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Llama Farm

Official

@llama-farm · United States of America

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20Public Repos
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30Published Skills

Local models, agents, and databases delivered anywhere.

Skills Distribution
DomainDeveloper To...System Architectur.. (40%)Frontend & UI Engi.. (30%)Specification & Li.. (30%)

Agent Skills by Llama Farm

Showing 30 vetted skills indexed across 2 GitHub repositories.

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demo-workflow

Coordinate artifact pipelines to generate product demo videos with timing data.

Official
Advanced
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2

openspec-new-change

Guide users through creating an OpenSpec change with the experimental artifact workflow.

Official
Intermediate
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2

openspec-archive-change

Archive completed OpenSpec changes with delta-spec comparison and metadata preservation.

Official
Advanced
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openspec-ff-change

Generate complete OpenSpec artifact sets with dependency-aware sequencing.

Official
Intermediate
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openspec-verify-change

Verify codebase implementations against delta specifications and change artifacts.

Official
Advanced
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openspec-explore

Facilitates early-stage project brainstorming and need analysis.

Official
Advanced
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openspec-bulk-archive-change

Batch-archive completed changes via the openspec CLI with conflict resolution.

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Advanced
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openspec-onboard

Guide users through a complete OpenSpec workflow cycle in a live codebase.

Official
Intermediate
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openspec-continue-change

Create the next OpenSpec change artifact based on workflow status.

Official
Intermediate
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2

openspec-sync-specs

Merge delta specs into main specs under openspec/specs.

Official
Advanced
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openspec-apply-change

Guide selection, status checks, and task execution for OpenSpec changes.

Official
Advanced
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835

rag-skills

Audit and optimize RAG pipelines with LlamaIndex, ChromaDB, and Celery best practices.

Official
Basic
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835

go-skills

Provides idiomatic Go patterns for CLI development with Cobra, Bubble Tea, and Lipgloss.

Official
Basic
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835

cli-skills

Design Go CLI applications with Cobra, Bubbletea, and Lipgloss patterns.

Official
Intermediate
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835

designer-skills

Provide design patterns and checklists for React UI with TailwindCSS, TanStack Query, and Radix UI.

Official
Advanced
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835

typescript-skills

Enforce strict typing and readonly props in React and Electron TypeScript codebases.

Official
Basic
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835

code-review

Analyze code diffs for security vulnerabilities, anti-patterns, and quality issues.

Official
Advanced
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835

reflect

Analyze user sessions and propose structured improvements to other skills.

Official
Basic
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835

server-skills

Enforce server-side pattern standardization for FastAPI, Celery, and Pydantic.

Official
Intermediate
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835

config-skills

Standardize and validate LlamaFarm configurations using Pydantic v2 and JSONSchema.

Official
Intermediate
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835

python-skills

Standardize Python development across LlamaFarm components with typing, testing, and security checks.

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Advanced
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835

electron-skills

Consolidate Electron architecture patterns for secure desktop app development.

Official
Advanced
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835

temp-files

Create and manage temporary files in the /tmp/claude/{sanitized-cwd} directory.

Official
Basic
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835

commit-push-pr

Stage changes, create conventional commits, push to origin, and open a PR via gh CLI.

Official
Advanced

Frequently Asked Questions About Llama Farm

FAQPage Schema
What specific engineering tasks are enabled by these patterns?

These patterns enable standardized Go development, React 18 UI architecture, and rigorous OpenSpec delta-specification management. They facilitate consistent configuration validation, secure desktop development via Electron, and structured code review processes to ensure high-quality, maintainable service deployments.

Which technical personas benefit most from these standards?

Full-stack engineers, systems architects, and technical leads working in monorepo environments benefit from these standardized patterns. They are designed for developers requiring consistent, type-safe implementations across Go services, React interfaces, and complex specification-driven development cycles.

What are the primary prerequisites for implementing these standards?

Implementation requires a foundational environment supporting Go, TypeScript, and Python 3.10+. Users must have access to standard development environments, including Git for worktree management and local runtime support for FastAPI and PyTorch-based inference services.