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objective-research

Separate agent contexts to research code paths and data flow objectively.

37|8|Updated Mar 4, 2026

Search Tags:#implementation planning #codebase analysis #agentic workflow #code research #bias mitigation #factual investigation

Ready to run

npx skills add https://github.com/mlopscommunity/Coding-Agents-Conference-skills --skill objective-research

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: objective-research
Source: https://github.com/mlopscommunity/Coding-Agents-Conference-skills/tree/main/skills/objective-research
Command: npx skills add https://github.com/mlopscommunity/Coding-Agents-Conference-skills --skill objective-research

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill provides a method to research codebases for implementation tasks without the bias that arises when the research agent knows the ultimate goal.

Core Features & Use Cases

Separates Intent from Investigation: Uses two distinct agent contexts to ensure factual, unbiased findings.
Targeted Question Generation: Decomposes tickets into specific, factual research questions.
Use Case: Before implementing a new feature in an unfamiliar part of the codebase, use this Skill to understand existing call paths, data flow, and current behavior, ensuring your implementation is based on accurate, objective information.

Quick Start

Use the objective-research skill to decompose the ticket into targeted research questions.

Frequently Asked Questions about objective-research

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I prevent confirmation bias during codebase research?▼

To prevent confirmation bias during codebase research, separate agent contexts for intent and investigation. This ensures research questions remain factual and intent-free, yielding objective data on existing code paths before development.

How do I analyze existing data flow and call paths before implementing a new feature?▼

To analyze existing data flow and call paths, use a two-context agentic workflow to decompose tickets into targeted research questions. This gathers objective data on current behavior and feature implementations before you start coding.

What is a factual investigation workflow for unfamiliar code paths?▼

A factual investigation workflow for unfamiliar code paths splits intent from investigation using two distinct agent contexts. This mechanism ensures the research agent gathers objective data without knowing the ultimate development goal.

How do I decompose implementation tickets into specific research questions?▼

To decompose implementation tickets into specific research questions, apply an intent-free context to the ticket details. This generates targeted, factual queries about existing code paths and current behavior for objective codebase investigation.

When should I use a two-context workflow for code research?▼

Use a two-context workflow for code research when you need to implement a new feature in an unfamiliar part of the codebase. It prevents the research agent's confirmation bias by keeping the ultimate goal hidden during data gathering.