Deep Technical Research

VerifiedSafe

Conducts deep research on technical topics for blog writing when the user asks to research, look into, or explore a topic. Searches the web extensively, reads high-quality sources, and creates structured research notes with visual diagram opportunities. Ideal for gathering comprehensive technical knowledge quickly.

Sby Skills Guide Bot
ContentIntermediate
6/2/2026
Claude Code
#research#blog-writing#technical-deep-dive#visual-diagrams#web-scraping

Recommended for

Automated summary

Performs deep research on a technical topic by exploring the web, extracting key concepts, and identifying diagram opportunities for blog writing.

Strengths

  • Structured research process with multiple web searches and deep reading
  • Organized extraction of concepts, historical context, and comparisons
  • Systematic identification of diagram opportunities to enhance understanding
  • Generates comprehensive research notes ready for blog post creation

Limitations

  • Requires reliable web access and may encounter fetch limits
  • Quality of output heavily depends on availability of good sources
  • Not suitable for non-technical topics or superficial research
When to use it

Best when preparing a detailed technical blog post that requires deep understanding and visual aids.

When not to use it

Avoid for quick fact-checking or simple definitions, or when the topic is non-technical.

Security analysis

Safe
Quality score90/100

This skill uses web search and content extraction for research purposes only, with no instructions to execute code, access sensitive data, or perform destructive actions.

No concerns found

How this analysis is made

Examples

Research Multi-Head Latent Attention
Research the Multi-head Latent Attention mechanism from DeepSeek for a blog post. I need a deep dive with diagrams.
Explore GRPO algorithm
Look into the GRPO algorithm used by DeepSeek-R1. I want to understand how it works and compare to PPO.
Research speculative decoding
Explore speculative decoding techniques for LLM inference. I want to write a technical blog post about it.

name: research-topic description: "Deep research on a technical topic for blog writing. Use when user says research, look into, explore, or provides a blog topic to investigate. Searches the web extensively and creates structured research notes with visual opportunity identification." allowed-tools: Bash, Read, Grep, Glob, WebFetch

Deep Research Skill

Input

$ARGUMENTS = the topic to research

Process

Step 1: Broad Search (5 to 8 searches)

Search the web for high-quality sources on the topic:

  • Original research papers (arXiv, conference proceedings)
  • Official documentation and blog posts from the creators
  • Well-written technical blog posts (Lilian Weng, Jay Alammar, etc.)
  • Video transcripts or lecture notes if available
  • GitHub implementations for reference

Step 2: Deep Read

For each promising source, use WebFetch to read the full content. Extract and organize:

Core Concepts

  • What is this? (one-paragraph definition)
  • Why does it exist? What problem does it solve?
  • What did it replace or improve upon?

How It Works (Technical Depth)

  • Step-by-step mechanism
  • Key equations and their intuition
  • Concrete numerical examples (shapes, dimensions, values)
  • Implementation details

Comparisons and Alternatives

  • How does this compare to previous approaches?
  • What are the trade-offs?
  • Quantitative comparisons (benchmarks, memory savings, speedups)

Historical Context

  • When was it introduced? By whom?
  • What papers are most relevant?
  • How has it evolved since introduction?

Step 3: Identify Visual Opportunities

This is critical. For EVERY concept, ask: "Would a diagram help here?" List 6 to 10 concepts that NEED visual diagrams:

  • Architecture overviews
  • Data flow through components
  • Step-by-step process walkthroughs
  • Before/after comparisons
  • Matrix operations with concrete shapes
  • Mathematical derivation steps

For each, write:

  • Diagram name (e.g., "fig_mla_architecture")
  • What it should show
  • Type: architecture / flowchart / comparison / step-by-step / matrix-operation

Step 4: Save Research Notes

Save to: research/<topic-slug>.md

Structure:

# Research: <Topic Name>

## Quick Summary
(2-3 sentence overview)

## Core Concepts
(detailed notes)

## How It Works
(step-by-step technical breakdown)

## Mathematical Foundation
(key equations with explanations)

## Comparisons and Alternatives
(vs previous approaches, with numbers)

## Visual Opportunities
(list of 6-10 diagrams needed with descriptions)

## Running Example
(define the simple example we will use throughout:
 e.g., 4 tokens, specific dimensions, concrete values)

## Key Sources
- [Paper Name](url) - what we extracted from it
- [Blog Post](url) - what we extracted from it

Output

Save to research/<topic-slug>.md and summarize key findings to user. Tell the user how many diagram opportunities were identified.

