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Foreman Verify

Organization
VisionForge-OU
foreman-verify

Headless self-verification gate a Foreman worker runs before it claims an issue is done. Re-run the real commands, read the actual output, and only then write the FOREMAN-SUMMARY — evidence before claims, always. Used inside a foreman-tdd build session; emits no summary of its own.

Overview

PublisherVisionForge-OU
Repositoryforeman
Skill nameforeman-verify
Stars
444
Forks
117
Bundled files
Instructions only
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by VisionForge-OU on GitHub. Read the source before you install it.

Installation

Install the Foreman Verify AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/VisionForge-OU/foreman/tree/main/src/foreman/skills/foreman-verify
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/VisionForge-OU/foreman.git /tmp/foreman
mkdir -p .claude/skills
cp -r /tmp/foreman/src/foreman/skills/foreman-verify .claude/skills/foreman-verify
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Foreman Verify in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Foreman Verify on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Foreman Verify is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

foreman-verify

(Adapted from obra/superpowers verification-before-completion (MIT) — see NOTICE. Made headless and wired to Foreman's trust boundary: the "claim" you are gating is the foreman-tdd FOREMAN-SUMMARY block and its evidence array, and the verification commands are the project's own, run through the foreman-test wrapper. Foreman re-runs every command itself regardless, so a dishonest claim is not just wrong — it is rejected and counts as a failed attempt.)

You are invoked inside a foreman-tdd build session, right before it would claim the slice is complete. Your job is to make that claim true and evidenced. You run headless and emit no FOREMAN-SUMMARY of your own — you populate the evidence the surrounding foreman-tdd run reports.

The Iron Law

NO COMPLETION CLAIM WITHOUT FRESH VERIFICATION EVIDENCE

If you have not run the verifying command in this session and read its output, you may not claim it passes. "Should pass", "I'm confident", "it worked earlier" are not evidence.

The gate function

For every claim the FOREMAN-SUMMARY will make (tests pass, lint clean, typecheck clean, the issue's acceptance_check passes, the behaviour works):

  1. Identify the exact command that proves it.
  2. Run it fresh and in full — the full foreman-test suite (not just --fast), then lint, then typecheck if configured, then the acceptance_check.
  3. Read the whole output: exit status, failure count, the ERROR lines.
  4. Save the output as an evidence artifact under the run's evidence directory Foreman gave you (the test log at minimum, plus each command's output tail, plus a screenshot for UI work via the configured e2e tooling).
  5. Reconcile the claim with the output. If it does not pass, the honest result is not done — let foreman-tdd keep working or, for a real blocker, escalate. Never round a failure up to a pass.

What counts (and what doesn't)

ClaimRequiresNot sufficient
Tests passfull foreman-test: 0 failures, saved loga --fast subsample, a previous run
Lint / typecheck cleanthe command's own output: 0 errors"the diff looks clean"
Acceptance check passesrunning the issue's acceptance_checkthe unit tests passing
Bug fixedthe original failing symptom now passesthe code changed
Regression test realred→green proven (it failed before the fix)it passes once now

Output

You do not write the summary — you guarantee it can be written honestly. Hand back to foreman-tdd with: the verification commands run, their pass/fail and output tails, and the exact list of evidence artifacts you saved (which becomes the FOREMAN-SUMMARY evidence array). An empty or unbacked evidence array is rejected by Foreman — so if you could not produce real evidence, say so plainly rather than claiming done.

Red flags — stop

  • Any wording implying success ("done", "great", "should be good") before the command has actually run in this session.
  • Saving an empty evidence directory and reporting success anyway.
  • Trusting a sub-agent's or a prior session's "it passed".
  • Verifying a subset and extrapolating to the whole.

Frequently asked questions

What does the Foreman Verify AI skill do?

Headless self-verification gate a Foreman worker runs before it claims an issue is done. Re-run the real commands, read the actual output, and only then write the FOREMAN-SUMMARY — evidence before claims, always. Used inside a foreman-tdd build session; emits no summary of its own.

Why use Foreman Verify on TypingMind?

Because you install it once and use it with any model. Foreman Verify is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Foreman Verify in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/VisionForge-OU/foreman/tree/main/src/foreman/skills/foreman-verify. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Foreman Verify?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Foreman Verify?

As many as you like. As long as a model supports skills, you can use Foreman Verify with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Foreman Verify AI skill free?

It is published on GitHub by VisionForge-OU. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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