Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add commands/thelobbi/claude/creategit clone --depth 1 https://github.com/TheLobbi/claudeWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/commands/thelobbi/claude/create)<a href="https://agentmods.dev/commands/thelobbi/claude/create"><img src="https://agentmods.dev/badge/commands/thelobbi/claude/create.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00022 | $0.02719 |
| Opus 5 | $0.00011 | $0.01359 |
| Sonnet 5 | $0.00004 | $0.00544 |
| Haiku 4.5 | $0.00002 | $0.00272 |
Grade A, and why
lg:create scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured today.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 446 lines — stays where its author put it; the contents beside it link to each section on GitHub.
lg:create - LangGraph Project Creator
Create production-ready LangGraph projects with best practices built-in.
Workflow Steps
-
Validate Input
- Check project name validity
- Verify output path exists
- Validate flag combinations
-
Generate Project Structure
- Create directory structure based on type
- Generate pyproject.toml with dependencies
- Create .env.example file
- Setup configuration files
-
Generate Core Components
- Create state schema
- Generate graph definition
- Implement chosen pattern
- Add memory/checkpoint system
-
Add Integrations
- Setup LLM provider configuration
- Add tool definitions
- Configure streaming (if enabled)
- Setup LangSmith tracing (if enabled)
-
Generate Wrappers
- Create CLI wrapper (if --cli)
- Create MCP server wrapper (if --mcp)
- Add FastAPI server (optional)
-
Create Tests
- Generate test files
- Add example test cases
- Create test fixtures
-
Generate Documentation
- Create README.md
- Add architecture diagram
- Document API/CLI usage
- Add deployment guide
-
Setup Development Environment
- Create virtual environment
- Install dependencies
- Run initial tests
- Verify graph structure
Architecture Patterns
ReAct Pattern
# Reasoning and Acting loop
graph = StateGraph(AgentState)
graph.add_node("agent", agent_node)
graph.add_node("tools", tool_node)
graph.add_edge(START, "agent")
graph.add_conditional_edges("agent", should_continue)
graph.add_edge("tools", "agent")
Supervisor Pattern
# Supervisor delegates to workers
graph = StateGraph(State)
graph.add_node("supervisor", supervisor_node)
graph.add_node("worker_1", worker_1_node)
graph.add_node("worker_2", worker_2_node)
graph.add_conditional_edges("supervisor", route_to_worker)
Swarm Pattern
# Autonomous agents collaborate
graph = StateGraph(SwarmState)
for agent in agents:
graph.add_node(agent.name, agent.node)
graph.add_edge(agent.name, "coordinator")
graph.add_conditional_edges("coordinator", route_next)
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- today First seen · 446 lines · 22 tokens per session scan A ceb18c0ae39d
lg:create is a command published in the GitHub repository TheLobbi/claude (21 stars, last pushed yesterday), licensed MIT. It adds 22 tokens to every session and 2,719 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-05.
Other commands, from other repositories
design-context-extract
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design-import
Scaffolds React components from a Claude Design handoff bundle and stops at files on disk: no stories, no tests, no pull request. Use when handed a claude.ai/design URL or a local bundle file; when that same scaffold should carry on through test generation, browser verification and an opened PR, run /ork:design-ship…
dev
One-command dev loop boot. Spins up portless (named HTTPS subdomain), emulate (stateful API mocks), the project's dev server, and an agent-browser session, all keyed to the current git branch. Use when starting a feature branch, switching worktrees, or returning to a project after a break. Skips silently with install…
design-ship
One-shot pipeline turning a claude.ai/design link into a pull request: scaffold via /ork:design-import, stories and specs via /ork:cover, browser verification via /ork:expect, then open the PR. Use when a design link should come back as a PR with no intermediate steps; if all you need is the components written to…
Hexagonal.Gatekeeper
Your role is to perform a deep, architecture-focused code review on a specific branch. You must validate that all changes strictly follow Hexagonal Architecture (Ports & Adapters) principles and align with the existing codebase patterns.
gen-release-notes
Generate professional release notes following the Keep a Changelog standard.