agent-spec — Agent Tool by ZhangHanDong

by ZhangHanDong · Agent Tool · ★ 266

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About agent-spec

agent-spec is an AI-native BDD/spec verification tool for task execution. The core idea is simple: humans review the contract agents implement against the contract the machine verifies whether the code satisfies the contract The primary planning surface is the Task Contract. The older view remains available as a compatibility alias, but new workflows should use . Task Contract A task contract is a structured spec with four core parts: : what to do, and why : technical choices that are already fixed : what may change, and what must not change : BDD scenarios that define deterministic pass/fail behavior The DSL supports English and Chinese headings and step keywords. Example spec spec: task name: "User Registration API" tags: [api, contract] Intent Implement a deterministic user registration API contract that an agent can code against and a verifier can check with explicit test selectors.

agentai-codingspec

Quick Facts

Stars266
Forks21
LanguageRust
CategoryAgent Tool
LicenseMIT
Quality Score73.9187592305646/100
Last Updated2026-06-21
Created2026-03-07
Platformsrust
Est. Tokens~26k

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Frequently Asked Questions

What is agent-spec?

agent-spec is `agent-spec` is an AI-native BDD/spec verification tool for task execution.. It is categorized as a Agent Tool with 266 GitHub stars.

What programming language is agent-spec written in?

agent-spec is primarily written in Rust. It covers topics such as agent, ai-coding, spec.

How do I install or use agent-spec?

You can find installation instructions and usage details in the agent-spec GitHub repository at github.com/ZhangHanDong/agent-spec. The project has 266 stars and 21 forks, indicating an active community.

What license does agent-spec use?

agent-spec is released under the MIT license, making it free to use and modify according to the license terms.

What are the best alternatives to agent-spec?

The top alternatives to agent-spec on Agent Skills Hub include Mysti, wcgw, claude-context-local. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.

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