard: usage goes up and to the right, everyone nods, nothing about the product's trustworthiness is known. Icarus replaces the vanity metric with **tweak-time** — a behaviour signal (0.7 on the ladder), read from production traces, that measures how much a customer edits an output before accepting it; tweak-time falling to zero is the product earning the right to act. It replaces "ship it and move on" with a standing regression harness: a new model release is a **regression risk until the eval set re-scores it**, not a free upgrade, so the whole golden set re-runs before any model change reaches production. And it replaces the autonomy promotion-by-confidence with a **ratchet driven by evidence in both directions** — the L0–L4 level from eval-first-spec climbs one rung only when the eval re-run passes that rung's derived failure rates over N real cycles, and drops when a model release regresses them. Tweak-time nominates; the eval confirms; feelings never vote.
15
16## When to use / When NOT
17
18Use it once a product is shipped or in a paid pilot, behind a sign-off gate, WITH an eval set and an autonomy ladder already produced by eval-first-spec. Trigger phrases: "what happens after launch", "improve the product", "set up the loop", "a new model came out — should we upgrade", "can we raise the autonomy level / drop the sign-off yet".
19
20Hard precondition: no eval set, no flywheel. The learn station has nothing to re-run without the 20-case golden set, and the refine station has no ladder to climb without the L0–L4 levels. If those do not exist, stop and route to eval-first-spec. Do not invent an eval set here.
21
22Do not use it for:
23
24| Request | Belongs to |
25|---|---|
26| "Which metrics / what's our North Star / does retention flatten / cost-per-outcome dashboard" | metrics-that-matter (08, sibling). It picks the metric set; this builds the ship→observe→learn→refine cadence and the autonomy ratchet. This skill *reads* tweak-time and cost-per-outcome; that skill decides the wider scorecard. Route metric selection there. |
This is a preview of SKILL.md. Download or install the skill to get the whole thing.
In the file
SKILL.md2,354 words
Files13
LicenceApache-2.0
Why you can read it

Nothing in a skill executes. The client loads the text and the model follows it, so a skill can be audited the way a runbook is — by reading it.

What it costs in context

Skills are not billed by the call. They are paid for in context: every token the instructions occupy is a token your code, your diff and your conversation cannot use. Here is what this one takes and when it takes it.

≈210
always loaded
The name and description, so the model knows the skill exists and when to reach for it.
11,215
on trigger
The instruction body and 12 supporting files, read only when the skill fires.
5.7%
of a 200k window
Ten skills this size would take about 57% of the window before you open a file.
050k100k150k200k context window

11.4k tokens, estimated from the bundle at four bytes to the token, held for the rest of the session once it triggers. Heavy. Teams tend to install this one per project rather than globally, and load it only when the job comes up.

Servers bill, skills cost

A server charges by the month. A skill charges once per session, in context, and then keeps charging it for as long as the session lives.

Before and after

The same question, put to the same model twice: once as it comes, and once with these instructions loaded.

No worked example has been published for this skill yet.

The procedure it runs

The procedure has not been set out here step by step. It is in the body of its SKILL.md: the start of it is shown above, and the whole file comes with the install.

Prose, not code

These steps are written for a model to follow, not executed by a runtime. It can still be told to skip one, and it will say so when it does.

Servers it uses

None. This skill calls no MCP servers at all.

Everything it needs is in the instructions, so it works in a project with nothing connected — the model reads the file and changes how it works with what it can already reach.

Its SKILL.md does not declare which tools it asks the agent for, so what it touches is whatever the instructions themselves ask for — read them before you install it.

What it asks for
Writes filesnot declared
Network accessnot declared

This SKILL.md carries no allowed-tools line, so neither is declared. A skill grants no permissions of its own — it can only ask for tools your client already has.

What it will not do

Every skill is narrow, and the useful ones say where they stop. These are the jobs this one is the wrong tool for.

What this skill is not for has not been published here. Nothing is implied by that: it is a section the author has not filled in.

What is in the bundle

13 files, 45.7 kB on disk. A bundle is text throughout: the instructions the model reads, plus the templates it fills in.

