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autoprompt-skill

Autoprompt is a coding-agent skill that cuts failures by 45% on agentic coding tasks.

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Set up

Skills are installed by placing their folder where your agent loads skills.

Install instructions come from the README

Skills do not use an MCP config. Follow the steps in the README below; one-click install arrives with accounts.

README

synced Oct 17, 2026

Contents

Install · Benchmarks · Invocation · Run controls · Workflow · Agents · Examples · FAQ · License

Install

Use the CLI below, or download an installer from GitHub Releases.

1. Install the CLI

npm install -g https://github.com/Spielewoy/autoprompt-skill/releases/download/v2.1.0/autoprompt-skill-2.1.0.tgz

2. Launch the installer

autoprompt

3. Install

Choose your coding agent, confirm its path, and install. N means enter another path.

For another CLI or IDE, choose Custom coding agent and use the compatibility guide.

git clone https://github.com/Spielewoy/autoprompt-skill
cd autoprompt-skill
npm install -g .
autoprompt

Requirements

  • Node.js 20+
  • Python 3.11+ available as python3 or python, with PyYAML
  • Bash 4.3+ on macOS or Linux
  • Windows native provider commands use the installed provider runtime plus the platform sandbox and owned-process controls; WSL and a hypervisor are not required for native paths
  • Native Windows Codex additionally requires an administrator-run Autoprompt controller and an initialized official Codex Windows sandbox. Setting Codex windows.sandbox="elevated" selects that sandbox mode; it does not elevate the Autoprompt controller.
  • Git only for the GitHub checkout method

Support

StatusCoding agentTested versionKey
WorkingClaude Code2.1.263claude
WorkingCodex0.148.0codex
WorkingOpenCode1.18.29opencode
WorkingKilo Code7.5.15kilo
WorkingVS Code1.136.1vscode
WorkingPrime Agent0.7.2prime
WorkingOh My Pi18.1.14omp
WorkingDeepSeek Harness0.1.2-rc.1deepseek
WorkingReasonix1.30.0reasonix
WorkingHermes Agent0.21.1hermes
WorkingGrok Build1.0.13grok

These versions passed Linux runs. Model and platform availability varies by provider.

Native Windows execution uses AppContainer isolation and Windows Job process ownership, with Node 20 or 24 on x64 or ARM64. Native macOS execution uses the system sandbox and owned-process controls. Windows command tools include the bundled Bash/MSYS/Node runtime; native paths do not require WSL or a VM.

The ten non-Codex providers can run their local capability checks on Linux, Windows, and macOS. All eleven checks must pass for the installed runtime before a mission starts; missing, failed, or skipped checks block activation. Codex uses its separate canonical validation route. On Windows, that route creates a fresh offline account and an own-SID Windows Filtering Platform policy for each activation. Their activation-bound lease is retained for resume. Permanent cleanup removes the account and policy only after owned Jobs drain; uncertain verification or cleanup fails closed and retains recovery records. The Linux version table above does not certify every provider/platform combination. Installer success and doctor --strict are prerequisite checks; local-canary-required means native validation is still pending. See configured Linux runtimes when a native path is unavailable.

See support and audit notes.

Check, update, or remove an installation

  • Check every detected installation: autoprompt doctor --strict
  • Check one provider: autoprompt doctor PROVIDER --strict
  • Update or repair: autoprompt, then choose an installed provider
  • Uninstall interactively: autoprompt uninstall
  • Uninstall one provider: autoprompt uninstall PROVIDER
  • Show every command: autoprompt help

Replace PROVIDER with a key from the support table, such as claude, codex, or prime.

Benchmarks

These are version 1 benchmarks. Version 2 benchmarks will follow.

TrackSolvedScoreFailed
OpenCode60/8967.42%29
OpenCode + Autoprompt73/8982.02%16
Change+13 solves+14.61 points45% fewer

DeepSeek's 82.7% used its own test setup, so it is a reference point, not a comparable third run. Read the setup and evidence boundaries, or request another benchmark.

Timing and token logs were not retained, so these are planning estimates based on user experience reports, not measured benchmark results. The measured result was 29 to 16 failures (45% fewer) in this run, which translates to about 2x fewer mistakes. Note: for very small tasks, this may differ significantly.

Anatomy of an invocation

autoprompt activate PROVIDER --target /absolute/project -- "<goal>"
PartWhat it does
PROVIDERA key from the support table, such as claude, codex, or grok.
--targetThe project to work on. Omit it to use the current directory.
--Separates launcher options from the request.
<goal>The result you want, constraints, and how to check success.
path=Optional auto, direct, light, or roadmap, before the quoted goal. See work paths.
autoprompt activate codex -- path=light "add retries and test the edge cases"

Run controls

The same controls apply to all eleven providers. Custom model setup

ControlWhat it does
--concurrency tokensaverRuns at most six subagents at once.
--concurrency wideStarts ready, independent work up to the host limit.
--concurrency custom --max-subs NSets your own concurrency limit.
configure PROVIDER --agents offUses the provider's configured model.
configure PROVIDER --agents MODELSelects one model. Add --effort LEVEL where supported.
configure PROVIDER --agents auto --model-map FILEChooses from a measured model registry. A comma-separated model list also requires --model-map.

Pass concurrency controls after --, before the quoted goal:

autoprompt activate codex -- --concurrency custom --max-subs 4 "add retries and tests"
autoprompt configure claude --agents provider/model --effort low

How it works

The agents

Examples

GoalPrompt
Fixautoprompt activate claude -- "fix the registration race and add a regression test"
Buildautoprompt activate codex -- --concurrency wide "build the booking flow from API to checkout"
Researchautoprompt activate hermes -- "compare job queues against this codebase and recommend one"
Limit parallel workautoprompt activate grok -- --concurrency custom --max-subs 4 "migrate every model"

Run these commands from your project, or supply --target /absolute/project before --.

FAQ

No. Give it a clear goal, constraints, and success criteria. Autoprompt handles the execution loop, so you do not have to prompt every step. Details

It can scope, implement, test, review, repair, and verify a goal. It stops for choices that change the result, actions that need your authority, or blockers it cannot safely resolve. Details

The layers separate coordination, management, execution, and independent judgment. That separation keeps one agent from planning, approving, and verifying its own work. Details

path=auto selects a route for the task. direct starts focused work, light adds a short plan, and roadmap organizes dependent work before execution. Every path includes independent verification. Details

--concurrency and --max-subs set parallel work limits. configure --agents selects models, and path= selects how work is planned and coordinated. Details

Because it changes cost, time, and workflow. Start it explicitly with autoprompt activate PROVIDER -- "<goal>".

License

MIT. Copyright 2026 Spielewoy.

Community: Contributors, Contributing, Code of Conduct, Security, and Support.

Contributors

johnatag · rollingdice · AincradBot · lunar-me · fatinghenji · c8dhjp4tyv-bit · Alexis-Fiolleau-LaPoste-BGPN · Oscar-Williams

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