MCP Server Builder
anthropics/skills
Guides the design and implementation of Model Context Protocol servers in TypeScript or Python, from tool naming and error messages to evaluation.
아이디어 브레인스토밍 — 멀티 프로바이더 토론과 ICE 평가로 아이디어를 정리합니다. An agent skill from autopus-ai/autopus-adk.
$ npx skills add autopus-ai/autopus-adk --skill auto-idea -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install autopus-ai/autopus-adk auto-idea --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/autopus-ai/autopus-adk.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.omp/skills/auto-idea .claude/skills/auto-idea && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "auto-idea" agent skill from https://github.com/autopus-ai/autopus-adk/tree/main/.omp/skills/auto-idea into .claude/skills/auto-idea/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "auto-idea", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/autopus-ai/autopus-adk/tree/main/.omp/skills/auto-ideaType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add autopus-ai/autopus-adk --skill auto-idea -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install autopus-ai/autopus-adk auto-idea --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/autopus-ai/autopus-adk.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.omp/skills/auto-idea .agents/skills/auto-idea && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "auto-idea" agent skill from https://github.com/autopus-ai/autopus-adk/tree/main/.omp/skills/auto-idea into .agents/skills/auto-idea/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "auto-idea", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add autopus-ai/autopus-adk --skill auto-idea -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install autopus-ai/autopus-adk auto-idea --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/autopus-ai/autopus-adk.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.omp/skills/auto-idea .cursor/skills/auto-idea && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "auto-idea" agent skill from https://github.com/autopus-ai/autopus-adk/tree/main/.omp/skills/auto-idea into .cursor/skills/auto-idea/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "auto-idea", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/autopus-ai/autopus-adk.git --path .omp/skills/auto-idea--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add autopus-ai/autopus-adk --skill auto-idea -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install autopus-ai/autopus-adk auto-idea --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/autopus-ai/autopus-adk.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.omp/skills/auto-idea .gemini/skills/auto-idea && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "auto-idea" agent skill from https://github.com/autopus-ai/autopus-adk/tree/main/.omp/skills/auto-idea into .gemini/skills/auto-idea/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "auto-idea", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install autopus-ai/autopus-adk auto-ideaInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add autopus-ai/autopus-adk --skill auto-idea -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/autopus-ai/autopus-adk.git skills-src && mkdir -p .github/skills && cp -r skills-src/.omp/skills/auto-idea .github/skills/auto-idea && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "auto-idea" agent skill from https://github.com/autopus-ai/autopus-adk/tree/main/.omp/skills/auto-idea into .github/skills/auto-idea/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "auto-idea", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add autopus-ai/autopus-adk --skill auto-idea -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install autopus-ai/autopus-adk auto-idea --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/autopus-ai/autopus-adk.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.omp/skills/auto-idea .opencode/skills/auto-idea && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "auto-idea" agent skill from https://github.com/autopus-ai/autopus-adk/tree/main/.omp/skills/auto-idea into .opencode/skills/auto-idea/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "auto-idea", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
auto-idea아이디어 브레인스토밍 — 멀티 프로바이더 토론과 ICE 평가로 아이디어를 정리합니다. An agent skill from autopus-ai/autopus-adk.
Auto Idea is an agent skill from autopus-ai/autopus-adk. 아이디어 브레인스토밍 — 멀티 프로바이더 토론과 ICE 평가로 아이디어를 정리합니다
Its SKILL.md is about 2.4k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts. Compatibility notes: omp
It sits in Agent Workflows. The repository describes itself as: Autopus-ADK is of the agents, by the agents. for the agents. Multi-model orchestration (consensus/pipeline/debate/fastest). Architecture-as-Code, Lore decision tracking… The licence is MIT.
3 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit fff509f. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
No scripts in the folder and no shell commands in SKILL.md (its code samples are markdown, bash and json).
From the folder's file list and the shell code blocks in SKILL.md.
Hosts in commands or code, which the agent is likely to contact:
github.comFrom URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
omp
From compatibility in the SKILL.md frontmatter.
Auto Idea loads about 2.4k tokens when it runs. Until then it costs about 14 tokens; SKILL.md has 772 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from autopus-ai/autopus-adk at commit fff509f, republished under its MIT licence (© autopus-ai). 772 words, ~2,390 tokens.
.claude/skills/auto-idea/SKILL.md (or your agent's skills folder)./auto idea .../auto-idea ...auto-idea for either entrypoint.프로젝트: autopus-adk | 모드: full
멀티 프로바이더 오케스트라를 활용해 아이디어를 구조화하고 발산 후 BS 파일로 저장합니다.
ICE 스코어링으로 아이디어를 평가하고 상위 N개를 선별합니다.
