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cristoslc
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swain-search

Collect, normalize, and cache research sources into structured Markdown evidence pools.

Updated Feb 22, 2026
Search Tags:#documentation#markdown#research#knowledge management#evidence#synthesis
One-click install
npx skills add https://github.com/cristoslc/tidegate --skill swain-search
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: swain-search
Source: https://github.com/cristoslc/tidegate/tree/main/.agents/skills/swain-search
Command: npx skills add https://github.com/cristoslc/tidegate --skill swain-search

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill automates the collection, normalization, and caching of research sources into reusable evidence pools, streamlining the process of gathering information for documentation and analysis.

Core Features & Use Cases

  • Evidence Collection: Gathers sources from web searches, URLs, local files, and media.
  • Normalization: Converts diverse source types into a consistent Markdown format.
  • Caching: Stores normalized sources in reusable evidence pools for future reference.
  • Use Case: When starting a new spike or ADR, use this Skill to automatically research a topic, collect relevant articles and documentation, and synthesize the key findings into a structured pool that can be easily referenced.

Quick Start

Use the swain-search skill to research the topic 'websocket vs sse'.

Frequently Asked Questions about swain-search

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

FAQPage Schema
How do I collect and normalize web search results into Markdown for research?▼

To build evidence pools, ingest local files, fetch URLs, perform web searches, or transcribe media. The tool normalizes these diverse research sources into structured Markdown with YAML frontmatter, caching them for future artifact referencing and knowledge management.

Can I use local files and media transcription to build a knowledge management evidence pool?▼

Yes, you can ingest local files and transcribe media to build a knowledge management evidence pool. These sources are collected, normalized to Markdown with YAML frontmatter, and cached alongside web search results to create a unified research repository.

What is the best way to manage research source freshness and refresh cached evidence pools?▼

The best way to manage research source freshness is to use pool refresh commands based on source staleness. This updates cached evidence pools, ensuring your normalized Markdown documentation remains current and accurately referenced for ongoing synthesis.

How do I structure research findings for an ADR or documentation spike?▼

To structure research findings for an ADR or documentation spike, collect relevant articles and normalize them into an evidence pool. This structured cache of Markdown sources can be easily synthesized and referenced during your documentation process.

Does this evidence collection approach require any external dependencies?▼

No, this approach to building evidence pools requires no external dependencies. It operates independently to gather sources from web searches, URLs, local files, and media, normalizing content into Markdown without needing additional packages.

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