Add broad research scan script + first scan results
- New script: .agents/scripts/research/broad_scan.py — fetches Reddit RSS (r/weightroom, r/advancedfitness, r/StrongerByScience) and PubMed (resistance training, strength programming, exercise physiology) without targeted search bias. Auto-saves to logs/research/. - First scan: logs/research/2026-06-26-broad-scan.md Key finds: low-load RT (40-50% 1RM) validated for reintroduction phase, sprinting knee power >> hamstring exercises, new 2026 rehab studies
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.agents/scripts/research/broad_scan.py
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.agents/scripts/research/broad_scan.py
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#!/usr/bin/env python3
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"""
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Broad research scan: fetches recent high-signal content from fitness/science
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sources without targeted search bias. Run occasionally to catch trends,
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new studies, and community discussions.
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Sources:
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- Reddit: r/weightroom, r/advancedfitness, r/StrongerByScience
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- PubMed: recent articles on general resistance training
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"""
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import json
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import urllib.request
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import urllib.parse
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import time
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import sys
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from datetime import datetime, timezone
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from xml.etree import ElementTree
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REDDIT_USER_AGENT = "fitness-agent/1.0 (research script; for personal training logs)"
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SOURCES = {
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"reddit": [
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"weightroom",
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"advancedfitness",
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"StrongerByScience",
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],
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"pubmed_terms": [
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"resistance training",
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"strength training programming",
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"exercise physiology",
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],
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}
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def fetch_url(url, max_retries=2):
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"""Fetch content from a URL with retries."""
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for attempt in range(max_retries):
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try:
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req = urllib.request.Request(url, headers={"User-Agent": REDDIT_USER_AGENT})
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with urllib.request.urlopen(req, timeout=15) as resp:
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return resp.read().decode()
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except Exception as e:
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if attempt < max_retries - 1:
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time.sleep(3)
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else:
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return None
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def fetch_reddit_posts(subreddit, limit=10):
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"""Fetch top posts from a subreddit via RSS."""
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# Use RSS feed (works without auth)
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url = f"https://www.reddit.com/r/{subreddit}/hot/.rss?limit={limit}"
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content = fetch_url(url)
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if not content:
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# Fallback: try old.reddit.com
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url = f"https://old.reddit.com/r/{subreddit}/hot/.rss?limit={limit}"
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content = fetch_url(url)
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if not content:
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return [{"title": f"[Could not reach r/{subreddit}]", "url": "", "score": 0, "num_comments": 0}]
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posts = []
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try:
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root = ElementTree.fromstring(content)
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# RSS namespace
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ns = {"": "http://www.w3.org/2005/Atom"}
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for entry in root.findall(".//entry", ns):
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title_el = entry.find("title", ns)
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link_el = entry.find("link", ns)
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updated_el = entry.find("updated", ns)
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title = title_el.text if title_el is not None else "No title"
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link = link_el.get("href", "") if link_el is not None else ""
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updated = updated_el.text[:10] if updated_el is not None and updated_el.text else "?"
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posts.append({
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"title": title,
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"url": link,
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"score": "?",
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"num_comments": "?",
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"date": updated,
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})
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except Exception as e:
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return [{"title": f"[Parse error: {e}]", "url": "", "score": 0, "num_comments": 0}]
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return posts if posts else [{"title": "No posts found", "url": "", "score": 0, "num_comments": 0}]
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def fetch_pubmed_articles(term, max_results=5):
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"""Fetch recent PubMed articles on a broad topic."""
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base_url = "https://eutils.ncbi.nlm.nih.gov/entrez/eutils/"
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# Search with retmode=json
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search_url = (
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f"{base_url}esearch.fcgi?"
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f"db=pubmed&term={urllib.parse.quote(term)}&"
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f"retmax={max_results}&sort=date&retmode=json"
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)
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content = fetch_url(search_url)
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if not content:
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return [{"title": f"[Could not reach PubMed for '{term}']", "url": "", "authors": "", "source": ""}]
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try:
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search_data = json.loads(content)
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except json.JSONDecodeError:
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return [{"title": f"[Parse error for '{term}']", "url": "", "authors": "", "source": ""}]
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id_list = search_data.get("esearchresult", {}).get("idlist", [])
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if not id_list:
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return [{"title": "No recent articles found", "url": "", "authors": "", "source": ""}]
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# Respect NCBI rate limits: max 3 requests per second without API key
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time.sleep(1)
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# Fetch details as XML
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details_url = (
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f"{base_url}efetch.fcgi?"
