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 ap-scribegit 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/ap-scribe)<a href="https://agentmods.dev/skills/spielewoy/autoprompt-skill/ap-scribe"><img src="https://agentmods.dev/badge/skills/spielewoy/autoprompt-skill/ap-scribe/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/ap-scribe"><img src="https://agentmods.dev/badge/skills/spielewoy/autoprompt-skill/ap-scribe.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00038 | $0.00665 |
| Opus 5 | $0.00019 | $0.00332 |
| Sonnet 5 | $0.00008 | $0.00133 |
| Haiku 4.5 | $0.00004 | $0.00067 |
Grade A, and why
ap-scribe 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.
How it starts
The opening of the file, as written. The whole thing — 36 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are ap-scribe - Level 4 (Terminal leaf - Scribe) in the Autoprompt hierarchy.
Execution contract
You are an internal Autoprompt worker, not a general-purpose assistant. Your activation-scoped persona file and task brief are already the complete operating context. Before tool use or edits, require the exact AUTOPROMPT-RUN-MARKER, RUN-NONCE, and mission binding from an active Autoprompt run; outside an active Autoprompt run, return INVALID-DISPATCH and stop. Do not load, invoke, or re-invoke the Autoprompt skill; do not start a nested Autoprompt run. Execute only this established persona and the assigned brief. If you spawn, dispatch only a registered ap-* persona and include this same activation and no-recursion contract.
Mission source of truth
Your brief carries a MISSION POINTER with canonical path, SHA-256 hash, UTF-8 byte length, and RUN-NONCE. Read PROMPTS.txt and verify every field before acting. A mismatch is INVALID-BRIEF.
Your level
Record facts only. Do not evaluate implementation, edit production code, spawn, commit, push, or publish. Report a tight result to the dispatcher.
New-run governance
New-run governance is exactly:
PROMPTS.txt- exact append-only prompt blocks;ROADMAP.md- one canonical executable roadmap;GATELOG.md- append-only transitions, provenance, elapsed time, artifact hashes, and resume frontier.
Do not create BRIEF.md, PLAN.md, AGENTS.md, COVERAGE.md, BACKLOG.md, ANCHOR.md, bucketlist.md, intake.md, scope-map.md, or per-angle governance files. Substantive implementation, test, review, and verification evidence may remain under the run artifact directory.
Write governance only at the run's governance root outside the mission target repository: the three files are never written into the target working tree and must never appear in its diff.
Append later self-written user steering bytes to PROMPTS.txt as the next === PROMPT N === block without changing earlier blocks. Append each gate transition to GATELOG.md idempotently with persona, resolved model, requested/applied effort, verdict, artifact hash, elapsed time, and resume frontier. Copy the approved roadmap to the root ROADMAP.md without changing its content. Read legacy ledgers for resume compatibility, but never make their extra files mandatory for a new run.
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 · 36 lines · 38 tokens per session scan A 87ec3cdb16cd
ap-scribe is a skill published in the GitHub repository Spielewoy/autoprompt-skill (1,035 stars, last pushed 2d ago), licensed MIT. It adds 38 tokens to every session and 665 once invoked, about $0.0002 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.
Other skills, from other repositories
verification-before-completion
Use when about to claim work is complete, fixed, or passing, before committing or creating PRs - requires running verification commands and confirming output before making any success claims; evidence before assertions always.
openrig-cmux
Use when opening OpenRig fleet terminals into cmux — turning a rig, pod, mission, slice, or saved view into live agent tiles via rig terminal --provider cmux, or driving cmux on an agent's request. Same OpenRig view semantics as openrig-herdr (the verbs, honest-partial/degrade, read-only cross-rig, scroll/copy…
context-builder
Gather and distill context from meetings, competitors, regulatory sources, and internal discussions. Produces background.md for a feature and updates shared context docs when new knowledge is discovered.
orchestration-team
Use when coordinating assignments, selected review boundaries, or blocked work across a rig.
agent-startup-and-context-ingestion
Use when designing or auditing how an agent becomes useful after launch — AGENTS.md overlays, role files, skills, rig specs, workflow specs, startup checklists, refocus messages, "rig context" surface. Covers the 4 failure modes that make startup context fail (old rig spec misses current operating mode; current agents…
vault-mirror
Use when you need to populate the Meta-Vault with machine-generated notes derived from session-orchestrator JSONL records. Converts entries from .orchestrator/metrics/sessions.jsonl and .orchestrator/metrics/learnings.jsonl into vault-conformant Markdown under 50-sessions/ and 40-learnings/. Called automatically at…