---
created: 2026-06-27 12:17
modified: 2026-06-27 12:17
type: note
tags:
  - ai
  - ai-agents
  - tool
  - tools
aliases: []
---
# [[Tools to try with AI]]


| Repository / Project Name | GitHub Repository URL | Description |
| :--- | :--- | :--- |
| **OpenMontage** | [calesthio/OpenMontage](https://github.com) | Text-to-video AI editor |
| **codebase-memory-mcp** | [DeusData/codebase-memory-mcp](https://github.com) | Agent context memory |
| **timesfm** | [google-research/timesfm](https://github.com) | Time-series forecasting model |
| **Zapier MCP** | [zapier/zapier-mcp](https://github.com) | App integration gateway |
| **peerd** | [notasithlord/peerd](https://github.com) | Local browser agent |
| **FluidVoice** | [altic-dev/FluidVoice](https://github.com) | Local dictation tool |
| **birdclaw** | [steipete/birdclaw](https://github.com) | Clean X reader |
| **worldmonitor** | [koala73/worldmonitor](https://github.com) | Global event dashboard |
| **penpot** | [penpot/penpot](https://github.com) | Open-source Figma alternative |
| **voicebox** | [jamiepine/voicebox](https://github.com) | Local voice cloner |
| **system_prompts_leaks** | [asgeirtj/system_prompts_leaks](https://github.com) | AI prompt repository |
| **Agent-Reach** | [Panniantong/agent-reach](https://github.com) | Social media connector |
| **ai-berkshire** | [xbtlin/ai-berkshire](https://github.com/xbtlin/ai-berkshire) | Turn Claude Code into a value-investing research team. |
| **ponytail** | [DietrichGebert/ponytail](https://github.com/DietrichGebert/ponytail) | Make AI coding agents solve tasks with the simplest code possible. |
| **inbox-zero** | [elie222/inbox-zero](https://github.com/elie222/inbox-zero) | A self-hostable AI email assistant for organizing and drafting replies. |
| **design.md** | [google-labs-code/design.md](https://github.com/google-labs-code/design.md) | Give AI agents a reusable design system so outputs match your brand. |
| **no-mistakes** | [kunchenguid/no-mistakes](https://github.com/kunchenguid/no-mistakes) | Add an AI safety gate before code reaches your team's repo. |
| **ai-website-cloner-template** | [JCodesMore/ai-website-cloner-template](https://github.com/JCodesMore/ai-website-cloner-template) | Rebuild an existing site as a clean modern codebase. |
| **lingbot-map** | [Robbyant/lingbot-map](https://github.com/Robbyant/lingbot-map) | Reconstruct a 3D scene from streaming camera frames. |
| **free-for-dev** | [ripienaar/free-for-dev](https://github.com/ripienaar/free-for-dev) | A huge maintained list of free developer tools and service tiers. |
| **orca** | [stablyai/orca](https://github.com/stablyai/orca) | Run multiple AI coding agents in parallel from one desktop environment. |
| **claude-video** | [bradautomates/claude-video](https://github.com/bradautomates/claude-video) | Give Claude the ability to watch any video. |
| **notebooklm-py** | [teng-lin/notebooklm-py](https://github.com/teng-lin/notebooklm-py) | Unofficial Python API and agentic skill for Google NotebookLM. |
| **obsidian-skills** | [kepano/obsidian-skills](https://github.com/kepano/obsidian-skills) | Agent skills for Obsidian — teach your agent to use Obsidian CLI and open formats. |
| **impeccable** | [pbakaus/impeccable](https://github.com/pbakaus/impeccable) | The design language that makes your AI harness better at design. |
| **pg_durable** | [microsoft.github.io/pg_durable](https://microsoft.github.io/pg_durable) | PostgreSQL crashproof functions. |
| **DuckDB** | [duckdb/duckdb](https://github.com/duckdb/duckdb) | Embedded analytical SQL database for high-performance data processing. |
| **BGS Stack** | [Obsidian note →](obsidian://open?vault=obsidian&file=200%20projects%2F210%20AI%20Resume%2FThe%20Modern%20Web%20Architecture%20Landscape%20Beyond%20the%20React%20Monopoly) | Go + HTMX + SQLite — the premier AI-friendly web architecture. |
| **last30days-skill** | [mvanhorn/last30days-skill](https://github.com/mvanhorn/last30days-skill) | AI agentic search tool for real-time social signals and community consensus. |


### pg_durable

pg_durable is a new open-source PostgreSQL extension that runs durable, crash-proof workflows right inside the database. The queue, worker, retry logic, and crash recovery you'd normally hand-build collapse into a few lines of SQL.

If you've been running Temporal, cron, or a background worker just for durable execution, watch this first.

📺 [pg_durable — Crashproof PostgreSQL workflows](https://www.youtube.com/watch?v=4Lmqvn_yz-c)

### DuckDB

DuckDB is an open-source, embedded analytical database that runs inside your application process — no server needed. It combines the lightweight simplicity of SQLite with the analytical speed of a cloud data warehouse like Snowflake.

