acceptance-orchestrator

Use when a coding task should be driven end-to-end from issue intake through implementation, review, deployment, and acceptance verification with minimal human re-intervention.

38 stars

Best use case

acceptance-orchestrator is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Use when a coding task should be driven end-to-end from issue intake through implementation, review, deployment, and acceptance verification with minimal human re-intervention.

Teams using acceptance-orchestrator should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/acceptance-orchestrator/SKILL.md --create-dirs "https://raw.githubusercontent.com/lingxling/awesome-skills-cn/main/antigravity-awesome-skills/plugins/antigravity-awesome-skills-claude/skills/acceptance-orchestrator/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/acceptance-orchestrator/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How acceptance-orchestrator Compares

Feature / Agentacceptance-orchestratorStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Use when a coding task should be driven end-to-end from issue intake through implementation, review, deployment, and acceptance verification with minimal human re-intervention.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# Acceptance Orchestrator

## Overview

Orchestrate coding work as a state machine that ends only when acceptance criteria are verified with evidence or the task is explicitly escalated.

Core rule: **do not optimize for "code changed"; optimize for "DoD proven".**

## When to Use
- The task already has an issue or clear acceptance criteria and should run end-to-end with minimal human re-intervention.
- You need structured handoff across implementation, review, deployment, and final verification.
- You want explicit stop conditions and escalation instead of silent partial completion.

## Required Sub-Skills

- `create-issue-gate`
- `closed-loop-delivery`
- `verification-before-completion`

Optional supporting skills:
- `deploy-dev`
- `pr-watch`
- `pr-review-autopilot`
- `git-ship`

## Inputs

Require these inputs:
- issue id or issue body
- issue status
- acceptance criteria (DoD)
- target environment (`dev` default)

Fixed defaults:
- max iteration rounds = `2`
- PR review polling = `3m -> 6m -> 10m`

## State Machine

- `intake`
- `issue-gated`
- `executing`
- `review-loop`
- `deploy-verify`
- `accepted`
- `escalated`

## Workflow

1. **Intake**
   - Read issue and extract task goal + DoD.

2. **Issue gate**
   - Use `create-issue-gate` logic.
   - If issue is not `ready` or execution gate is not `allowed`, stop immediately.
   - Do not implement anything while issue remains `draft`.

3. **Execute**
   - Hand off to `closed-loop-delivery` for implementation and local verification.

4. **Review loop**
   - If PR feedback is relevant, batch polling windows as:
     - wait `3m`
     - then `6m`
     - then `10m`
   - After the `10m` round, stop waiting and process all visible comments together.

5. **Deploy and runtime verification**
   - If DoD depends on runtime behavior, deploy only to `dev` by default.
   - Verify with real logs/API/Lambda behavior, not assumptions.

6. **Completion gate**
   - Before any claim of completion, require `verification-before-completion`.
   - No success claim without fresh evidence.

## Stop Conditions

Move to `accepted` only when every acceptance criterion has matching evidence.

Move to `escalated` when any of these happen:
- DoD still fails after `2` full rounds
- missing secrets/permissions/external dependency blocks progress
- task needs production action or destructive operation approval
- review instructions conflict and cannot both be satisfied

## Human Gates

Always stop for human confirmation on:
- prod/stage deploys beyond agreed scope
- destructive git/data operations
- billing or security posture changes
- missing user-provided acceptance criteria

## Output Contract

When reporting status, always include:
- `Status`: intake / executing / accepted / escalated
- `Acceptance Criteria`: pass/fail checklist
- `Evidence`: commands, logs, API results, or runtime proof
- `Open Risks`: anything still uncertain
- `Need Human Input`: smallest next decision, if blocked

Do not report "done" unless status is `accepted`.

## Limitations
- Use this skill only when the task clearly matches the scope described above.
- Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
- Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.

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