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A curated map of open-source AI & agent tools — and what actually pairs with what.
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195 repos · 17 topics · curated by ShipWithAI · new: last30days-skill, pdf-inspector, supervision →

The /last30days skill: researches any topic across Reddit, X, YouTube, HN, TikTok and Polymarket in parallel, scores by real engagement, and synthesizes one grounded brief. 50+ agent hosts.
Firecrawl's Rust PDF triage: classifies text-based vs scanned in ~10-50ms, extracts positioned text and clean Markdown without OCR — routing the ~54% of PDFs that never needed a model.

Roboflow's reusable computer-vision toolkit: one Detections API over any model (YOLO, SAM, transformers), 20+ annotators, zone counting, tracking and dataset tools. 48k stars, MIT.

htop for AI coding agents: every Claude Code, Codex and OpenCode session in one TUI — tokens, context-window %, rate limits, child processes, orphan ports. Read-only, no API keys. Rust.
Apple's official Core AI toolkit: recipes exporting Hugging Face models to .aimodel, PyTorch primitives for authoring, Swift runtime for macOS/iOS apps — plus skills for coding agents.
Rust 'software factory' for coding agents: define the SDLC as a graph, agents execute it through verification gates, you intervene only at the stages that matter. Server, runs board, sandboxes.
The 74k-star LLM-native crawler: turns any site into clean, RAG-ready Markdown — adaptive crawling, JS rendering, extraction strategies, Docker deploy. Python, Apache-2.0.

Code intelligence MCP in pure C: tree-sitter knowledge graph over 158 languages, average repo indexed in milliseconds, sub-ms queries, 10x fewer tokens. Single static binary, zero deps.

PM Skills Marketplace: 68 skills and 42 chained workflows in 9 plugins — discovery, strategy, PRDs, launch, growth — encoding Torres/Cagan-style frameworks for Claude Code and Cowork.

A skill that makes your agent code like the laziest senior dev: YAGNI enforced — ~54% less code, ~20% cheaper, ~27% faster on measured Claude Code sessions. Works with 20 agents.
Zilliz's unified memory for coding agents: one Markdown + Milvus store shared across Claude Code, Codex, OpenCode and OpenClaw — hybrid search, plus repeated workflows distilled into skills.

Self-improving loop from the SIA paper: Meta, Target and Feedback agents evolve a task agent's harness AND weights against a benchmark — #1 on MLE-Bench Hard, 14x kernel speedups.

The full LLM pipeline hand-written in plain PyTorch — tokens, transformer, pretraining, then SFT, reward model, PPO, DPO, GRPO. No trl, no peft: read every algorithm, train on one GPU.
AST-based semantic code search for coding agents: pipx install, zero config, local embeddings out of the box — a CLI/skill/MCP that cuts agent context ~70% vs grepping. Built on CocoIndex.
Alibaba's battle-tested AI code-review CLI: deterministic pipelines + LLM agent, line-level comments, tuned rulesets (NPE, XSS, SQLi) — higher precision than general agents at ~1/9 the tokens.

Learning loop for any agent: reflect on failures, distill strategies into a Skillbook, inject them next run — 2x consistency on Tau2, 49% token cuts. LiteLLM-based, 100+ providers.
Pytest for LLM apps: 40+ research-backed metrics — G-Eval, RAG suite, agent task completion, hallucination — as unit tests you run in CI, judged by any LLM including local ones.

Context compression layer for agents: squeezes tool outputs, logs, files and RAG chunks 20-95% before the LLM — reversible, local-first; library, proxy, one-command agent wrap, or MCP.
Self-hosted NotebookLM alternative: multi-modal sources, vector plus full-text search, context-aware chat and multi-speaker podcast generation — 18+ model providers incl. Ollama, full REST API.

Karpathy-style autoresearch on any codebase: /evo:discover instruments the benchmark, /evo:optimize runs tree search with parallel subagents in worktrees. Plugin for Claude Code, Codex & co.

Native Mac app for on-device LLM fine-tuning via mlx-lm-lora: pick a model, choose SFT/LoRA/DPO-family algorithms, watch loss fall live, push to Hugging Face. No cloud, no code.
Sudoless Apple Silicon monitor: SwiftUI dashboard plus menu-bar suite tracking ANE, Media Engine and memory bandwidth Activity Monitor won't show — with DVR-style record & replay.

Agent memory that learns, not just recalls: retain/recall/reflect API over Postgres, SOTA on LongMemEval. Self-host via Docker with UI; Python/TS clients, any LLM provider.
Berkeley's visual RAG: render pages and PDFs to screenshot tiles and retrieve with a VLM embedder — tables, charts and layout survive. pixelshot CLI plus a hosted 8.28M-page Wikipedia index.

Push-to-talk offline dictation: hotkey, speak, text lands in whatever field has focus. Whisper or Parakeet fully on-device; cross-platform Rust/Tauri, built to be forked.
Open-source meta-harness over Claude Code, Codex, Cursor, OpenCode, Hermes, Pi and custom agents: swap harnesses without rewriting, enforce policies and sandboxes, follow sessions from any device.

KV-cache layer for scalable LLM serving: offload and reuse KV across GPU/CPU/disk/remote tiers to cut TTFT and prefill cost. vLLM-first; used by NVIDIA Dynamo and llm-d.

Paste a GitHub URL or drop a local folder → interactive architecture map in the browser: dependency graph, blast radius, health grade, security scan. Single index.html, zero install.
Pure-C, zero-dep MoE runtime that runs GLM-5.2 (744B) on a 25GB-RAM consumer box by streaming experts from disk — VRAM/RAM/NVMe as one tiered hierarchy, never touching precision.

Turns any PDF into a fillable form: FFDNet models detect text, checkbox and signature fields; one CLI command writes the interactive PDF. Paper, dataset and weights all open.
AI-native Envoy-based proxy for agentic apps: agent orchestration via a 4B routing model, smart LLM routing, guardrail filter chains and zero-code OTEL traces. Rust, framework-agnostic.

Local-first agentic runtime with persistent AI rooms and approval-gated memory: every memory write needs your OK; rooms, KB and artifacts are plain files on disk.

Open-source GenBI engine: agents write governed SQL and deploy shareable dashboards over 22+ data sources, grounded in a Git-friendly context layer (MDL semantics, definitions, memory).

Distributed LLM inference in Rust: pool GPUs across machines into one OpenAI-compatible endpoint — local fit first, mesh routing, and stage splits for models too large for any single box.
Open-source AI gateway: call 100+ LLM providers in OpenAI format via a Python SDK or self-hosted proxy — with cost tracking, virtual keys, guardrails, load balancing and logging.

ICLR 2026 memory framework for LLMs/agents: LLMLingua pre-compression, topic segmentation and offline memory updates — leading LoCoMo/LongMemEval results at lower token cost.
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