Codebugs FAQs

Question 1

How does Codebugs help save AI tokens?

Accepted Answer

Instead of re-processing large codebases or chat histories, AI assistants can query Codebugs for structured summaries of findings. This token-efficient method provides instant context recovery, drastically reducing operational costs.

Question 2

How do developers interact with Codebugs?

Accepted Answer

Developers interact with Codebugs primarily through a user-friendly command-line interface (CLI) to add, query, update, and manage findings. AI assistants use an MCP server interface to integrate seamlessly into their workflows.

Question 3

What problem does Codebugs solve for AI assistants?

Accepted Answer

Codebugs provides AI assistants with persistent memory, preventing the loss of code review findings, bug reports, and technical debt context between sessions. This eliminates the need for AI to re-read files, saving significant tokens.

Question 4

What kind of information can Codebugs track?

Accepted Answer

Codebugs tracks code review findings, bug reports, and technical debt. It includes core fields like severity, category, file, and status, plus flexible JSON columns for custom metadata and tags, allowing comprehensive tracking.

Question 5

Can Codebugs help identify systemic code quality issues?

Accepted Answer

Yes, Codebugs' pattern detection capabilities allow you to analyze findings by category over time. This reveals recurring issues, helping teams identify systemic problems that require architectural changes, new lint rules, or pre-commit checks.

Codebugs

Codebugs

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Características Principales

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