analyst-core

Analyze structured inputs to produce evidence-based conclusions with risk and confidence.

Updated Mar 9, 2026
One-click install
npx skills add https://github.com/yin52133/roleflow-agents --skill analyst-core
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: analyst-core
Source: https://github.com/yin52133/roleflow-agents/tree/main/skills/analyst-core
Command: npx skills add https://github.com/yin52133/roleflow-agents --skill analyst-core

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill provides clear, evidence-based analysis of data, helping to make informed decisions by identifying risks and confidence levels without taking direct action.

Core Features & Use Cases

  • Data Interpretation: Analyzes structured inputs to provide concise summaries, evidence, and confidence scores.
  • Risk Assessment: Identifies potential risks associated with data or decisions.
  • Recommendation Generation: Offers actionable recommendations to an orchestrator (e.g., revise, trial, approve).
  • Use Case: An analyst uses this Skill to review a new marketing campaign's performance data, providing a summary, key evidence, confidence in the results, and a recommendation on whether to approve it for daily execution or if it needs further revision.

Quick Start

Analyze the provided sales data and recommend whether to approve for daily execution.

Frequently Asked Questions about analyst-core

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

FAQPage Schema
How do I get decision-ready conclusions from structured data analysis?

To perform data interpretation for decision support, you analyze structured inputs to generate concise summaries, key evidence, and confidence scores. This process identifies potential risks and provides actionable recommendations for workflow progression.

What is risk assessment in data interpretation and decision support?

Risk assessment in data interpretation identifies potential risks associated with data points or proposed decisions. It provides clear, evidence-based analysis to help make informed decisions without taking direct execution authority.

How do I generate actionable recommendations from marketing campaign data?

Generating actionable recommendations from marketing campaign data involves reviewing performance metrics to provide a summary, key evidence, and a confidence score. This analysis recommends whether to approve, revise, or trial the campaign for daily execution.

Can I use this for workflow progression and decision support without direct execution?

Yes, this approach satisfies requirements for clear communication of analytical findings and decision support without direct execution authority. It offers recommendations to an orchestrator, such as revise, trial, or approve, for workflow progression.

Does data interpretation work with structured inputs to provide confidence scores?

Yes, data interpretation analyzes structured inputs to provide concise, decision-ready conclusions. It explicitly includes confidence scores and evidence alongside risk assessments to support informed decision-making.

What are the limitations of using decision support for data interpretation?

The primary limitation is that this analytical approach provides recommendations without direct execution authority. It acts strictly as an advisory layer, meaning an orchestrator must execute the suggested actions for workflow progression.