deep-reading-analyst_skill

This skill helps you perform deep reading analyses of long-form content using multiple thinking frameworks to extract insights and actions.
  • Python

189

GitHub Stars

1

Bundled Files

2 months ago

Catalog Refreshed

4 months ago

First Indexed

Readme & install

Copy the install command, review bundled files from the catalogue, and read any extended description pulled from the listing source.

Installation

Preview and clipboard use veilstrat where the catalogue uses aiagentskills.

npx veilstrat add skill yyh211/claude-meta-skill --skill deep-reading-analyst

  • SKILL.md14.9 KB

Overview

This skill is a comprehensive framework for deep analysis of articles, papers, and long-form content using 10+ proven thinking models. It guides readers from structural understanding to actionable application, adapting depth from a 15-minute quick scan to multi-hour research synthesis. Use it to surface core claims, test arguments, expose risks, and produce study notes or decision-ready outputs.

How this skill works

Provide the content (paste text or a URL) and specify your goal and desired depth. The workflow asks three quick setup questions (goal, depth, preferred frameworks) and then runs a structured pipeline: structural mapping (SCQA, 5W2H), argument evaluation (critical thinking, inversion), and deeper lenses as requested (mental models, first principles, systems thinking, six thinking hats). Outputs are tailored: concise insights, evidence-based critiques, action plans, learning notes, or cross-source syntheses.

When to use it

  • You want a clear one-sentence thesis and structure map from a long article
  • You need to identify logical flaws, unsupported claims, or hidden assumptions
  • You want actionable insights or a step-by-step application plan from a reading
  • You are creating study notes, summaries, or teaching materials from complex content
  • You need to compare multiple sources and produce an integrated synthesis
  • You want to apply a specific thinking framework (e.g., SCQA, inversion, first principles) to a piece of writing

Best practices

  • Start by stating your goal and how deep you want the analysis to be (quick/standard/deep/research)
  • Share context about how you’ll use the insights so outputs are practical and prioritized
  • Allow progressive deepening: begin with a quick scan, then request deeper models on specific sections
  • Prefer specific frameworks for targeted outcomes (SCQA for clarity, inversion for risks, first principles for redesign)
  • Ask for citations or paragraph references when you need to quote or validate claims

Example use cases

  • Turn a 3,000-word industry report into a 5‑minute executive brief with top 3 actions
  • Evaluate an opinion piece to surface logical fallacies and counterarguments for a debate
  • Transform a research paper into study notes with verification questions and core equations
  • Compare three conflicting articles and synthesize consensus, divergence, and a recommended stance
  • Run an inversion pre-mortem on a proposed strategy to identify failure modes and mitigations

FAQ

Typical durations follow levels: Quick 15min, Standard 30min, Deep 60min, Research 120min+. Choose based on desired thoroughness.

Can you apply only specific frameworks?

Yes. Specify frameworks like "SCQA + Inversion" and the process will focus those lenses without unnecessary extras.

Will the analysis quote the original text?

I paraphrase to stay faithful while avoiding verbatim copying. I can include exact quotes or paragraph references on request for citation.

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