nonstop-agent
Generates structured autonomous agent harnesses following Anthropic's long-running agent best practices.
Install
mkdir -p .claude/skills/nonstop-agent && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/15426" && unzip -o skill.zip -d .claude/skills/nonstop-agent && rm skill.zipInstalls to .claude/skills/nonstop-agent
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
Creates long-running autonomous agents. Use when the user asks for "롱 러닝 에이전트 만들어줘", "자율 에이전트 생성", "autonomous agent", "long-running agent", "nonstop agent", or "24/7 agent". Collects requirements through AskUserQuestion and generates agent structure following Anthropic best practices.Key capabilities
- →Collect project state information
- →Determine desired agent type
- →Identify preferred programming language for the agent
- →Select tools for the agent to use
- →Set security level for agent operations
- →Describe main functionality for the agent
How it works
The skill collects user requirements through sequential questions, then analyzes existing project details if applicable, and finally generates an agent structure based on Anthropic's best practices.
Inputs & outputs
When to use nonstop-agent
- →Create autonomous coding agents
- →Build long-running research agents
- →Setup repetitive task automation bots
About this skill
Nonstop Agent Generator
Creates autonomous agent harnesses based on Anthropic's long-running agent best practices.
Execution Instructions (For Claude)
When this skill is invoked, you MUST execute the steps below in order.
STEP 1: Requirements Collection (MUST use AskUserQuestion)
Use the AskUserQuestion tool to ask the following questions sequentially.
1.1 First Question Set (Ask at once)
AskUserQuestion call:
questions: [
{
question: "What is the current project state?",
header: "Project State",
options: [
{ label: "New Project", description: "Starting from scratch" },
{ label: "Existing Project", description: "Already has code (will analyze first)" },
{ label: "Partially Complete", description: "Some features already implemented" }
],
multiSelect: false
},
{
question: "What type of agent do you want to create?",
header: "Agent Type",
options: [
{ label: "Coding Agent", description: "Code generation, modification, refactoring" },
{ label: "Research Agent", description: "Information gathering and analysis" },
{ label: "Automation Agent", description: "Repetitive task automation" },
{ label: "Custom", description: "Define your own" }
],
multiSelect: false
},
{
question: "Which language will you use?",
header: "Language",
options: [
{ label: "Python", description: "Claude Agent SDK (Python)" },
{ label: "TypeScript", description: "Claude Agent SDK (TypeScript)" }
],
multiSelect: false
}
]
1.2 Second Question Set
AskUserQuestion call:
questions: [
{
question: "Select the tools the agent will use",
header: "Tool Selection",
options: [
{ label: "File System", description: "Read, Write, Edit, Glob, Grep" },
{ label: "Terminal", description: "Bash command execution" },
{ label: "Web Search", description: "WebSearch, WebFetch" },
{ label: "Browser Automation", description: "Playwright MCP" }
],
multiSelect: true
},
{
question: "Select the security level",
header: "Security Level",
options: [
{ label: "High (Recommended)", description: "Only allowed commands can run" },
{ label: "Medium", description: "Only dangerous commands blocked" },
{ label: "Low", description: "Most commands allowed (for local dev)" }
],
multiSelect: false
}
]
1.3 Third Question (Free Input)
AskUserQuestion call:
questions: [
{
question: "Describe the main functionality the agent should perform",
header: "Target Features",
options: [
{ label: "Enter manually", description: "Provide detailed feature description" }
],
multiSelect: false
}
]
STEP 2: Existing Project Analysis (Conditionally Required)
Important: MUST run if "Existing Project" or "Partially Complete" is selected
Do NOT skip this step. You MUST run tests and understand current state.
2.1 Project Structure Discovery
pwd
ls -la
cat README.md 2>/dev/null || echo "No README.md"
cat CLAUDE.md 2>/dev/null || echo "No CLAUDE.md"