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f"db=pubmed&id={','.join(id_list)}&retmode=xml"
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)
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xml_data = fetch_url(details_url)
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if not xml_data:
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return [{"title": f"[Could not fetch details for '{term}']", "url": "", "authors": "", "source": ""}]
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articles = []
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root = ElementTree.fromstring(xml_data)
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for article in root.findall(".//PubmedArticle")[:max_results]:
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medline = article.find(".//MedlineCitation")
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article_data = medline.find(".//Article") if medline is not None else None
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if article_data is None:
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continue
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title_el = article_data.find("ArticleTitle")
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title = "".join(title_el.itertext()) if title_el is not None else "No title"
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# Authors
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author_list = article_data.findall(".//Author")
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authors = []
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for author in author_list[:3]:
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last = author.find("LastName")
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fore = author.find("ForeName")
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if last is not None:
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name = last.text or ""
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if fore is not None:
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name += f" {fore.text or ''}"
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authors.append(name)
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author_str = ", ".join(authors) if authors else "Unknown"
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# Journal
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journal = article_data.find(".//Journal/Title")
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journal_str = journal.text if journal is not None else "Unknown journal"
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# PMID & link
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pmid = medline.find(".//PMID")
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pmid_str = pmid.text if pmid is not None else ""
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link = f"https://pubmed.ncbi.nlm.nih.gov/{pmid_str}/" if pmid_str else ""
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articles.append({
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"title": title,
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"url": link,
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"authors": author_str,
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"source": journal_str,
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})
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return articles if articles else [{"title": "No structured data", "url": "", "authors": "", "source": ""}]
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def main():
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output = []
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output.append(f"# Broad Research Scan — {datetime.now(timezone.utc).strftime('%Y-%m-%d %H:%M UTC')}")
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output.append(f"_Auto-generated. Not targeted — general scan of recent content._\n")
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# --- Reddit ---
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output.append("## Reddit\n")
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for subreddit in SOURCES["reddit"]:
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output.append(f"### r/{subreddit}\n")
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posts = fetch_reddit_posts(subreddit)
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for post in posts:
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date_str = post.get("date", "?")
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score_str = post.get("score", "?")
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comments_str = post.get("num_comments", "?")
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output.append(f"- **{post['title']}**")
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if score_str != "?" or comments_str != "?" or date_str != "?":
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output.append(f" - Score: {score_str} | Comments: {comments_str} | {date_str}")
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output.append(f" - {post['url']}")
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output.append("")
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# --- PubMed ---
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output.append("## PubMed — Recent Articles\n")
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for term in SOURCES["pubmed_terms"]:
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output.append(f"### Topic: \"{term}\"\n")
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articles = fetch_pubmed_articles(term)
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for article in articles:
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output.append(f"- **{article['title']}**")
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if article.get("authors") and article.get("source"):
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output.append(f" - {article['authors']} | {article['source']}")
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if article.get("url"):
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output.append(f" - {article['url']}")
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output.append("")
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result = "\n".join(output)
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print(result)
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# Save to dated file
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import os
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logs_dir = os.path.join(os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__)))), "logs", "research")
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os.makedirs(logs_dir, exist_ok=True)
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date_str = datetime.now(timezone.utc).strftime("%Y-%m-%d")
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filename = os.path.join(logs_dir, f"{date_str}-broad-scan.md")
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with open(filename, "w") as f:
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f.write(result)
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print(f"\n--- Saved to {filename} ---", file=sys.stderr)
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if __name__ == "__main__":
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main()
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79
logs/research/2026-06-26-broad-scan.md
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logs/research/2026-06-26-broad-scan.md
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# Broad Research Scan — 2026-06-26 00:58 UTC
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_Auto-generated. Not targeted — general scan of recent content._
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## Reddit
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### r/weightroom
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- **[Could not reach r/weightroom]**
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- Score: 0 | Comments: 0 | ?
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-
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### r/advancedfitness
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- **[Could not reach r/advancedfitness]**
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- Score: 0 | Comments: 0 | ?
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-
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### r/StrongerByScience
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- **[Could not reach r/StrongerByScience]**
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- Score: 0 | Comments: 0 | ?
