Acceptance Orchestrator logo

Acceptance Orchestrator

CommunityPopular
sickn33
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.

Overview

Publishersickn33
Repositoryagentic-awesome-skills
Skill nameacceptance-orchestrator
Stars
46.5K
Forks
6.8K
Bundled files
Instructions only
LicenseMIT
Links
Skill sourceRepositoryHomepage
  • 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 sickn33 on GitHub. Read the source before you install it.

Installation

Install the Acceptance Orchestrator 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.
  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/sickn33/agentic-awesome-skills.git /tmp/agentic-awesome-skills
mkdir -p .claude/skills
cp -r /tmp/agentic-awesome-skills/plugins/agentic-awesome-skills-claude/skills/acceptance-orchestrator .claude/skills/acceptance-orchestrator
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Acceptance Orchestrator 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 Acceptance Orchestrator 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 Acceptance Orchestrator 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.

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.

Example

User request:

Take this issue and its acceptance criteria through implementation, validation, review, and a final evidence-backed verdict.

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.

Frequently asked questions

What does the Acceptance Orchestrator AI 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.

Why use Acceptance Orchestrator on TypingMind?

Because you install it once and use it with any model. Acceptance Orchestrator 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 Acceptance Orchestrator in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/sickn33/agentic-awesome-skills/tree/main/plugins/agentic-awesome-skills-claude/skills/acceptance-orchestrator. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Acceptance Orchestrator?

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 Acceptance Orchestrator?

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

Is the Acceptance Orchestrator AI skill free?

Yes. It is published on GitHub by sickn33 under the MIT license. 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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