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AI · alternatives · 2026

24 alternatives to Crespo – Tree-sitter AST blueprints instead of raw code for LLMs

Crisp Repos, Sharp AI. Contribute to hrudulmmn/crespo development by creating an account on GitHub.

Crespo is a developer tool that transforms code into tree-sitter abstract syntax tree (AST) blueprints for use with large language models. Rather than feeding raw code to LLMs, it converts source code into structured… Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. Prices are shown for the 1 we have checked on their own sites, 1 of them free or with a free tier.

  1. 1

    This started as a hard requirement for my TUI-based editor application, it ended up going in a few different directions. A suite of tools that help with semantic code entities: https://github.com/odvcencio/gts-suite A next-gen version control system called Got: https://github.com/odvcencio/got I think this has some pretty big potential! I think there's many classes of application (particularly legacy architecture) that can benefit from these kinds of analysis tooling. My next post will be about composing all these together, an exciting project I call…

    Feb 2026 · github.com · its alternatives →

  2. 2
    Croct▲387

    We just launched Croct Templates, a way to drop CMS-powered components into your app with a single command. It's like Shadcn, but for CMS, AB testing and personalization: * Built-in support for A/B testing, content editing, and dynamic logic * Works with existing projects (Next.js, React, etc.) * Supports community libraries via `npm://`, `shadcn-ui://`, etc. Example: ```bash npx croct@latest use shadcn-ui://block/pricing-page ``` Happy to answer any questions!

    2025 · croct.com · its alternatives →

  3. 3

    Built a tool for transforming unstructured data into structured outputs using language models (with 100% adherence). If you're facing problems getting GPT to adhere to a schema (JSON, XML, etc.) or regex, need to bulk process some unstructured data, or generate synthetic data, check it out. We run our own tuned model (you can self-host if you want), so, we're able to have incredibly fine grained control over text generation. Repository: https://github.com/automorphic-ai/trex Playground: https://automorphic.ai/playground

    2023 · automorphic.ai · its alternatives →

  4. 4AI

    I built this software to help users who need to do static code analysis for C/C++ codebase. This can help you to explore the ASTs interactively. It can replace the Clang ast dump completely and also you can search the code/ASTs in a structual way. For example you can search a function which matches specific name or number of paremeters.

    May 2026 · uvic-aurora.github.io · its alternatives →

  5. 5

    AST-based fragmental source code refactoring toolkit for Python - isidentical/refactor

    2021 · github.com · its alternatives →

  6. 6

    Ollama for classical ML models. AOT compiler that turns XGBoost, LightGBM, scikit-learn, CatBoost & ONNX models into native C99 inference code. One command to load, one command to serve. 336x faster than Python inference. - kossisoroyce/timber

    Mar 2026 · github.com · its alternatives →

  7. 7

    `cronexpr` is a library to parse and drive the crontab expression.

    2024 · docs.rs · its alternatives →

  8. 8

    Onboard-CLI—a blazing-fast developer tool I built in Go. It uses AST parsing (Tree-sitter) to map out codebase architecture and automatically blocks spaghetti code and bad dependencies locally before you even commit. I heavily optimized the concurrency, so it can parse 50k+ files in under 10 seconds.

    Jul 2026 · github.com · its alternatives →

  9. 9

    Create beautiful ascii trees. Contribute to spandanb/asciitree development by creating an account on GitHub.

    2019 · github.com · its alternatives →

  10. 10

    Lisp-like-R: A clojure inspired lisp that compiles to R in R - dirkschumacher/llr

    2021 · github.com · its alternatives →

  11. 11

    Next-level syntax for C-like languages :). Contribute to kiselgra/c-mera development by creating an account on GitHub.

    2018 · github.com · its alternatives →

  12. 12

    I've been building a tool that changes how LLM coding agents explore codebases, and I wanted to share it along with some early observations. Typically claude code globs directories, greps for patterns, and reads files with minimal guidance. It works in kind of the same way you'd learn to navigate a city by walking every street. You'll eventually build a mental map, but claude never does - at least not any that persists across different contexts. The Recursive Language Models paper from Zhang, Kraska, and Khattab at MIT CSAIL introduced a cleaner framing. Instead of cramming everything into…

    Feb 2026 · github.com · its alternatives →

  13. 13

    Embedding-based code duplication detector. Contribute to rafal-qa/slopo development by creating an account on GitHub.

