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features
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support

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Description

Blume serves as a desktop sidecar tailored for AI coding agents, enabling developers to monitor each agent's actions, maintain consistent project context, and identify potential drift before it impacts the codebase. It integrates seamlessly with tools like Cursor, Claude Code, Codex, omp, and Pi, consolidating agent activities, hidden files, skills, hooks, rules, and provider usage into a single interface. The Agents view provides insights into the status of each coding agent, indicating whether they are currently active, have completed their tasks, or are pending approval, while the Setup section reveals the instructions and configuration files that dictate agent behavior. Additionally, usage tracking helps developers keep tabs on remaining plan limits and token usage across various providers like Claude, Codex, and Cursor, thereby minimizing the risk of unexpected disruptions. Blume also securely stores conversation history locally, enabling on-device reviews of rules, skills, and hooks. Its Improve workflow actively identifies recurring points of friction within conversations, groups related issues, and suggests actionable improvements, which may include new rules or the creation of reusable skills, ultimately enhancing the overall coding experience. Furthermore, this continuous feedback loop fosters a more efficient development process, allowing teams to adapt and refine their workflows as needed.

Description

Anyone can get an AI agent to turn tests green on a toy problem. kodwai measures the part that is harder to fake: how well you direct it. Developers pick a real engineering challenge (a CRDT text buffer, an event-sourced ledger, a zero-downtime migration), pull it down with npx @kodwai/cli@latest challenge <slug>, and solve it locally with Claude Code, Cursor or Codex. No browser sandbox. When they run npx @kodwai/cli@latest submit, kodwai reads the session (prompts, commits, test runs) and returns a 0 to 100 score across three axes: Direction (how you steer, verify and decompose), Outcome (what shipped, replayed and stress-tested) and Lift (how far you beat a solo AI). Each signal cites its evidence, and the score comes with a confidence interval instead of false precision. Developers get 3 free scored submissions, then connect their own Anthropic key for unlimited runs. Teams can use the hiring track to run private real-world interviews.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Claude Code Yes 
Cursor Yes 
OpenAI Codex Yes 
Claude No 
Codex CLI No 
Git No 
Node.js No 
Pi Yes 
omp Yes 

Integrations

Claude Code Yes 
Cursor Yes 
OpenAI Codex Yes 
Claude Yes 
Codex CLI Yes 
Git Yes 
Node.js Yes 
Pi No 
omp No 

Pricing Details

Free
Free Trial No 
Free Version Yes 

Pricing Details

Free
Free for developers: 3 scored submissions on kodwai's key, then connect your own Anthropic API key for unlimited submissions. The challenges, score, public profile and leaderboard are free. Hiring track for teams: contact us for pricing.
Free Trial No 
Free Version Yes 

Deployment

Web-Based No 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac Yes 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac Yes 
Linux Yes 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

blume

Country

United States

Website

blume.codes/

Vendor Details

Company Name

kodwai

Country

Istanbul, Turkey

Website

www.kodwai.com

Product Features

Product Features

Coding Challenge

Kodwai is an innovative platform designed for hands-on coding challenges that emphasize agency in coding. The challenges presented are practical, bite-sized tasks—ranging from creating a bookshelf REST API to implementing a simplified version of the Raft consensus algorithm—and each task incorporates subtle pitfalls that a simple prompt might overlook. Participants tackle these challenges locally using their own AI coding agents, and the scoring system evaluates not only the success of the tests but also how effectively the user guided their agent. Scores are based on three criteria: Direction, Outcome, and Lift, with a scale from 0 to 100 and detailed evidence for each metric. The platform features a public leaderboard, a dynamic Direction rating that updates with each scored attempt, and weekly competitions to foster a sense of community.

Alternatives

Alternatives

No Alternatives
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