research-gatherer

What problem does it solve?

Manually collecting and cross-checking research from disparate internal (codebases, tickets, transcripts) and external (web, industry sources) sources is time-consuming, error-prone, and often leads to missed contradictions or unsubstantiated claims. This skill automates the end-to-end gathering and verification process to deliver raw, fully verified findings without requiring a full synthesized report.

Core Features & Use Cases

• Parallel multi-source gathering: Collects findings from internal sources (code, documentation, tickets, transcripts) and external sources (web, industry standards, competitor sites) simultaneously via specialized subagents.
• Automated cross-verification: Flags contradictions between sources, assigns confidence levels to each finding, and tags unsubstantiated declarative claims from stakeholders to avoid bias.
• Use case: If you need to compile unprocessed data on internal codebase gaps and competitor feature parity for a product roadmap review, this skill will gather all relevant findings, verify them across sources, and deliver structured raw data for your team to analyze without writing a final report.

Quick Start

Use the research-gatherer skill to collect and cross-verify raw findings on how our product's checkout flow compares to top 3 competitors, including internal code limitations and external UX best practices.