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# mvanhorn/last30days-skill
## Metadata
- **Full name:** mvanhorn/last30days-skill
- **Description:** AI agent skill that researches any topic across Reddit, X, YouTube, HN, Polymarket, and the web - then synthesizes a grounded summary
- **Stars:** 20,980
- **Last pushed:** 2026-04-11
- **License:** MIT
- **Topics:** ai-skill, claude-code, deep-research, reddit, research, social-media, twitter, youtube, web-search, polymarket, hackernews
## Archetype
**utility-with-skill** - Single-purpose research aggregation skill with a Python backend. Searches 13+ platforms in parallel, scores results by engagement metrics (upvotes, likes, real money), and synthesizes into grounded summaries.
## Structure
```
SKILL.md # Runtime skill spec (source of truth)
skills/last30days/ # Skill definition
agents/ # Agent configurations
hooks/ # Hook definitions
scripts/ # Python research engine
vendor/ # Vendored dependencies
tests/ # Test suite
fixtures/ # Test fixtures
```
## Extractable Value
### Processes (specializations/)
1. **multi-source-research-synthesis** - The v3 research methodology is interesting: intelligent pre-research (entity resolution before search), parallel multi-source search, engagement-weighted scoring (upvotes > editorial SEO), cross-source cluster merging (dedup same story across platforms), synthesis with source citations. This is a research methodology pattern, not just a tool. **Placement: specializations/shared/multi-source-research**
### Plugin Ideas
1. **last30days-integration** - A babysitter marketplace plugin that wraps /last30days as a research task. The pre-meeting research, competitive analysis, and trend monitoring use cases map well to babysitter orchestration tasks. The plugin would provide a `research` task type that delegates to the last30days engine. However, this is borderline since it requires the user to have last30days installed separately.
### SKIP
- The actual platform-specific API integrations (Reddit JSON, X API, YouTube transcripts) - tool-specific implementation details
- ELI5 mode - presentation concern, not methodology
## Processes
### 1. Multi-Source Research Synthesis
- **Source**: V3 research methodology with intelligent pre-research and engagement-weighted scoring
- **Placement**: `specializations/shared/multi-source-research-synthesis.js`
- **Description**: Research methodology pattern: entity resolution before search → parallel multi-source search → engagement-weighted scoring (upvotes > editorial SEO) → cross-source cluster merging → synthesis with source citations.
## Plugin Ideas
- **Last30Days Research Integration**: Babysitter marketplace plugin that wraps /last30days as a research task for pre-meeting research, competitive analysis, and trend monitoring.
## Library Mapping
| Extractable Process | Library Status | Action | Existing Path | Target Placement |
|-------------------|----------------|--------|---------------|------------------|
| Multi-Source Research Synthesis | NEW | Research methodology: entity resolution → parallel search → engagement scoring → cluster merging → citation synthesis | - | specializations/shared/multi-source-research-synthesis.js |
| Engagement-Weighted Content Scoring | NEW | Content ranking algorithm using engagement metrics (upvotes, likes, real money) over editorial SEO | - | specializations/shared/engagement-weighted-content-scoring.js |
| Cross-Source Content Clustering | NEW | Deduplication and clustering of same stories across multiple platforms and sources | - | specializations/shared/cross-source-content-clustering.js |
## Plugin Marketplace Mapping
| Plugin Idea | Marketplace Status | Action | Existing Plugin | Target Placement |
|-------------|-------------------|--------|-----------------|------------------|
| Last30Days Research Integration | NEW | Multi-platform research aggregation with engagement scoring and synthesis | - | plugins/a5c/marketplace/blueprints/last30days-research-integration/ |
## Priority Assessment
**LOW-MEDIUM** - The multi-source research synthesis methodology is conceptually interesting but the actual value is tightly coupled to the platform integrations (API keys, browser sessions). The methodology pattern (entity-resolve -> parallel-search -> engagement-score -> cluster-merge -> synthesize) could inform a generic research process, but it's thin without the platform access. Better as inspiration than a direct port.
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