2.2 Dependencies Check
# Python project
cat pyproject.toml 2>/dev/null || cat requirements.txt 2>/dev/null
# Node.js project
cat package.json 2>/dev/null | head -50
2.3 Run Tests (REQUIRED!)
# Python (uv - as per CLAUDE.md rules)
uv run pytest -v 2>&1 | head -100
# Node.js
npm test 2>&1 | head -100
MUST record test results:
- Total test count
- Passed test count
- Failed test list (these become first items in feature_list.json)
2.4 Build/Lint Check
# Python
uv run ruff check . 2>&1 | head -50
uv run mypy . 2>&1 | head -50
# Node.js
npm run build 2>&1 | head -50
npm run lint 2>&1 | head -50
2.5 Record Analysis Results
Create claude-progress.txt file:
## Initial Project Analysis - [Today's Date]
### Project Overview
- Name: [Project Name]
- Type: [Web App/CLI/Library]
- Tech Stack: [Languages, Frameworks]
### Test Status
- Total Tests: X
- Passed: X
- Failed: X
- Coverage: X%
### Failed Tests (Priority Fix Targets)
1. test_xxx: [Failure Reason]
2. test_yyy: [Failure Reason]
### Build/Lint Status
- Build: PASS/FAIL
- Lint Errors: X
- Type Errors: X
### Discovered TODO/FIXME
[TODO list found in code]
### Next Steps
1. Fix failed tests
2. Resolve lint/type errors
3. Process TODO items
STEP 3: Generate Agent Structure
3.1 Create Directory
mkdir -p agent/prompts
3.2 Copy and Substitute Templates
Copy files from this skill's templates/python/ (or templates/typescript/) directory and substitute the following placeholders:
| Placeholder | Substitution |
|---|---|
{{AGENT_DESCRIPTION}} | Target functionality description from STEP 1.3 |
{{MODEL}} | claude-opus-4-5-20251101 (default) |
{{SYSTEM_PROMPT}} | System prompt appropriate for agent type |
{{BUILTIN_TOOLS}} | Selected tool list (e.g., "Read", "Write", "Edit", "Bash") |
{{MCP_TOOLS}} | MCP tool list (Playwright if browser automation selected) |
{{MCP_SERVERS}} | MCP server configuration |
{{EXTRA_COMMANDS}} | Additional allowed bash commands |
3.3 Files to Generate
agent/
├── main.py # Entry point
├── agent.py # Session logic
├── client.py # Claude SDK client
├── progress.py # Progress tracking
├── security.py # Security hooks
├── prompts.py # Prompt loading
├── requirements.txt # Dependencies
└── prompts/
├── app_spec.txt # Application specification
├── initializer_prompt.md # Initialization prompt
├── coding_prompt.md # Coding prompt
└── existing_project_prompt.md # Existing project analysis
STEP 4: feature_list.json Generation Strategy
For Existing Projects (Priority Order)
[
// Priority 1: Failed tests (each as a feature)
{
"id": 1,
"category": "bugfix",
"description": "Fix failing test: test_user_authentication",
"steps": [
"Step 1: Read the failing test code",
"Step 2: Understand what it's testing",
"Step 3: Find and fix the bug",
"Step 4: Run the test to verify"
],
"passes": false
},
// Priority 2: Build/lint errors
{
"id": 2,
"category": "bugfix",
"description": "Fix type error in user_service.py line 45",
"steps": [...],
"passes": false
},
// Priority 3: TODO/FIXME items
{
"id": 3,
"category": "enhancement",
"description": "TODO: Implement password reset flow",
"steps": [...],
"passes": false
},
// Priority 4: New features
{
"id": 4,
"category": "functional",
"description": "User can modify their profile",
"steps": [...],
"passes": false
}
]
For New Projects
Generate feature list based on app_spec.txt
STEP 5: Usage Instructions
After generation, provide the following instructions:
## Agent Generation Complete!
### Authentication Setup (Required)
```bash
# Set Claude Code OAuth token
export CLAUDE_CODE_OAUTH_TOKEN="your-oauth-token"
# Or login via Claude Code CLI
claude login
The SDK authenticates through the bundled CLI.
Running the Agent
New Project:
cd agent/
uv add claude-agent-sdk
uv run python main.py --project-dir ../my_project
Existing Project (Analyze First):
cd agent/
uv add claude-agent-sdk
uv run python main.py --project-dir ../existing_project --analyze-first
Resume Previous Session:
cd agent/
uv run python main.py --project-dir ../my_project --resume
Key Options
--project-dir: Project directory path--max-iterations: Maximum iteration count (default: unlimited)--analyze-first: Existing project analysis mode--resume: Resume previous session (uses saved session_id)--model: Claude model (default: claude-opus-4-5-20251101)
Generated Files
agent/main.py: Main entry pointagent/prompts/: Agent promptsagent/security.py: Allowed command list (modify as needed)
Check Progress
cat feature_list.json | jq '[.[] | select(.passes == true)] | length'
cat claude-progress.txt
---
## Core Principles Summary
1. **2-Agent Pattern**: Initializer (first session) → Coding (subsequent sessions)
2. **Mandatory Existing Project Analysis**: Run tests → Identify failures → Generate feature_list
3. **State Persistence**: git + claude-progress.txt + feature_list.json
4. **Incremental Progress**: One feature at a time
5. **Immutable Rules**: NEVER modify description/steps in feature_list.json
---
## References
- [ARCHITECTURE.md](ARCHITECTURE.md) - Detailed Architecture
- [templates/python/](templates/python/) - Python Templates
- [Anthropic: Effective Harnesses](https://www.anthropic.com/engineering/effective-harnesses-for-long-running-agents)
- [Claude Agent SDK](https://platform.claude.com/docs/en/agent-sdk/overview)
- [Autonomous Coding Demo](https://github.com/anthropics/claude-quickstarts/tree/main/autonomous-coding)
When not to use it
- →When the user does not want to create a long-running autonomous agent
- →When the user wants to perform creative generation tasks
- →When the user wants to modify an existing agent without generating a new structure
Limitations
- →Requires user interaction to answer questions
- →Existing project analysis requires specific commands to be run
- →Generated agent structure follows Anthropic's long-running agent best practices
How it compares
This workflow interactively gathers detailed requirements and generates a structured agent harness, unlike manually configuring an agent from scratch.
Compared to similar skills
nonstop-agent side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| nonstop-agent (this skill) | 0 | 7mo | Review | Beginner |
| autonomous-agent-patterns | 4 | 6mo | Review | Intermediate |
| llama-factory | 15 | 8mo | No flags | Advanced |
| crewai | 4 | 6mo | No flags | Advanced |
Try saying
Example prompts that trigger this skill in your AI assistant.
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