okf-studio: Skill for Claude Code

.agents/skills/autopilot/SKILL.md

autopilot is a skill for Claude Code, Codex from saschb2b/okf-studio. It costs 131 tokens per session (2,481 once invoked), scanned A, original, MIT.

An autonomous work mode for a coding agent. It surveys a project, chooses a small low-risk improvement, makes and checks the change, commits it, and repeats until stopped or blocked.

In plain words
What is it for?
It helps with incremental codebase improvements, verification, and focused Git commits when the developer wants the agent to continue without step-by-step direction.
Why use it?
Open-ended maintenance usually requires a person to keep choosing the next task and checking each result. This mode handles that sequence while keeping changes separate and reviewable.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: mentions CLAUDE.md; installed under .agents/ (shared by several agents).

This is saschb2b/okf-studio's own configuration. It tells Claude Code and Codex how to work on okf-studio itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything okf-studio configures →

Reuse

Borrowing it

Nothing to install: this file belongs to saschb2b/okf-studio. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/saschb2b/okf-studio/main/.agents/skills/autopilot/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/saschb2b/okf-studio

Made for: Claude Code, Codex.

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 autopilot

README.md
[![agentmods](https://agentmods.dev/badge/skills/saschb2b/okf-studio/autopilot/github.svg)](https://agentmods.dev/skills/saschb2b/okf-studio/autopilot)
Your own site
<a href="https://agentmods.dev/skills/saschb2b/okf-studio/autopilot"><img src="https://agentmods.dev/badge/skills/saschb2b/okf-studio/autopilot/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for autopilot

Your own site · 80×15
<a href="https://agentmods.dev/skills/saschb2b/okf-studio/autopilot"><img src="https://agentmods.dev/badge/skills/saschb2b/okf-studio/autopilot.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 131 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,481 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 5.1 $0.00131 $0.02481
Opus 5.5 $0.00052 $0.00992
Sonnet 5.5 $0.00026 $0.00496
Haiku 4.5 $0.00013 $0.00248

Measured 3d ago against content hash 3678986d5562, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

autopilot 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 3d 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.

.agents/skills/autopilot/SKILL.md · 109 lines

How it starts

The opening of the file, as written. The whole thing — 109 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Autopilot

The mode

You operate without waiting for direction. You pick the work, do it, prove it works, commit it, and pick the next thing. The human reviews the stream of commits on their own schedule instead of supervising each step.

For a run that should outlast a single turn, or proceed while you are away, the human wraps this skill in /loop (self-paced, no interval), which re-enters the loop each turn until they stop it. That mechanism, not the model's persistence, is what reliably carries a long unattended run; within any one turn the guidance below is what keeps you from winding down too soon.

Two non-negotiables make this safe to leave running:

  1. Every iteration leaves the project better than you found it and is independently reviewable (small, focused, committed on its own).
  2. You never cross an out-of-bounds line (below) without surfacing it first. When you hit one, write it down and move to the next in-bounds thing. A blocked avenue never stops the loop.

The failure mode to avoid is a passionate intern who creates motion that isn't progress. Motion is easy. The discipline is picking work a senior reviewer would thank you for.

The loop

  1. Survey. First iteration, and again whenever your map goes stale. Read the README, CLAUDE.md, recent commits, the test suite, open TODO and FIXME markers. Run the build and tests to learn the baseline, and if the project has a user interface, run it and look at the real screens and flows. You can't improve what you haven't seen.
  2. Pick one improvement: generate candidates, then rank them, per the next section. One concern per iteration.
  3. Scope it small enough to finish and review in a single sitting. If it can't be, it's a parent. Pick the smallest valuable slice and leave the rest as a note.
  4. Do it in the idiom of the surrounding code. Match its conventions, not your preferences.
  5. Verify. Run the tests, build, and lint. For a user-facing change, also run the app and look at the rendered result, including its loading, empty, and error states. A green build never tells you a screen looks right or a flow feels right. Prove the change works with evidence, not "should work."
  6. Commit on its own with a message saying what changed and why. One iteration, one reviewable commit.
  7. Loop. Pick the next thing. Do not ask permission to continue. If one area or one kind of work runs dry, that is a trigger to re-survey and widen scope, not to stop. The whole repo is the field, never just the module you were last in. There is no commit quota and no natural finishing size: thirty small correct commits is a better run than eight, not a tired one. When the high-leverage work is gone, lower the leverage bar and rotate to a different kind of work in a different part of the repo rather than winding down. "Worth doing" means a senior reviewer would thank you, which is a far lower bar than "the single best thing left in the repo."

Read the full file on GitHub · 109 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. 3d ago First seen · 109 lines · 131 tokens per session scan A 3678986d5562

Subscribe to this mod's changes

autopilot is a skill published in the GitHub repository saschb2b/okf-studio (47 stars, last pushed yesterday), licensed MIT. It adds 131 tokens to every session and 2,481 once invoked, about $0.0005 per session on Opus 5.5. 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 2026-10-23.

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