tech-search

Perform deep-tech research via parallel web searches and structured documentation.

Updated Aug 23, 2026

Search Tags:#documentation #webfetch #web-search #haiku #research-pipeline #tech-research

Ready to run

npx skills add https://github.com/gabriel-daldegan/missionary_journal --skill tech-search-gabriel-daldegan

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: tech-search
Source: https://github.com/gabriel-daldegan/missionary_journal/tree/main/.claude/skills/tech-search
Command: npx skills add https://github.com/gabriel-daldegan/missionary_journal --skill tech-search-gabriel-daldegan

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Centralizes and automates deep-tech research workflows by orchestrating web search, content extraction, and structured documentation without external dependencies.

Core Features & Use Cases

Phase-driven workflow: Auto-clarify, decompose, parallel search, evaluate, synthesize, and document findings.
Zero external dependencies: Runs with built-in capabilities, outputs to docs/research.
Documentation-first outputs: Produces structured research artifacts for reuse and auditing.

Quick Start

In your query, ask for a deep technical topic to begin the end-to-end research pipeline.

Frequently Asked Questions about tech-search

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

FAQPage Schema

How do I automate deep technical research and generate structured documentation?▼

You can automate deep technical research by orchestrating a phase-driven workflow that decomposes queries, performs parallel web searches, synthesizes findings, and outputs structured documentation artifacts automatically.

Can I run a web search research pipeline without external dependencies?▼

Yes, this research pipeline runs entirely with built-in capabilities, requiring zero external dependencies to execute web searches, extract content, and generate structured documentation.

How does the research pipeline structure its output artifacts for reuse?▼

The research pipeline structures output artifacts by saving them as documentation files under the docs/research/{YYYY-MM-DD}-{slug}/ directory, ensuring generated findings are auditable and reusable.

What is the workflow for decomposing complex technical topics during research?▼

The workflow for decomposing technical topics involves an auto-clarify phase, parallel web searches across sub-topics, an evaluation stage, and a final synthesis step to document structured findings comprehensively.

When do I need a phase-driven workflow for technical research?▼

You need a phase-driven workflow for technical research when tackling complex topics that require systematic decomposition, parallel data gathering, content evaluation, and structured synthesis into reusable documentation.

Are there limitations to using built-in capabilities for content extraction in research?▼

A key limitation of using built-in capabilities for content extraction is the reliance on internal webfetch mechanisms, which may lack the advanced parsing depth of specialized external scraping libraries.