satya-anguluri/capstead — explained in plain English
Analysis updated 2026-05-18
Track how often an AI-powered method runs, its cost, and its success rate across a team.
Set a daily spending budget on an AI capability and automatically block calls once it's reached.
Expose a catalog of AI capabilities in an app through Spring Boot Actuator endpoints.
| satya-anguluri/capstead | android-hacker/xposedwechathelper | fiberjw/chat.cool | |
|---|---|---|---|
| Stars | 7 | 7 | 7 |
| Language | Java | Java | Java |
| Last pushed | — | 2018-03-13 | 2017-04-17 |
| Maintenance | — | Dormant | Dormant |
| Setup difficulty | moderate | hard | moderate |
| Complexity | 3/5 | 3/5 | 3/5 |
| Audience | developer | developer | developer |
Figures from each repo's GitHub metadata at analysis time.
Requires a Spring Boot app already using an AI provider like Spring AI or LangChain4j.
Capstead is a Spring Boot library that adds governance and visibility on top of AI features you build in a Java application. It is not a framework for calling AI models itself, and it does not replace tools like Spring AI or LangChain4j. Instead, it wraps around whatever you already use to talk to a model and turns your normal methods into tracked, versioned business capabilities, all from adding one annotation to a method. Once you install it and annotate a method with @Capability, giving it a name, a domain, an owner, and a version, Capstead automatically starts recording how often that method runs, which model it used, how many tokens were consumed, what it cost, whether it succeeded, and which version was live at the time. This information becomes available through built in endpoints, including a catalog of all capabilities, a scorecard with invocation counts and cost data, a detailed execution history, and a small web dashboard. There are three ways to declare a capability: putting the annotation directly on your method, describing it in a YAML configuration file without touching the code at all, or writing an interface method with no implementation body that Capstead fills in for you by rendering a prompt and calling the configured model. You can set a daily spending budget per capability, and once that budget is reached, further calls are blocked until the next day. Cost tracking works by attributing token and pricing information from your existing model calls to the capability that triggered them, which requires adding a small bridge dependency if you use Spring AI, or manually recording model calls yourself if you use something else. Every capability call also becomes a recorded execution, and when one capability calls another, the nested calls are linked together automatically, forming a traceable execution tree. This is aimed at Java and Spring Boot developers who are shipping AI features across a team and need to answer basic questions like what capabilities exist, who owns them, and what they cost to run.
A Spring Boot library that adds a governance and cost tracking layer over your existing AI features using a single annotation.
Mainly Java. The stack also includes Java, Spring Boot, Spring AI.
Setup difficulty is rated moderate, with roughly 30min to a first successful run.
Mainly developer.
This repo across BitVibe Labs
double-check against the repo, no cap.