factory-state-machine

factory-state-machine is a skill for Claude Code from ivegamsft/basecoat. It costs 65 tokens per session (257 once invoked), scanned A, original, MIT.

A state-machine guide for defining and checking the stages of an automated work process in `.github/factory-state.json`. It makes each move between stages explicit, including automatic progress, human escalation, completion, and rollback.

In plain words
What is it for?
Use it to model intake, pending, and complete stages; validate transition rules; and set escalation checks for factory or workcell orchestration.
Why use it?
It prevents workflows from guessing hidden steps or mixing automated actions with decisions that need a person. A single, predictable state file also makes the process easier for other tools to read safely.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter.

Good fit Use it to model intake, pending, and complete stages; validate transition rules; and set escalation checks for factory or workcell orchestration.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/ivegamsft/basecoat/factory-state-machine
Install

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.

Any agent
npx skills add ivegamsft/basecoat --skill factory-state-machine
Clone the repo
git clone --depth 1 https://github.com/ivegamsft/basecoat

Made for: Claude Code.

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 factory-state-machine

README.md
[![agentmods](https://agentmods.dev/badge/skills/ivegamsft/basecoat/factory-state-machine/github.svg)](https://agentmods.dev/skills/ivegamsft/basecoat/factory-state-machine)
Your own site
<a href="https://agentmods.dev/skills/ivegamsft/basecoat/factory-state-machine"><img src="https://agentmods.dev/badge/skills/ivegamsft/basecoat/factory-state-machine/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 factory-state-machine

Your own site · 80×15
<a href="https://agentmods.dev/skills/ivegamsft/basecoat/factory-state-machine"><img src="https://agentmods.dev/badge/skills/ivegamsft/basecoat/factory-state-machine.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 65 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 257 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 $0.00065 $0.00257
Opus 5 $0.00032 $0.00129
Sonnet 5 $0.00013 $0.00051
Haiku 4.5 $0.00006 $0.00026

Measured today against content hash 72ab54abf0f9, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

factory-state-machine 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 today.

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.

skills/factory-state-machine/SKILL.md · 36 lines

What it actually says

Factory State Machine Skill

Model and validate factory state transitions for orchestration workflows.

Templates in This Skill

Template Purpose
factory-state-template.json Starter .github/factory-state.json with states, transitions, and escalation rules

Core Rules

  • Keep the state file as the single source of truth.
  • Model each transition explicitly; do not infer hidden hops.
  • Separate automatic transitions from human escalation.
  • Make terminal states and rollback states obvious.
  • Keep state names and conditions deterministic so workflows can read them safely.

Agent Pairing

Use with factory orchestration agents that read .github/factory-state.json and trigger Workcell workflows.

Files

What ships with it

2 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.

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. today First seen · 36 lines · 65 tokens per session scan A 72ab54abf0f9

Subscribe to this mod's changes

factory-state-machine is a skill published in the GitHub repository ivegamsft/basecoat (4 stars, last pushed today), licensed MIT. It adds 65 tokens to every session and 257 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 2026-09-08.

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