From the file to a first result

The download contains exactly the content displayed on this page. This copy may differ from the latest version in the source repository.

View the source and supporting files

This download contains SKILL.md only. Any scripts, references, templates and dependencies are not included. Get the required files from the source, preserving their directory structure, before continuing.

1. Download the file

Download SKILL.md

From the root of a test project, save the file as .skill-downloads/deep-technical-research-mm5t8a94/SKILL.md, or use the command below. This folder is for inspecting the skill before installation.

Command for macOS/Linux or WSL: requires a POSIX shell and curl. On Windows without WSL, use the download button and create the folder manually.

mkdir -p '.skill-downloads/deep-technical-research-mm5t8a94' && curl --fail --show-error --location 'https://skills-guides.com/api/skills/deep-technical-research-mm5t8a94/download' --output '.skill-downloads/deep-technical-research-mm5t8a94/SKILL.md.part' && mv '.skill-downloads/deep-technical-research-mm5t8a94/SKILL.md.part' '.skill-downloads/deep-technical-research-mm5t8a94/SKILL.md'

2. Check prerequisites

Read SKILL.md before using it. If it references scripts or external services, inspect them and prepare the required access in your test environment.

Tools declared by the author (check availability in your agent): Bash, Read, Grep, Glob, WebFetch

No recognized prerequisites section in this file. This does not mean it is self-contained: libraries, tools and access requirements may be mentioned elsewhere in the content or source repository.

The platforms on this page are catalog indications. The paths below follow tool documentation; they do not prove this skill has been run in those tools. No minimum tool version is confirmed for this listing.

3. Load the skill

After inspection, copy the complete folder into your project using one of the commands below, then open a new tool session. The command stops if a folder with the same name already exists: compare the files before replacing it.

Claude Code
test -f '.skill-downloads/deep-technical-research-mm5t8a94/SKILL.md' && test -s '.skill-downloads/deep-technical-research-mm5t8a94/SKILL.md' && mkdir -p '.claude/skills' && test ! -e '.claude/skills/research-topic' && cp -R '.skill-downloads/deep-technical-research-mm5t8a94' '.claude/skills/research-topic'

OpenSkills

OpenSkills must already be installed. The local install/read procedure is checked with OpenSkills 1.5.0, which requires Node.js ≥ 20.6.0. Catalog slugs are not resolved automatically.

Official OpenSkills installation
openskills install './.skill-downloads/deep-technical-research-mm5t8a94'

openskills read 'deep-technical-research-mm5t8a94'

Reading should display the installed file content and its base directory. It does not run the skill or install its dependencies.

For an agent that reads AGENTS.md, then sync the index. This command changes AGENTS.md: review the diff before using it.

openskills sync

Manual method or another tool: attach SKILL.md to a conversation, or open it in an agent that can read files. Include any required supporting resources. No universal folder is recognized by every tool.

4. Try a first task

Use a short, synthetic input: an API endpoint, a small document or an interface brief. In a new conversation, attach the file or give the agent its path, then adapt this request:

Read .skill-downloads/deep-technical-research-mm5t8a94/SKILL.md and apply its instructions to this example: [describe a test input]. Identify any missing files, dependencies or access. Produce the result requested by the skill without inventing data or running unreviewed scripts.

Expected result: output matching the skill instructions, or a precise list of missing prerequisites. A read confirmation alone does not validate a first use. If an external resource is unavailable, that path remains untested.

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