Why does this skill run in an isolated context?

Running in a fork context prevents exploratory search results and 'noise' from cluttering your main conversation history, keeping your primary workspace clean for actual coding.

What is the ACE-FCA quality equation?

ACE-FCA stands for Correct + Complete + Minimal noise. It is a quality standard used by this skill to ensure that research findings are accurate, comprehensive, and free from irrelevant search artifacts.

When is the best time to use the researching-codebase skill?

It is best used before any non-trivial implementation task, when navigating unfamiliar areas of a codebase, or before making significant architectural decisions.

How does the skill ensure evidence-based results?

Every claim made by the skill must include a specific file path, line numbers, and relevant code references (like function or class names) to ensure the information is auditable.

Codebase Research (ACE-FCA)

Name: Codebase Research (ACE-FCA)
Author: qte77

byqte77

0•

开发者工具

Conducts isolated, evidence-based codebase investigations to gather deep technical context before planning implementation tasks.

The researching-codebase skill implements the ACE-FCA (Correct + Complete + Minimal noise) framework to provide objective insights into a repository's architecture and logic. By running investigations in an isolated fork context, it prevents search artifacts from polluting the main conversation while extracting precise file paths, patterns, and constraints. This skill is essential for developers working in unfamiliar codebases or preparing for complex architectural decisions, ensuring that every plan is backed by documented evidence rather than assumptions.

主要功能

01Structured markdown output designed for immediate planning use

02ACE-FCA quality standard for high-signal, low-noise context

03Automated identification of codebase patterns and constraints

04Isolated context exploration to prevent main-thread pollution

050 GitHub stars

06Evidence-based reporting with exact file paths and line numbers

使用场景

01Validating architectural constraints before a major system refactor

02Gathering evidence and file references for non-trivial feature implementations

03Onboarding to a large, unfamiliar repository before making changes

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add qte77/claude-code-utils-plugin researching-codebase

For use in Claude.ai and ChatGPT

主要功能

01Structured markdown output designed for immediate planning use

02ACE-FCA quality standard for high-signal, low-noise context

03Automated identification of codebase patterns and constraints

04Isolated context exploration to prevent main-thread pollution

050 GitHub stars

06Evidence-based reporting with exact file paths and line numbers

使用场景

01Validating architectural constraints before a major system refactor

02Gathering evidence and file references for non-trivial feature implementations

03Onboarding to a large, unfamiliar repository before making changes

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add qte77/claude-code-utils-plugin researching-codebase

For use in Claude.ai and ChatGPT