  • SKILL.md14.4 kB
  • template.md5.9 kB
  • examples/sample.md6.0 kB
  • tests/RESULTS.md7.3 kB
  • tests/rubric.json1.1 kB
  • tests/adversarial/01.md1.1 kB
  • tests/adversarial/02.md1.2 kB
  • tests/adversarial/03.md1.3 kB
  • tests/golden/01.md1.8 kB
  • tests/golden/02.md1.4 kB
  • tests/golden/03.md1.6 kB
  • tests/golden/04.md1.2 kB
  • tests/golden/05.md1.4 kB
What is not in it

No dependencies and nothing executable: a skill is text the agent reads, so the bundle is 13 files you can review in full before installing. The Apache-2.0 licence covers the templates and examples as well as the instructions.

Install

Installing copies the bundle into your project. Nothing runs at install time — the files sit on disk until the model reads them.

# Refine Flywheel · 11.4k tokens when loaded · macOS, Linux mkdir -p .claude/skills && t=$(mktemp -d) && curl -fsSL -o "$t/bundle.tar.gz" https://mcprush.com/api/skills/refine-flywheel/bundle.tar.gz && tar -xzf "$t/bundle.tar.gz" -C "$t" && [ -d "$t/refine-flywheel" ] && { [ ! -e .claude/skills/refine-flywheel ] || { mv .claude/skills/refine-flywheel "$t/.previous" && echo "Previous copy moved to $t/.previous"; }; } && mv "$t/refine-flywheel" .claude/skills/ && echo "Installed .claude/skills/refine-flywheel"
On Windows, or any OS with Node 20+
npx mcprush@latest skill add the-utopia-studio/refine-flywheel

Windows PowerShell says 'running scripts is disabled on this system'? Run Set-ExecutionPolicy -Scope CurrentUser RemoteSigned once, or type npx.cmd instead of npx (codex.cmd, gemini.cmd, grok.cmd likewise). PowerShell 7 needs neither. Writes to .claude/skills/refine-flywheel/ in the current project. For every project instead, run mkdir -p ~/.claude/skills && t=$(mktemp -d) && curl -fsSL -o "$t/bundle.tar.gz" https://mcprush.com/api/skills/refine-flywheel/bundle.tar.gz && tar -xzf "$t/bundle.tar.gz" -C "$t" && [ -d "$t/refine-flywheel" ] && { [ ! -e ~/.claude/skills/refine-flywheel ] || { mv ~/.claude/skills/refine-flywheel "$t/.previous" && echo "Previous copy moved to $t/.previous"; }; } && mv "$t/refine-flywheel" ~/.claude/skills/ && echo "Installed ~/.claude/skills/refine-flywheel" (macOS, Linux) — or add --global to the npx line. The curl line replaces .claude/skills/refine-flywheel/ only after the download succeeds, so files left there by another skill of the same name, or by an older release, do not mix in. A copy already there is moved aside, not deleted, and the line prints where.

Which clients pick it up on their own

A skill is a folder of text. Most of these read a skills folder and pick it up without being told; the rest take the same folder another way — an upload in the app, a parameter on an API call — and then choose it by its description just the same.

Claude Code.claude/skills/
Claude DesktopCustomize › Skills
ChatGPTSkills › Create › Upload
Cursor.cursor/skills/
VS Code.github/skills/
Codex CLI.agents/skills/
Gemini CLI.gemini/skills/
Grok Build.grok/skills/
Microsoft CopilotSkills › Upload a skill
PerplexityComputer › Skills › Upload a skill
DeepSeek Harness.dsh/skills/
Zed.agents/skills/
Devin Desktop.devin/skills/
Windsurf (legacy).windsurf/skills/
OpenAI Agents SDKInstructions or sandbox Skills
HTTP / APIa request parameter
This release
Versionnot versioned
Publishedno release date on file
PriceFree
Referencethe-utopia-studio/refine-flywheel

Versions

Its author publishes no version number, so there is nothing here to pin to: what you install is the folder as it stands today. Instructions change more often than APIs do — a skill can be rewritten entirely without anything it depends on moving.

Pinning

Nothing to pin to: this skill carries no version number of its own. What you install is what the folder holds on the day you install it.

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