> ## Documentation Index
> Fetch the complete documentation index at: https://docs.stet.sh/llms.txt
> Use this file to discover all available pages before exploring further.

# Choose a workflow

> Match your coding-agent question to a bounded Stet workflow

Each workflow changes one meaningful harness surface at a time, uses a matched
task slice, and returns a Trial Result you can interpret before deciding what to
keep. Choose the question that matches the decision in front of you.

<span id="agents-md-ab" />

## Is my AGENTS.md change helping?

Use a manifest-backed A/B comparison when you have a proposed instruction change
and want the model and other relevant settings held fixed.

**Recommended prompt**

```text wrap theme={null}
Use the Stet skill to A/B test my proposed AGENTS.md change. Keep the model
fixed, plan before launch, and return the canonical Trial Result with its
recommendation, evidence limitations, and next action.
```

**Evidence expectation:** A credible result compares baseline and candidate on
the same retained repository tasks, with the intended instruction lever
isolated and the required tests and graders present. A quick smoke can guide
iteration but is not a rollout decision.

<span id="iterative-instruction-improvement" />

## Improve my AGENTS.md

Use the iterative loop when you want the agent to propose bounded instruction
edits and measure them one at a time. Set a search space and stop rule before
launching; holdout evidence and promotion remain explicit decisions.

**Recommended prompt**

```text wrap theme={null}
Use the Stet skill to improve AGENTS.md within a bounded search space and stop
rule. Test one change at a time and ask before using holdout evidence or
promoting a finalist.
```

**Evidence expectation:** Each iteration should name the single changed lever,
preserve the task and grader contract, and stop when the result is inspect-only,
not improving, or otherwise unable to support the next decision.

<span id="skill-evaluation" />

## Is this skill helping?

Evaluate a skill against the right baseline: an effectively absent skill for a
new skill, or the committed skill for a revision. Keep repository work and
behavior-relevant graders matched.

**Recommended prompt**

```text wrap theme={null}
Use the Stet skill to test whether this repo-managed skill helps. Plan before
launch, use the right baseline, and report promote, hold, or inspect.
```

**Evidence expectation:** The baseline must actually represent skill absence or
the committed version, and the result should include behavior-relevant grader
coverage. Missing coverage turns a comparison into an inspectable diagnostic,
not a keep decision.

<span id="model-reasoning-comparison" />

## Which model or reasoning effort should I use?

Compare models on the same retained tasks, or hold the model fixed while
comparing reasoning settings. Keep the rest of the harness stable enough to
attribute the observed difference.

**Recommended prompt**

```text wrap theme={null}
Use the Stet skill to compare these configurations on the same repository
tasks. First ask whether I want a cheap diagnostic read or a gateable rollout
decision. Keep diagnostic evidence labeled directional; for a gateable choice,
use matched runs and return the canonical Trial Result.
```

**Evidence expectation:** Read correctness, quality dimensions, cost,
uncertainty, validity, and residual risk separately. Do not choose a default from
stale, partial, incomparable, or inspect-only evidence.

## What happens next

Start with [the prompt cookbook](/prompts) for compact copy-paste wording. When
your run finishes, [read the Trial Result](/concepts/trial-result) before making
a rollout decision.