Opportunity-Solution Tree, 다관점 브레인스토밍, 가정 식별을 포함합니다.
product-discovery, double-diamond, brainstorming 스킬의 문제 정의, 가정 검증, HMW/SCAMPER 흐름을 참고해 사용자의 의도를 먼저 구체화합니다.
{
"schema": "orchestration-contract.v1",
"workflow": "idea",
"semantics": {
"forward_strategy_and_providers": true,
"minimum_rounds": 2,
"fallback_minimum_rounds": 2,
"blind_separate_judge": true,
"fresh_judge_session": true,
"preserve_dissent": true
}
}/auto-idea "아이디어 설명"
/auto-idea "아이디어 설명" --strategy consensus
/auto-idea "아이디어 설명" --auto
/auto-idea "아이디어 설명" --deep-clarify| Flag | Description |
|---|---|
--strategy | 오케스트레이션 전략: debate (기본), consensus, pipeline, fastest |
--providers | 사용할 프로바이더 목록 (기본: 전체) |
--auto | 질문 없이 assumed/deferred rows 기록 후 /auto plan --from-idea BS-{ID} 자동 체이닝 |
--deep-clarify | 기본 1문항 대신 최대 3문항까지 clarification 허용 |
--multi: idea에서는 기본적으로 orchestra가 기본 엔진이므로 사실상 항상 활성 상태로 취급합니다.--auto: 완료 후 plan 체이닝까지 자동 진행합니다.task batch 기반 subagent-first를 기본 원칙으로 사용합니다.idea에서는 메인 세션이 오케스트라 실행과 최종 합성을 담당합니다.task batch 호출을 제한하면, 하네스 기본값과 제약을 명시적으로 알린 뒤 사용자에게 서브에이전트 진행 여부 또는 단일 세션 진행을 확인받습니다.입력에서 아이디어 설명과 플래그를 추출합니다.
오케스트라를 호출하기 전에 사용자의 의도를 먼저 선명하게 만듭니다.
참고 스킬:
product-discovery: Outcome, Opportunity, Assumption, Experiment 구조double-diamond: Problem Statement와 Discover/Define 수렴brainstorming: HMW, SCAMPER, ICE 발산/수렴Clarification gate:
Clarification Ledger rows are exactly goal, scope_boundary, constraints, done_evidence, brownfield_impact in that order.Field, Status, Source, Confidence, Decision / Assumption, If Wrong, Plan Handoff.1-10; expected gain is impact_weight * (1 - confidence/10).goal=8, scope_boundary=8, constraints=5, done_evidence=9, brownfield_impact=6.done_evidence has confidence 2 and impact weight 9, expected gain is 9 * (1 - 2/10) = 7.20, so it is selected before lower-gain rows.6 이하와 non-empty If Wrong이 필요합니다.--deep-clarify는 총 3문항까지 허용합니다.Current understanding, Blocked decision, Recommended answer, Question 네 블록을 사용합니다.ask the user directly이 있으면 반드시 사용합니다. Codex App Server client는 같은 질문 contract를 tool/requestUserInput으로 매핑합니다. Codex 질문 tool이 없을 때만 같은 네 블록을 포함한 짧은 plain-text 질문으로 묻습니다. BS 파일 또는 handoff notes에 question_transport, question_count, unresolved fields를 기록합니다.--auto는 질문 0개, orchestra 계속 진행, unresolved rows를 assumed 또는 deferred로 기록합니다.Question 블록에 둡니다.--auto에서는 질문 없이 ## Visual Brief와 관련 ledger row에 wireframe intent: assumed 또는 wireframe intent: deferred를 남깁니다.https://github.com/devbrother2024/skills, commit 8b4233816f6710271bf8523ffdc107a8e6bf00e1, source path deep-interview/SKILL.md, license MIT, source SHA-256 25d77112663b9c19251a5ef32295216a864b17a74de8712def9fc88f936552c2. Upstream text is not executed, vendored, or treated as trusted instructions; do not require installing devbrother2024/skills.answered → requirements/scope/acceptance seeds, assumed → risks/acceptance assumptions/validation experiments/reviewer focus, deferred → research/open questions unless they block the Outcome Lock, scope_boundary → explicit non-goals.## Outcome Lock for the one primary SPEC that closes the user-visible result, and ## Evolution Ideas for optional improvements that must not auto-create follow-up or sibling SPECs.Intent Brief를 만든 뒤에만 Step 3으로 진행합니다:
## Intent Brief
- Problem: {증상이 아니라 해결할 핵심 문제}
- Target users: {사용자/운영자/이해관계자}
- Desired outcome: {바뀌어야 하는 행동 또는 운영 결과}
- Success signal: {측정 가능한 신호 또는 확인 방법}
- Constraints: {기술/일정/운영/비즈니스 제약}
- Scope boundary: {이번에 하지 않을 것}
