last30days-skill

name	last30days-skill
description	AI agent skill for cross-platform topic research and summarization across Reddit, X, YouTube, HN, Polymarket, and the web
version	1.0.0
author	Hermes Agent
license	MIT
platforms	["linux","macos","windows"]
metadata	{"hermes":{"tags":["ai-agent","research","summarization","cross-platform","real-time"],"related_skills":["web-research","youtube-content","polymarket"]}}

last30days-skill

An AI agent skill that researches any topic across multiple platforms and synthesizes a grounded summary with citations.

Prerequisites

• Python 3.8+
• pip
• API keys for desired platforms (optional but recommended for full functionality)

Installation

pip install last30days-skill

Usage

Basic Research

from last30days_skill import Last30DaysSkill

skill = Last30DaysSkill()
result = await skill.research("latest developments in AI agents")

print(result.summary)
print(result.sources)

With Platform Filters

# Research only on specific platforms
result = await skill.research(
    "quantum computing breakthroughs",
    platforms=["reddit", "twitter", "arxiv"]
)

Custom Time Range

# Research from the last 7 days instead of 30
result = await skill.research(
    "AI regulation news",
    days=7
)

Common Pitfalls

1. Rate limiting: Some platforms have strict rate limits. Implement exponential backoff.
2. API costs: Some data sources may incur costs. Monitor usage.
3. Data quality: Cross-reference sources for accuracy. Not all sources are equally reliable.
4. Freshness vs depth: Recent data may lack context. Balance recency with comprehensiveness.

Verification

# Test installation
python -c "from last30days_skill import Last30DaysSkill; print('OK')"

# Run a simple test
python -c "
import asyncio
from last30days_skill import Last30DaysSkill

async def test():
    skill = Last30DaysSkill()
    result = await skill.research('test topic', days=1)
    print(f'Sources found: {len(result.sources)}')
    print(f'Summary length: {len(result.summary)}')

asyncio.run(test())
"