**Key capabilities:**
- **Columnar storage** — reads only the columns you query, minimising disk and memory usage.
- **Vectorised execution** — processes data in CPU-cache-sized chunks (2,048 rows at a time) for maximum hardware efficiency.
- **Direct file querying** — queries Parquet, CSV, and JSON files directly on disk or in cloud storage (S3) without importing.
- **Rich integrations** — zero-copy data exchange with Pandas, Arrow, Polars, and R dataframes.
- **Advanced SQL** — Postgres-compatible dialect with window functions, complex joins, and nested data types.

### BGS Stack (Go + HTMX + SQLite)

The BGS Stack is the premier AI-friendly web architecture — a server-driven alternative to React SPAs built with **Go**, **HTMX**, and **SQLite**. It eliminates `node_modules`, build pipelines, and client-side state management, replacing them with a single linear backend loop that LLMs excel at generating.

Why it's optimised for AI coding:
- **Single-loop context** — one Go function reads from SQLite and returns HTML. No fragmented useState/useEffect/API layer to track across paradigms.
- **Deterministic HTML** — LLMs generate clean HTML and server routes far more reliably than complex React component hierarchies.
- **Fewer moving parts** — no Webpack, Vite, or bundle config for an AI agent to break. Bugs stay contained in one Go file or template.

📄 [Full breakdown — The Modern Web Architecture Landscape Beyond the React Monopoly](obsidian://open?vault=obsidian&file=200%20projects%2F210%20AI%20Resume%2FThe%20Modern%20Web%20Architecture%20Landscape%20Beyond%20the%20React%20Monopoly)

### last30days-skill

last30days-skill is an open-source AI agentic search tool for platforms like Claude Code and Cursor. It focuses on real-time social signals and community consensus over the past 30 days, aggregating data from Reddit, X, and YouTube to produce curated research briefs that bypass SEO-optimised content.

🔗 [mvanhorn/last30days-skill](https://github.com/mvanhorn/last30days-skill)

# AI Engineering Tools Overview

## 🛠️ Structured Data & Model Control

### Instructor (567-labs)
*   **What it is:** A library that patches LLM clients (OpenAI, Anthropic, Gemini) to return strict Python data structures.
*   **Why you need it:** Instead of asking an LLM for JSON and hoping it formats it correctly, you define a Pydantic schema. Instructor guarantees the model's output will match that schema perfectly, automatically retrying and feeding errors back to the LLM if validation fails.
*   **URL:** https://useinstructor.com

### Outlines (dottxt-ai)
*   **What it is:** A library that enforces strict structure at the token generation level for local and API-based LLMs.
*   **Why you need it:** Unlike Instructor (which validates data after or during generation), Outlines guides the LLM dynamically. It alters the model's math so it physically cannot choose a token that violates your regex, schema, or choice list, resulting in 100% reliable structure with zero parsing errors.
*   **URL:** https://github.com

---

## 🔌 Universal Integration & Routing

### LiteLLM
*   **What it is:** A lightweight proxy and SDK that acts as a universal translator for over 100 different LLM APIs.
*   **Why you need it:** Every AI provider has a slightly different code structure for API calls. LiteLLM lets you use the standard OpenAI format (`openai.chat.completions.create`) to talk to Anthropic, Bedrock, Cohere, or HuggingFace, while also handling fallbacks, load balancing, and spend tracking.
*   **URL:** https://github.com

---

## 🧠 Programming & Optimizing Prompts

### DSPy (Stanford NLP)
*   **What it is:** A framework that treats prompt engineering like programming rather than manual "prompt hacking."
*   **Why you need it:** Instead of spending hours tweaking strings like "You are an expert...", you write Python modules (e.g., Chain-of-Thought, RAG). DSPy then compiles and automatically optimizes the prompts and few-shot examples based on your evaluation data, similar to how neural networks learn weights.
*   **URL:** https://github.com

---

## 🕸️ Data Scraping & Preparation

### Crawl4AI
*   **What it is:** An open-source web crawler designed specifically to scrape websites and convert them into data optimized for LLMs.
*   **Why you need it:** Standard web scrapers pull raw, messy HTML full of ads and scripts. Crawl4AI extracts the core text, strips the noise, and outputs clean Markdown or structured JSON, making it perfect for feeding live web data into a RAG pipeline.
*   **URL:** https://github.com

### Chonkie
*   **What it is:** A highly optimized, lightweight text-chunking library designed for Retrieval-Augmented Generation (RAG).
*   **Why you need it:** LLMs cannot ingest massive documents all at once; text must be broken down first. Chonkie focuses on speed and accuracy, splitting text intelligently (by tokens, sentences, or semantics) so context is never cut in half mid-sentence before being embedded.
*   **URL:** https://github.com