dialectic

Run a four-stage startup investment analysis pipeline with structured JSON output.

30|7|Updated Jan 12, 2026
One-click install
npx skills add https://github.com/pantageepapa/DIALECTIC --skill dialectic-pantageepapa
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: dialectic
Source: https://github.com/pantageepapa/DIALECTIC/tree/main
Command: npx skills add https://github.com/pantageepapa/DIALECTIC --skill dialectic-pantageepapa

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

DIALECTIC automates a structured venture-capital startup analysis pipeline using Claude Code, enabling teams to quickly evaluate opportunities with repeatable, data-driven arguments and recommendations.

Core Features & Use Cases

  • Website-first intake with automatic company info inflation from scraping, plus manual fallback
  • LinkedIn founder/team extraction via screenshots to populate rich Team data
  • End-to-end multi-agent pipeline: decomposition → argument generation → devil's advocate critique → refinement (2 iterations)
  • Pro/con argument generation with scoring and a concrete investment recommendation

Quick Start

Open Claude Code and type /dialectic to start a full startup investment analysis.

Frequently Asked Questions about dialectic

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

FAQPage Schema
How do I automate startup investment analysis using Claude Code?

You can automate startup investment analysis by running the /dialectic slash command in Claude Code, which triggers a multi-agent pipeline to evaluate opportunities and generate data-driven investment recommendations.

What is the devil's advocate approach in AI venture capital analysis?

The devil's advocate approach in venture capital analysis is a pipeline stage where AI critiques generated investment arguments, running two refinement iterations to stress-test pros and cons before delivering a final recommendation.

Can I extract founder data from LinkedIn screenshots for startup evaluation?

Yes, you can extract founder data from LinkedIn screenshots for startup evaluation. The pipeline accepts image uploads to automatically populate rich team profiles during the investment analysis workflow.

How do I scrape startup website data to generate investment arguments?

To scrape startup website data for investment arguments, the pipeline uses a website-first intake mechanism that automatically inflates company information, with a manual fallback option if scraping yields insufficient data.

Does the DIALECTIC pipeline output structured JSON for downstream tooling?

Yes, the DIALECTIC pipeline outputs structured JSON for downstream tooling. This format captures the decomposed arguments, devil's advocate critiques, scores, and the final investment recommendation for integration.

What are the limitations of automated VC analysis for startup evaluation?

A limitation of automated VC analysis is its dependency on initial data quality; if website scraping or LinkedIn screenshots lack depth, the generated pro/con arguments and investment recommendations may require manual verification.