Skip to content
Agentmart
Submit a tool

productionos-auto-mode

Idea-to-running-code lifecycle orchestration.

Skill by ShaheerKhawaja

IndexedMIT★ 8
Write a review

Chalk Labs

Need help deploying productionos-auto-mode?

Chalk Labs sets up agents like this inside real teams: connected to your tools, tested on your data, with a human in the loop where it matters.

Book a call

Install

Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

npx agentmarket install skill/shaheerkhawaja-productionos-auto-mode

Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.

Get the weekly diff

The weekly diff: one email a week with new agent tools, notable updates and grade changes, plus security alerts for tools you follow. Double opt-in, one-click unsubscribe.

We use your email only for this newsletter. Privacy

About

Idea-to-running-code lifecycle orchestration. 10-phase pipeline with 5 hard decision gates, wave-based parallelism, and STATE.json resumability. Composes /deep-research, /auto-swarm-nth, /production-upgrade, /security-audit, and /ship into a single end-to-end flow.

Use cases: data, security, research, agent-building

No reviews yet. Installed it? Reviews come from verified installers only. How reviews work

Permissions

What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.

Tools
No tools found
Secrets
None asked for
Install scripts
None found

Network hosts it talks to 1

  • codeload.github.com · found in install command

Files it touches

  • ~/.claude/skills/productionos-auto-mode

What's inside

Skill name
productionos-auto-mode
Description
Idea-to-running-code lifecycle orchestration. 10-phase pipeline with 5 hard decision gates, wave-based parallelism, and STATE.json resumability. Composes /deep-research, /auto-swarm-nth, /production-upgrade, /security-audit, and /ship into a single end-to-end flow.
License
MIT
Instructions
55 lines in SKILL.md · view on GitHub

Files (1)

  • SKILL.md

SKILL.md (first lines)

# productionos-auto-mode


Use this alias when you want the same workflow through a top-level Codex-safe name without the `productionos:` namespace.
## Overview

This is the Codex-native workflow wrapper for [.claude/commands/auto-mode.md](../../.claude/commands/auto-mode.md).

Use it when the user wants this exact ProductionOS workflow, not just the umbrella `productionos` router.

## Source of Truth

1. Read the source command spec at [.claude/commands/auto-mode.md](../../.claude/commands/auto-mode.md).
2. Use [CODEX-PARITY-HANDOFF.md](../../docs/CODEX-PARITY-HANDOFF.md) to confirm runtime support and parity expectations.
3. Preserve the source workflow's guardrails, scope, artifacts, and verification intent.
4. Translate Claude-only slash-command and hook semantics into Codex-native execution instead of copying them literally.

## Codex Behavior

- Summary: Idea-to-running-code lifecycle orchestration. 10-phase pipeline with 5 hard decision gates, wave-based parallelism, and STATE.json resumability. Composes /deep-research, /auto-swarm-nth, /production-upgrade, /security-audit, and /ship into a single end-to-end flow.
- Use the source command as the behavioral spec, then execute the same intent with Codex-native tools and constraints.

## Inputs

- `idea` — The idea to build (text description, file path, or URL) Required.
- `depth` — Pipeline depth: quick | standard | deep | exhaustive (default: deep) Default: `deep` Optional.
- `resume` — Resume from last checkpoint — reads STATE.json (default: false) Default: `false` Optional.
- `output_dir` — Where to create the project (default: current working directory) Optional.

## Execution Outline

1. Preamble

## Agents And Assets

- Agents: `adversarial-reviewer`, `api-contract-validator`, `architecture-designer`, `business-logic-validator`, `code-reviewer`, `comparative-analyzer`, `context-retriever`, `database-auditor`, `debate-tribunal`, `decision-loop`, `deep-researcher`, `density-summarizer`, `dependency-scanner`, `discuss-phase`, `dynamic-planner`, `ecosystem-scanner`, `frontend-designer`, `gap-analyzer`, `gitops`, `intake-interviewer`, `llm-judge`, `naming-enforcer`, `performance-profiler`, `prd-generator`, `refactoring-agent`, `requirements-tracer`, `research-pipeline`, `scaffold-generator`, `security-hardener`, `swarm-orchestrator`, `test-architect`, `ux-auditor`, `verification-gate`
- Templates: `INVOCATION-PROTOCOL.md`, `PREAMBLE.md`
- Artifacts: `.productionos/auto-mode/`, `.productionos/auto-mode/STATE.json`, `.productionos/auto-mode/STATE.json.bak`, `.productionos/auto-mode/{ARTIFACT}.md`

## Workflow

1. Load only the agents, templates, prompts, and docs referenced by the source command.
2. Execute the workflow intent with Codex-native tools.
3. If the source command implies parallel agent work, only delegate when the user explicitly wants that overhead.
4. Verify with the smallest relevant checks before concluding.
5. Summarize what changed, what was verified, and what still needs human approval.

## Guardrails

- Do not claim that Claude-only marketplace, hook, or slash-command behavior runs directly in Codex.
- Keep the scope faithful to the source command rather than broadening into a generic repo audit.
- Prefer concrete outputs and validation over describing the workflow abstractly.
- Preserve the scope and stop conditions from the source command rather than broadening into a generic repo audit.

From ShaheerKhawaja/ProductionOS, MIT.

More from ShaheerKhawaja/ProductionOS

Signals

Stars
8
Forks
1
Open issues
0
Last commit (this folder)
Apr 3, 2026 (7 months ago)

From GitHub (fetched Oct 24, 2026).

Details

License
MIT
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

More from ShaheerKhawaja

Done for you

Rather not set it up yourself?

Chalk Labs scopes, builds and runs agents for your team: the task audit, the eval harness, the integrations and the weekly ops report. Fixed scope, priced before we start.

See how we build AI agents →Read the case studies

Chalk Labs is a two-founder AI and growth studio. We build AI agents, CRMs and MVPs for Web3 and AI companies, and have shipped 50+ product and token launches.

launches shipped
50+
launches shipped
media placements
500+
media placements
founders on every account
2
founders on every account

Press we've placed: Forbes · CoinDesk · Decrypt · Cointelegraph · The Block

Rahil Jain, Co-founder, Chalk Labs. Ex-Goldman Sachs engineer. You talk to the person who builds it.

Get productionos-auto-mode running in your business

Tell us what you want to automate. A founder replies within one working day with a plan, not a pitch deck.

Goes to the Chalk Labs founders, not the newsletter. Privacy

Need help deploying productionos-auto-mode?

CallGet help
Cite this page

productionos-auto-mode skill. Agent Mart. https://agentmart.dev/skills/shaheerkhawaja-productionos-auto-mode (last updated 2026-10-24)