ACSR Research Lifecycle

Orchestrate the Aggregate, Compute, Synthesize, and Repeat research methodology for PE/VC financial analysis.

Updated Mar 10, 2026
One-click install
npx skills add https://github.com/ganoro/equiforte-workspaces-local-2 --skill acsr-research-lifecycle
Or copy as Structured Prompt for Agent
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Skill: ACSR Research Lifecycle
Source: https://github.com/ganoro/equiforte-workspaces-local-2/tree/main/df1ef9f0-3138-4b76-8be9-a0e40bc4ccef/claude-plugin/skills/acsr-lifecycle
Command: npx skills add https://github.com/ganoro/equiforte-workspaces-local-2 --skill acsr-research-lifecycle

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill provides a structured methodology for conducting research and analysis tasks, ensuring comprehensive data aggregation, rigorous computation, and clear synthesis of findings.

Core Features & Use Cases

  • ACSR Methodology: Implements the Aggregate → Compute → Synthesize → Repeat loop for all research.
  • Provenance Tracking: Ensures every fact extracted has detailed source information.
  • Confidence Scoring: Assigns confidence levels to extracted data and synthesized findings.
  • Gap Identification: Systematically identifies missing data and areas for further investigation.
  • Use Case: When asked to analyze a company's financial performance, this Skill will guide the process from gathering all relevant financial statements to performing calculations, synthesizing key insights, and identifying any remaining data gaps.

Quick Start

Initiate the ACSR research lifecycle for any new analysis request.

Frequently Asked Questions about ACSR Research Lifecycle

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

FAQPage Schema
What is the ACSR methodology for financial research and analysis?

The ACSR methodology is a structured research process implementing an Aggregate, Compute, Synthesize, and Repeat loop for financial analysis. It guides tasks from gathering financial statements to performing calculations and synthesizing key insights.

How do I conduct PE/VC financial analysis with provenance tracking and confidence scoring?

To conduct PE/VC financial analysis, use the ACSR lifecycle to orchestrate data aggregation and computation. It automatically manages provenance tracking for extracted facts and assigns confidence levels to synthesized findings.

How do I identify data gaps when synthesizing financial research?

To identify data gaps during financial research synthesis, the ACSR lifecycle systematically evaluates aggregated data and computed results. It highlights missing data areas to guide further investigation and generate decision-ready conclusions.

Can I use this research lifecycle for structured data extraction in quantitative analysis?

Yes, you can use this research lifecycle for structured data extraction in quantitative analysis. It supports extracting financial data, performing rigorous computations, and synthesizing quantitative findings into decision-ready outputs.

Does this structured research methodology work for private equity and venture capital tasks?

Yes, this structured research methodology is specifically designed for private equity and venture capital tasks. It orchestrates comprehensive financial analysis, managing provenance and confidence scoring throughout the PE/VC evaluation process.

Why does my financial research synthesis lack decision-ready conclusions?

Financial research synthesis lacks decision-ready conclusions when missing the ACSR loop's rigorous computation and gap identification. Repeating the aggregate, compute, and synthesize phases ensures all missing data is addressed for confident conclusions.