    Jul 2026 · github.com · its alternatives →

  14. 14

    A polyglot tool for code searching, linting, rewriting

    2023 · ast-grep.github.io · its alternatives →

  15. 15
    Scapefree tier, from $9.99/mo▲59

    Hey HN, we've been using Claude Code daily for months, and built Scape to fix our biggest pain point: managing multiple worktrees quickly & reducing the mental load of switching between them quickly. What we built: Scape is a macOS menu bar app that sits on top of Claude Code and gives you: - One-click worktrees: click a button, get a new git worktree with a Claude session already working on it. Develop in parallel without leaving your current branch. - Toolkit: per-session actions like "Create PR", "Commit & Push", "Run & Fix Tests." Add your own with bash scripts or prompts. -…

    24d ago · scape.work · its alternatives →

  16. 16

    Seamless GitHub PR management from the command-line - maiao/docs/getting-started.md at main · adevinta/maiao

    2022 · github.com · its alternatives →

  17. 17

    Simon(sfarshid) and I spend a lot of time on GitHub. As data nerds we put together a quick tool to explore your repository’s data. How it works: - Data Loading: We use dlt to pull data (issues, PRs, commits, stars) from GitHub - Semantic Layer: Relta wraps the underlying dataset into a semantic layer so the LLM doesn’t hallucinate. - Text-to-SQL: A text-to-SQL agent transforms your plain-English question into a query using the semantic layer - Generative Charts: assistant-ui dynamically generates a chart based on the SQL query - Refinements: If the semantic layer can’t handle your question,…

    2024 · github.com · its alternatives →

  18. 18

    Directed acyclic graphs are muched discussed in comp-sci, but octopus appears to be the first reusable, turnkey, ready-to-wear, off-the-shelf implementation of a DAG for application development, in any language, that I'm aware of. This is remarkable because DAGs hit a sweet spot in the middle of the three common programming paradigms (OO, event-driven, functional). Let's have a DAG as the top-level structure of our applications. Data-fetching and onChange handlers live in DAG nodes, next to the data they act on. The UI flows out from the DAG with fine-grained reactivity. Our app state is…

    2023 · github.com · its alternatives →

  19. 19DE

    Hey! I wanted to share a tool I've been working on. It's still very early and a work in progress, but I've found it incredibly helpful when working with Claude and OpenAI's models. What it does: I created a Python script that dumps your entire Git repository into a single file. This makes it much easier to use with Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) systems. Key Features: - Respects .gitignore patterns - Generates a tree-like directory structure - Includes file contents for all non-excluded files - Customizable file type filtering Why I find it useful for…

    2024 · its alternatives →

  20. 20

    Hey HN, We’re two developers (co-founders) with a team of 20 who got tired of spending hours reviewing PRs, so we built Infinitcode.ai, an AI-powered code reviewer that: - *Summarizes PRs in plain English*: No more deciphering 1,000-line diff jungles - *Catches more than bugs*: Security holes, performance pitfalls, code smells, even typos (yes, we’ll flag “vurnerabilities” and vulnerabilities) - *Zero onboarding*: Works instantly—no “let me learn your codebase for weeks” nonsense. Why we’re posting: We’re in alpha and need brutal honesty. Roast our tool, mock our UI, or tell us why AI will…

    2025 · infinitcode.ai · its alternatives →

  21. 21

    Hello all, Very excited to share this project with you all! Panoptisch scans your Python file or module to find it's imports (aka dependencies) and recursively does so for all dependencies and sub-dependencies. It then generates a dependency tree in JSON for you to parse and enforce import policies. Supply chain attacks are no joke, and this is one way to transparently analyze your dependencies to see if any malicious imports are taking place. For example, your yaml parser, nor it's sub-dependencies should import socket, or sys. Panoptisch is in early stages, with known limitations (for…

    2022 · github.com · its alternatives →

  22. 22

    Give your LLM agents the power of JetBrains Rider IDE! Supports C# 15 Syntax! - zachsaw/graphify-csharp

    Sep 2026 · github.com · its alternatives →

  23. 23AC

    For the past couple of months, I’ve been building a tool that enables natural language search over large codebases using Tree-Sitter for syntax parsing and Qdrant for vector-based retrieval. https://app.repogram.com ### How It Works - Tree-Sitter is used to parse syntax trees and extract high-quality vector embeddings of code. - These embeddings are stored in Qdrant, enabling fast similarity search across your entire repo. - A combination of re-ranking processes refine search results, producing highly relevant answers to code-related questions. The results have been incredibly…

    2025 · app.repogram.com · its alternatives →

  24. 24

    Hey HN! We’re been building Composo - a platform that helps teams achieve high performance, guarantee accuracy & minimise the cost of LLM applications. Problem we’re solving: LLM applications are non-deterministic, so evaluating whether results are good or bad is highly subjective and often requires domain expertise. Iterating over 1000s of combinations of prompts, models, temperatures, RAG settings (& many other elements) is therefore very manual & time consuming. How we are solving it: Composo links directly to your application (in a simple to set up, but highly powerful way) which enables…

    2024 · composo.ai · its alternatives →

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