Technical Explainer

Generate a source-backed technical explainer with a labeled hero image.

6|2|Updated May 21, 2026
One-click install
npx skills add https://github.com/anajuliabit/aeon --skill technical-explainer-anajuliabit
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: Technical Explainer
Source: https://github.com/anajuliabit/aeon/tree/main/skills/technical-explainer
Command: npx skills add https://github.com/anajuliabit/aeon --skill technical-explainer-anajuliabit

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes assets (resource) components.

What problem does it solve?

It generates a sharp, visual, technical explainer for a specific recent mechanism, so you can understand how something works without reading scattered sources or guessing the core move.

Core Features & Use Cases

  • Deterministic topic selection: Picks the newest relevant mechanism from recent articles, paper picks, or memory logs when you don’t provide an explicit topic.
  • Triangulated research: Runs three targeted WebSearch queries to extract the core mechanism, failure modes, and concrete quantitative anchors with primary-source emphasis.
  • Replica hero image with safe fallback: Attempts to generate a labeled schematic via Replicate when REPLICATE_API_TOKEN is set; otherwise it reliably ships a text-only explainer and logs the skip reason.
  • Structured, reusable output: Saves a 600–1000 word explainer (with sources) to articles/ and notifies with the key idea line and read link.

Quick Start

Run the skill with an explicit topic like Technical Explainer var="entropy trajectory reasoning" to produce articles/explainer-<today>.md including a key idea, step-by-step mechanism, numbers with sources, and a notification.

Frequently Asked Questions about Technical Explainer

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

FAQPage Schema
How do I generate a technical explainer with primary sources and diagrams?

To generate a technical explainer, you provide a topic and the skill runs three targeted web searches to extract core mechanisms, failure modes, and quantitative anchors from primary sources. It then outputs a structured 600–1000 word article with a labeled hero image.

What is triangulated research for explaining technical mechanisms?

Triangulated research is a method that runs three distinct web searches to cross-verify a technical mechanism. It extracts the core mechanism, failure modes, and concrete quantitative anchors with primary-source emphasis to ensure falsifiable precision in the final article.

Can I generate labeled schematic diagrams without an API token?

You cannot generate visual schematic diagrams without a token, but you can reliably ship a text-only technical explainer. The skill safely falls back to a text-only output and logs the skip reason if the required image generation token is not set.

How do I write a step-by-step mechanism article from recent papers?

You write a step-by-step mechanism article by running the skill with an explicit topic. It performs triangulated research, optionally fetches primary paper metadata, and saves a structured 600–1000 word explainer with a key idea, mechanism steps, and numbers with sources.

Does the technical writing explainer require explicit topic input?

The technical writing explainer does not require explicit topic input. It uses deterministic topic selection to automatically pick the newest relevant mechanism from recent articles, paper picks, or memory logs when you do not provide a specific topic.

What are the limitations of using agent automation for technical writing?

A key limitation is the dependency on external tokens for visual output; without it, the agent automation ships text-only explainers. Additionally, it is scoped to single recent mechanisms, meaning it is not designed to synthesize broad, multi-topic overviews.