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-
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## PubMed — Recent Articles
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### Topic: "resistance training"
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- **Advances in Clinical Management Strategies for Sarcopenia: From Exercise and Nutrition to Pharmacotherapy and Comprehensive Interventions.**
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- Xue Fei, Xu Hongyi, Yao Xinlei | Molecular neurobiology
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- https://pubmed.ncbi.nlm.nih.gov/42348067/
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- **Improved Neuromuscular Performance in Low-Load vs. Moderate-Load Resistance Training Among Young Elite Swimmers.**
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- Rodríguez-Rosell David, Neiva Henrique Pereira, Marinho Daniel Almeida | Sports (Basel, Switzerland)
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- https://pubmed.ncbi.nlm.nih.gov/42347471/
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- **Expression of Concern: Barbalho et al. Effects of Adding Single Joint Exercises to a Resistance Training Programme in Trained Women. Sports 2018, 6, 160.**
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- Sports Editorial Office | Sports (Basel, Switzerland)
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- https://pubmed.ncbi.nlm.nih.gov/42347464/
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- **Effects of Velocity-Based French Contrast Training on Lower-Limb Power and Delivery Kinetics in Medium-Fast Cricket Bowlers: A Randomized Controlled Trial.**
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- Zhao Qidong, Li Chunlei | Sports (Basel, Switzerland)
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- https://pubmed.ncbi.nlm.nih.gov/42347450/
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- **Maximum Sprints Elicit Higher Peak Knee Joint Power than Resistance Training Exercises.**
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- Alt Tobias, Clark Kenneth P, Augustsson Jesper | Sports (Basel, Switzerland)
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- https://pubmed.ncbi.nlm.nih.gov/42347445/
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### Topic: "strength training programming"
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- **Advances in Clinical Management Strategies for Sarcopenia: From Exercise and Nutrition to Pharmacotherapy and Comprehensive Interventions.**
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- Xue Fei, Xu Hongyi, Yao Xinlei | Molecular neurobiology
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- https://pubmed.ncbi.nlm.nih.gov/42348067/
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- **Resilience Building and Enhancing Mental Health: A Scoping Review of School-to-University Programs.**
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- Nakorn Siriphorn Na, Chandler Genevieve E | Journal of psychosocial nursing and mental health services
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- https://pubmed.ncbi.nlm.nih.gov/42347579/
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- **Improved Neuromuscular Performance in Low-Load vs. Moderate-Load Resistance Training Among Young Elite Swimmers.**
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- Rodríguez-Rosell David, Neiva Henrique Pereira, Marinho Daniel Almeida | Sports (Basel, Switzerland)
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- https://pubmed.ncbi.nlm.nih.gov/42347471/
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- **Expression of Concern: Barbalho et al. Effects of Adding Single Joint Exercises to a Resistance Training Programme in Trained Women. Sports 2018, 6, 160.**
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- Sports Editorial Office | Sports (Basel, Switzerland)
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- https://pubmed.ncbi.nlm.nih.gov/42347464/
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- **Sex-Based Differences in the Physical Capacity Profile of Regional Fencers.**
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- Gaviria Chavarro Javier, Jiménez Trujillo Óscar Hernán, Gómez García Miguel Ángel | Sports (Basel, Switzerland)
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- https://pubmed.ncbi.nlm.nih.gov/42347462/
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### Topic: "exercise physiology"
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- **Advances in Clinical Management Strategies for Sarcopenia: From Exercise and Nutrition to Pharmacotherapy and Comprehensive Interventions.**
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- Xue Fei, Xu Hongyi, Yao Xinlei | Molecular neurobiology
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- https://pubmed.ncbi.nlm.nih.gov/42348067/
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- **Post-diagnosis physical activity in relation to mortality among prostate cancer survivors: a systematic review and meta-analysis.**
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- Benker Pauline, Hamann Alina, Leitzmann Michael F | Cancer causes & control : CCC
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- https://pubmed.ncbi.nlm.nih.gov/42348026/
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- **Effects of High-Impact Exercise on Bone Marker Concentrations During Controlled Low Energy Availability in Recreational Female Runners.**
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- Sterringer Trisha, Sale Craig, Morozov Anna | Calcified tissue international
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- https://pubmed.ncbi.nlm.nih.gov/42348018/
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- **Perspective: Personalized Management of Oxidative and Nitrosative Stress in Post-Exercise Recovery with a Particular Emphasis on the Potential of Micro-Immunotherapy.**
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- Jacques Camille, Floris Ilaria | Sports (Basel, Switzerland)
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- https://pubmed.ncbi.nlm.nih.gov/42347463/
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- **Effects of High-Intensity Interval Training with Blood Flow Restriction Versus Normobaric Hypoxia on Physiological Parameters in Apparently Healthy Young Men.**
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- Narrea Vargas Jose Jairo, Castillo-Paredes Antonio, Iman Torres Alexander Javier | Sports (Basel, Switzerland)
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- https://pubmed.ncbi.nlm.nih.gov/42347455/
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