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nexpath

hi0001234d · hi0001234d/nexpath

Giúp tác nhân lập trình AI của bạn phát hiện các bài kiểm tra, kiểm tra an toàn và vấn đề bảo trì còn thiếu bằng cách cải thiện prompt và cung cấp hướng dẫn.

Quy trình làm việc lập trình AI ưu tiên cục bộ dành cho vibe coder, indie hacker, nhà sáng lập kỹ thuật và quản lý sản phẩm — phát hiện các bài kiểm tra và kiểm tra an toàn bị thiếu trên Claude Code, Cursor, Windsurf, Replit, Lovable và Bolt.new.

355 sao16Giấy phép: Apache-2.0Cập nhật 17 ngày trước0 lượt mở

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Bạn có thể làm gì với nó

  • Đảm bảo mã do AI tạo ra bao gồm các bài kiểm tra và kiểm tra an toàn phù hợp trước khi triển khai.
  • Cải thiện khả năng bảo trì mã do tác nhân AI tạo ra bằng cách phát hiện sớm các vấn đề tiềm ẩn.
  • Hướng dẫn các tác nhân AI tuân theo các quy trình phát triển trưởng thành, giảm rủi ro thay đổi chưa được xác minh.

Kiểm tra an toàn

An toàn

Không thấy dấu hiệu rủi ro trong các file đã quét.

Quét tự động các file trong repo. Luôn xem lại code trước khi chạy.

Trích từ README

Nexpath CLI — Build Fast. Ship with Confidence.

A local-first behaviour guidance layer that helps builders catch missing checks before AI-generated work becomes shipped risk.

AI coding agents make it easy to move fast. Nexpath helps reduce the chance that speed quietly becomes an unverified bug, an unsafe change, an unmaintainable codebase, or hours of manual review later.

Prompt Enhancement — A Practical Twist

Within Nexpath's broader behaviour-guidance vision, Prompt Enhancement is the first feature we're introducing as a practical twist: it saves vibe coders from writing every prompt detail by hand while preserving their original intent. When a task needs more rigour, it can suggest missing development practices, verification, or confirmation steps — encouraging users to give a mature development flow the time it needs to finish.

Demo: Prompt Enhancement in action, on YouTube


Why Nexpath Exists

  • AI can introduce a bug without making the risk obvious.
  • Fast generation can leave a codebase harder to maintain after every change.
  • Security, rollback, regression, and acceptance checks are easy to miss while momentum is high.
  • Reviewing every AI-generated decision manually can cost more time than the generation saved.

Nexpath reduces these risks by noticing what the current workflow is missing and bringing the relevant check into the work at the right moment. It does not replace developer judgement or promise bug-free code; it helps make that judgement faster, more structured, and harder to skip.


A Workflow, Not Another Tool

  1. Build with your AI coding agent — Work in the tools and flow you already use.
  2. Review with Nexpath — Let the Prompt Quality Layer surface missing verification, safety, scope, or maintenance steps while the context is still fresh.
  3. Ship confidently — Move forward after the important checks are visible, reviewed, and included in the task.

Nexpath is one focused step inside a better shipping workflow — not a new place where development has to happen.

Built during AI Hackfest 2026 by MLH.


The Prompt Quality Layer — How It Works

  1. Understand — Nexpath reviews the prompt, the current development stage, and relevant workflow signals while preserving the complete original request.
  2. Structure — It builds one editable prompt with the sections the task needs, such as scope, constraints, acceptance expectations, verification, or missing-practice guidance.
  3. Safeguard — Higher-risk work can receive confirmation, safety, rollback, or evidence requirements. Complex work can also receive a sequence-aware breakdown when multiple prompts would be more effective.
  4. Review — You inspect and edit the result before sending it, or return to the original prompt. Nexpath provides the quality layer; you keep the final decision.

Benchmarked on SWE-bench Verified

Prompt quality is easy to demonstrate and hard to prove. To check whether Nexpath actually changes what a coding agent produces, we ran it against a public benchmark where the answer is graded by each project's own test suite — not by a person, and not by another model.

Setup: Claude Code (sonnet) attempted 40 tasks from SWE-bench Verified twice — once on its own, once with the Nexpath-reviewed prompt. The task, starting commit, container, model, time limit, and tools were identical in both runs. The prompt is the only thing that changed. Grading used the official SWE-bench harness.

Claude CodeClaude Code + Nexpath
Tasks solved27/40 (67.5%)29/40 (72.5%)
Issue's own tests pass27/40 (67.5%)29/40 (72.5%)
Ran the project's tests before submitting38/40 (95.0%)39/40 (97.5%)

Paired outcomes: solved by both — 27 · solved only with Nexpath — 2 · solved only without Nexpath — 0 · solved by neither — 11

Full results

Every number above traces to a file below. The full benchmark report (Nexpath_benchmark/README.md) has the method, the two tasks Nexpath won, and the eleven neither run could solve. These are the raw files behind it — all 40 tasks, both runs, and the list we locked before the first run.

Complete reportBenchmark report
Every task, both runsfinal_per_task.csv
All measurementsfinal_summary.json
Task list and settings, locked before the runstrat40-manifest.json
Prompt checks run before startingpreflight-strat40.json
Raw data for the confirmation-line testbefore · after

How Nexpath Reduces Risk

Fewer Silent Bugs and Missed Checks

  • Verification and test expectations can be added for debugging, maintenance, planning, review, and other tasks that need proof of completion.
  • Absence signals can surface missing regression checks, acceptance criteria, reproduction evidence, or project grounding.
  • Weak or unrelated signals are not used as filler; guidance must match the current task. The core interaction keeps your request and the added workflow guidance together:

Safer High-Risk Changes

  • Sensitive actions can receive explicit confirmation, rollback, backup, or safety requirements before the reviewed prompt is used.
  • Double confirmation, cross-confirmation, and final confirmation are used only when the task's complexity or risk justifies them.
  • The quality layer does not silently expand authority, auto-send work, or treat an agent response as proof of completion.

A More Maintainable Development Flow

  • Scope, constraints, acceptance expectations, affected surfaces, and behaviour-preservation needs stay visible instead of bein
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