Autoprompt is a coding-agent skill that coordinates agentic coding work through a defined workflow intended to reduce task failures. Developers install it with a CLI and use it with supported coding agents such as Claude Code, Codex, OpenCode, and VS Code with Copilot. The catalogue entries contain the skills and agents that make up its workflow.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add Spielewoy/autoprompt-skill --skill deepseekgit clone --depth 1 https://github.com/Spielewoy/autoprompt-skillWrote 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.
[](https://agentmods.dev/skills/spielewoy/autoprompt-skill/deepseek)<a href="https://agentmods.dev/skills/spielewoy/autoprompt-skill/deepseek"><img src="https://agentmods.dev/badge/skills/spielewoy/autoprompt-skill/deepseek/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.
<a href="https://agentmods.dev/skills/spielewoy/autoprompt-skill/deepseek"><img src="https://agentmods.dev/badge/skills/spielewoy/autoprompt-skill/deepseek.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 14 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00056 | $0.02564 |
| Opus 5 | $0.00028 | $0.01282 |
| Sonnet 5 | $0.00011 | $0.00513 |
| Haiku 4.5 | $0.00006 | $0.00256 |
Grade A, and why
autoprompt 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 10d 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.
Copies of this mod
2 near-identical copies found in the catalogue:
- autoprompt — 88% identical, 15 lines differ
- autoprompt — 86% identical, 16 lines differ
How it starts
The opening of the file, as written. The whole thing — 123 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Autoprompt
Autoprompt is a useful-first orchestration loop. It stores the mission once, produces one independently approved executable roadmap, dispatches implementation-ready lanes directly, and proves the delivered behavior with real tests and fresh review.
1. Start contract
The invocation authorizes the mission. Do not ask the user to restate, narrow, or approve it.
Loading the skill or invoking it without a mission never starts or resumes a run, regardless of leftover artifacts. A bare invocation performs only the section-10 frontier check, reports the result, and stops.
Before spawning, resolve only undefined operator knobs:
- Concurrency:
tokensaver(default, up to six live),wide/billionaire(all ready disjoint work up to the global ceiling), orcustom max_subs=N. - Agent selection:
off/inherit. DeepSeek Harness subagents inherit the runtime model, so effort capability is exactlyinherited-only; never claim a selectable effort.
In an attended session, ask all undefined knobs in one question before repository/tool work. In an unattended supervisor run, do not ask: default to tokensaver and agents=off and record the assumptions. A permission-bypass flag is not unattendedness.
After the chooser, dispatch the L1 scope coordinator ap-scope-coordinator; it dispatches the useful-first roadmap author. There is no separate intake round trip and no mandatory preflight agent.
An invoked mission always enters orchestration: the bounded scope topology is the minimum topology, and the main agent never silently self-triages an invoked mission into direct execution. Skipping or narrowing dispatch is an explicit decision recorded in GATELOG.md with its rationale, never a silent one.
2. Capability fast path
A supervisor may provide a versioned capability attestation bound to provider/runtime, CLI version, permission profile, agent selector, agent-definition hash, casting hash, effort status/source, and exact RUN/READ/WRITE success. Use it only when every binding matches the live launch. Missing, malformed, stale, unknown, or contradictory values are safe misses.
What ships with it
51 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- agent-preset/agent.cordis.yml 95 KB
- agent-preset/preset.yml 95 B
- agents/ap-arbiter.md 2.9 KB
- agents/ap-depth-prober.md 3.4 KB
- agents/ap-execharness-resolver.md 3.5 KB
- agents/ap-feature-coordinator.md 3.6 KB
- agents/ap-framework-generator.md 3.5 KB
- agents/ap-framework-validator.md 3.2 KB
- agents/ap-fresh-verifier.md 2.4 KB
- agents/ap-goal-checker.md 4.4 KB
- agents/ap-implementer.md 4.3 KB
- agents/ap-intake.md 2.2 KB
- agents/ap-janitor.md 2.7 KB
- agents/ap-juror.md 2.7 KB
- agents/ap-manager.md 4.3 KB
- agents/ap-planner.md 2.5 KB
- agents/ap-preflight-probe.md 2.4 KB
- agents/ap-re-anchor.md 2.4 KB
- agents/ap-researcher.md 4.0 KB
- agents/ap-reviewer.md 2.6 KB
- agents/ap-scope-coordinator.md 4.0 KB
- agents/ap-scoper.md 3.7 KB
- agents/ap-scribe.md 2.8 KB
- agents/ap-sweep-coordinator.md 3.0 KB
- agents/ap-sweeper.md 2.4 KB
- agents/ap-synthesizer.md 2.5 KB
- agents/ap-verifier.md 2.6 KB
- frameworks/apply.md 5.0 KB
- frameworks/backend-build.md 5.5 KB
- frameworks/backend-fix.md 8.7 KB
- frameworks/backend-implement.md 5.5 KB
- frameworks/composition.md 4.2 KB
- frameworks/docs.md 4.8 KB
- frameworks/frontend-build.md 5.0 KB
- frameworks/frontend-fix.md 6.1 KB
- frameworks/frontend-implement.md 5.1 KB
- frameworks/frontend-review.md 6.8 KB
- frameworks/generation.md 5.0 KB
- frameworks/plan-design.md 3.5 KB
- frameworks/plan-research.md 4.1 KB
- frameworks/plan-scope.md 4.6 KB
- frameworks/polish.md 5.2 KB
- frameworks/QUICKSTART.md 3.7 KB
- frameworks/README.md 9.1 KB
- frameworks/refactor.md 5.8 KB
- GATES.md 16 KB
- headless.patch.yml 96 KB
- MODES.md 7.8 KB
- PLAYBOOKS.md 7.3 KB
- README.md 651 B
- VERSION 6 B
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.
- 10d ago First seen · 123 lines · 56 tokens per session scan A 021c3f185c62
autoprompt is a skill published in the GitHub repository Spielewoy/autoprompt-skill (1,035 stars, last pushed 2d ago), licensed MIT. It adds 56 tokens to every session and 2,564 once invoked, about $0.0003 per session on Opus 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 2026-08-30.
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