by Spielewoy
Autoprompt is a coding-agent skill that cuts failures by 45% on agentic coding tasks.
# Add to your Claude Code skills
git clone https://github.com/Spielewoy/autoprompt-skillGuides for using ai agents skills like autoprompt-skill.
autoprompt-skill is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by Spielewoy. Autoprompt is a coding-agent skill that cuts failures by 45% on agentic coding tasks. It has 57 GitHub stars.
autoprompt-skill's catalog security scan is still queued. You can run an instant dependency and prompt-injection check now with the "Scan for vulnerabilities" button above.
Clone the repository with "git clone https://github.com/Spielewoy/autoprompt-skill" and add it to your Claude Code skills directory (see the Installation section above).
autoprompt-skill is primarily written in JavaScript. It is open-source under Spielewoy on GitHub, so you can review or fork the full source.
Yes. SkillsLLM lists many other AI Agents skills you can browse and compare side by side. Open the AI Agents category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh autoprompt-skill against similar tools.
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⚠️ Third-Party Software Notice
This skill is third-party open-source software developed and hosted independently on GitHub. SkillsLLM is an informational directory and does not control or maintain the underlying repository.
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Review the source code, permissions, dependencies, and configuration before installing or running any third-party skill. Use is at your own risk. To the maximum extent permitted by applicable law, SkillsLLM is not liable for losses arising from third-party software.
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Install · Benchmarks · Invocation · Run controls · Workflow · Agents · Examples · FAQ · License
Use the CLI below, or download an installer from GitHub Releases.
npm install -g autoprompt-skill
autoprompt
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
python, with PyYAML| Status | Coding agent | Audited requirement | Key |
|---|---|---|---|
| Working | Claude Code | 2.1.219+; audited 2.1.233 | claude |
| Working | Codex | Subagent-capable build; audited 0.147.0 | codex |
| Working | OpenCode | 1.18.7+; audited 1.18.18 | opencode |
| Working | Kilo Code | 7.4.22+; audited 7.4.22 | kilo |
| Working | VS Code | 1.133+; audited 1.133.0 with Copilot 0.61.0 | vscode |
| Working | Prime Agent | 0.7.2; audited 0.7.2; native package adapter | prime |
autoprompt doctor --strictautoprompt doctor PROVIDER --strictautoprompt, then choose an installed providerautoprompt uninstallautoprompt uninstall PROVIDERautoprompt helpReplace PROVIDER with a key from the support table, such as claude, codex, or prime.
| Track | Solved | Score | Failed |
|---|---|---|---|
| OpenCode | 60/89 | 67.42% | 29 |
| OpenCode + Autoprompt | 73/89 | 82.02% | 16 |
| Change | +13 solves | +14.61 points | 45% 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 heavily.
Use mode= to set concurrency. Use agents= to route models where the host supports it. Custom model setup
| Control | Claude Code | Codex | OpenCode | Kilo | VS Code | Prime Agent |
|---|---|---|---|---|---|---|
mode= |
✓ | ✓ | ✓ | ✓ | ✓ | ✓ |
Custom agents= routing |
✓ | ✓ | ✕ Not available - inherits active model | ✕ Not available - inherits active model | ✕ Not available - inherits active model | ✕ Not available - inherits selected parent model |
| Goal | Prompt |
|---|---|
| Fix | /autoprompt fix the registration race and add a regression test |
| Build | /autoprompt mode=wide build the booking flow from API to checkout |
| Research | /autoprompt compare job queues against this codebase and recommend one |
| Limit parallel work | /autoprompt mode=custom max_subs=4 migrate every model |
Use $autoprompt instead of /autoprompt in Codex.
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
mode=tokensaver caps active subagents at six. mode=wide opens every ready lane. mode=custom max_subs=N sets your own ceiling. agents controls model routing where the host supports it. Details
Because it changes cost, time, and workflow. Start it explicitly with /autoprompt <goal>, or $autoprompt in Codex.
MIT. Copyright 2026 Spielewoy.
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