- Outcome lock: {primary SPEC가 반드시 닫아야 하는 사용자 가시 결과}
- Completion evidence: {sync에서 완료 판정에 쓸 증거}
- Open assumptions: {확인되지 않은 가정과 confidence}
- Evolution candidates: {선택 개선 후보, 필수 후속 작업 아님}
- Debate focus: {토론자가 반드시 검증할 질문 2-4개}Clarification Ledger도 Step 3 입력에 포함합니다:
## Clarification Ledger
| Field | Status | Source | Confidence | Decision / Assumption | If Wrong | Plan Handoff |
|---|---|---|---:|---|---|---|
| goal | answered/assumed/deferred | user/project-doc/code/inferred/none | 1-10 | ... | ... | requirement seed |
| scope_boundary | answered/assumed/deferred | ... | 1-10 | ... | ... | explicit non-goal |
| constraints | answered/assumed/deferred | ... | 1-10 | ... | ... | risk or constraint seed |
| done_evidence | answered/assumed/deferred | ... | 1-10 | ... | ... | acceptance seed |
| brownfield_impact | answered/assumed/deferred | ... | 1-10 | ... | ... | reviewer focus |## Question Audit
- question_transport: ask the user directly | plain_text | none
- question_count: 0-3
- unresolved_fields: [...]Visual Brief도 Step 3 입력과 사용자 설명에 포함합니다:
## Visual Brief
- Diagram type: flowchart | wireframe | sequence | data-flow | command-flow
```mermaid
flowchart TD
A[Current state] --> B[Proposed change]
B --> C[Outcome Lock]
```
```text
[Low-fi wireframe or flow sketch]
- UI가 있으면 화면/상태/행동을 배치합니다.
- UX-related이면 사용자 의도 확인을 위해 wireframe을 먼저 보여주고 confirm or adjust 를 요청합니다.
- --auto이면 wireframe intent: assumed/deferred 를 표시합니다.
- UI가 없으면 sequence/data-flow/command-flow를 사용합니다.
```Visual Brief는 설명 보조 자료입니다. Outcome Lock, mandatory requirements, acceptance seeds에 연결된 항목만 필수 범위로 취급합니다.
Intent Brief의 Problem은 가능하면 double-diamond 형식으로 씁니다:
[사용자]는 [맥락]에서 [목표]를 달성하려 하지만 [장애물] 때문에 어렵다.
Opportunity-Solution Tree (기존 제품 개선 시):
Assumption Identification (4축):
PM/Designer/Engineer 3가지 관점에서 다각적 발산을 유도합니다.
Step 2의 Intent Brief를 {structured idea}에 포함하고, 토론자들이 솔루션을 내기 전에 문제 정의와 미확인 가정을 먼저 검증하도록 지시합니다.
IMPORTANT: 이 단계는 반드시 orchestra CLI 호출을 먼저 시도해야 합니다. Step 4로 건너뛰거나, 먼저 자체 생성 아이디어로 대체하면 안 됩니다.
debate 호출 (기본):
auto orchestra brainstorm "{structured idea}" --strategy debate --providers {providers} --rounds 2 --judge {invoking_provider} --no-detach --format json다른 strategy 호출:
auto orchestra brainstorm "{structured idea}" --strategy {strategy} --providers {providers} --no-detach --format json
```json
{
"i": "Dispatching bounded OMP work",
"context": "Shared goal, constraints, owned-path boundaries, and cross-task contracts.",
"tasks": [
{
"name": "Worker",
"task": "Complete the assigned work and return the required receipt.",
"outputSchema": {
"type": "object",
"additionalProperties": false,
"required": ["owned_paths", "changed_files", "verification", "blockers", "next_required_step"],
"properties": {
"owned_paths": {"type": "array", "items": {"type": "string"}},
"changed_files": {"type": "array", "items": {"type": "string"}},
"verification": {"type": "array", "items": {"type": "string"}},
"blockers": {"type": "array", "items": {"type": "string"}},
"next_required_step": {"type": "string"}
}
},
"schemaMode": "strict"
}
]
}🐙 Workflow: BS-{ID} ● idea → ○ plan → ○ go → ○ sync
출력은 workflow 상태와 함께 Visual Brief의 핵심 플로우차트 또는 wireframe 요지를 짧게 설명합니다.
`--auto` 설정 시 Outcome Lock을 포함해 자동으로 `/auto plan --from-idea BS-{ID}`로 체이닝합니다.
그렇지 않으면 다음 단계로 `/auto plan --from-idea BS-{ID} "feature description"` 를 안내합니다.© autopus-ai, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Just SKILL.md in .omp/skills/auto-idea of autopus-ai/autopus-adk.
