research-librarian

Gather and organize sourced information into evidence packets with facts, inferences, and gaps.

Updated May 12, 2026
One-click install
npx skills add https://github.com/intelligent-alpha/mft-plugins --skill research-librarian
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: research-librarian
Source: https://github.com/intelligent-alpha/mft-plugins/tree/main/intelligent-alpha-mft/skills/research-librarian
Command: npx skills add https://github.com/intelligent-alpha/mft-plugins --skill research-librarian

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

It reduces the time and risk of weak or messy research by gathering sources, separating facts from inference, and producing clean evidence summaries with explicit gaps.

Core Features & Use Cases

  • Evidence gathering & organization: Collects relevant materials and groups them into usable research outputs.
  • Sourced vs. inferred separation: Clearly labels what is supported by sources versus what is an inference.
  • Gap detection & confidence signaling: Flags missing, stale, or low-confidence coverage so downstream work doesn’t pretend certainty.
  • Research dossier / packet prep: Packages evidence for analyst use or direct user review, suitable for dossiers and market mapping.

Quick Start

Use the research-librarian skill to build an evidence packet for this question: "What are the key drivers and risks for the Morgan Family Trust market priorities in 2025, and what sources support each claim?"

Frequently Asked Questions about research-librarian

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

FAQPage Schema
How do I organize research sources into a structured evidence packet?

To create an evidence packet, gather relevant materials and group them into structured outputs that distinctly label sourced facts versus inferences. This process packages the information for analyst-ready downstream work.

What is fact vs inference separation in evidence synthesis?

Fact vs inference separation in evidence synthesis is the practice of clearly labeling what is directly supported by sources versus what is an analytical inference. This distinction prevents downstream work from pretending certainty where gaps exist.

How do I identify coverage gaps and signal confidence in a research dossier?

Identify coverage gaps and signal confidence in a research dossier by flagging missing, stale, or low-confidence information. This ensures the dossier explicitly highlights unresolved gaps for accurate downstream analysis.

Can I use this approach for market mapping and source consolidation?

Yes, you can use this approach for market mapping and source consolidation. It gathers and organizes sourced information into evidence packets suitable for dossiers, ensuring correct evidence handling and explicit gap detection.

Does evidence gathering prioritize provided project context over web research?

Evidence gathering prioritizes active project context and provided materials first, using web research as needed. This ensures correct evidence handling by building on existing information before seeking external sources.