Open the folder on GitHubat commit fff509f
Auto Idea next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Auto Idea this skillautopus-ai/autopus-adk | 110 | — | ~2.4k | Automated safety check: Pass | MIT | |
| MCP Server Builderanthropics/skills | 180k | 63 repos | ~2.3k | Automated safety check: Pass | Apache-2.0 | |
| Hook Development for Claude Code Pluginsanthropics/claude-plugins-official | 38k | 10 repos | ~4.1k | Automated safety check: Notes | Apache-2.0 | |
| Using Superpowersfarm-fe/farm | 5.6k | 35 repos | ~1.4k | Automated safety check: Pass | MIT | |
| Executing Plans Inlineobra/superpowers | 297k | 2 repos | ~5.1k | Automated safety check: Pass | MIT | |
| Skill CreatorAzure/azqr | 795 | 89 repos | ~8.2k | Automated safety check: Pass | Apache-2.0 |
anthropics/skills
Guides the design and implementation of Model Context Protocol servers in TypeScript or Python, from tool naming and error messages to evaluation.
anthropics/claude-plugins-official
Explains how to write Claude Code plugin hooks, both prompt-based checks and bash commands, for events such as PreToolUse, Stop and SessionStart.
farm-fe/farm
A skill your agent uses when starting any conversation - establishes how to find and use skills, requiring Skill tool invocation before ANY response including clarifying questions
obra/superpowers
Has the agent carry out an implementation plan itself, task by task in the current session, keeping a ledger, proving each step with a test and ending with one whole-branch review.
Azure/azqr
Create new skills, modify and improve existing skills, and measure skill performance.
anthropics/claude-plugins-official
Explains how to write agents for Claude Code plugins: the markdown file with YAML frontmatter, trigger descriptions, model and color settings, and system prompt design.
autopus-ai/autopus-adk
QAMESH project QA mesh — plan, run, report, and publish deterministic QA evidence
autopus-ai/autopus-adk
프로젝트 컨텍스트 생성 — 코드베이스를 분석하고 ARCHITECTURE.md 및 .autopus/project 문서를 생성합니다
autopus-ai/autopus-adk
문서 동기화 — 구현 이후 SPEC, CHANGELOG, 문서를 반영합니다. An agent skill from autopus-ai/autopus-adk.
autopus-ai/autopus-adk
@AX code annotation workflow skill for agent-driven tag application
autopus-ai/autopus-adk
터미널 환경 자동 감지 브라우저 자동화 스킬 — AI 에이전트가 직접 웹 페이지를 조작하고 검증. An agent skill from autopus-ai/autopus-adk.
autopus-ai/autopus-adk
작은 인터페이스 뒤에 많은 동작을 숨기는 deep module을 설계하기 위한 공용 어휘(module, interface, seam, adapter, depth)와 원칙
Categories
아이디어 브레인스토밍 — 멀티 프로바이더 토론과 ICE 평가로 아이디어를 정리합니다. An agent skill from autopus-ai/autopus-adk. Auto Idea is an agent skill from autopus-ai/autopus-adk.
Auto Idea fits situations like: agent Workflows work in your project.
Run `npx skills add autopus-ai/autopus-adk --skill auto-idea -a claude-code`. Or copy the skill folder (.omp/skills/auto-idea in autopus-ai/autopus-adk) into .claude/skills/auto-idea in your project. Claude Code loads it when a task matches its description.
Run `npx skills add autopus-ai/autopus-adk --skill auto-idea -a codex`. Or copy the skill folder (.omp/skills/auto-idea in autopus-ai/autopus-adk) into .agents/skills/auto-idea in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add autopus-ai/autopus-adk --skill auto-idea -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/auto-idea, .gemini/skills/auto-idea, .github/skills/auto-idea and .opencode/skills/auto-idea in your project.
SKILL.md names no scripts, command-line tools or credentials: Auto Idea is instructions for the agent only. Compatibility (from SKILL.md): omp.
SKILL.md names 1 domain. In commands or code: github.com; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
Auto Idea is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 2.4k tokens (SKILL.md is roughly 9.6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Auto Idea: MCP Server Builder (anthropics/skills, 180k stars), Hook Development for Claude Code Plugins (anthropics/claude-plugins-official, 38k stars), Using Superpowers (farm-fe/farm, 5.6k stars) and Executing Plans Inline (obra/superpowers, 297k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
autopus-ai (a GitHub organization) maintains it in autopus-ai/autopus-adk, which has 110 GitHub stars. The repository holds 11 skills in this directory. The repository was last updated on October 9, 2026.
Source: autopus-ai/autopus-adk on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.