community-query

name	community-query
description	Query patterns for non-academic CS sources — Hacker News (Algolia), Reddit, Stack Exchange. Reference for the research-community subagent. Covers endpoints, query syntax, curated subreddits, and User-Agent requirements.
user-invocable	false

Community Query Reference

Three sources, all HTTP+JSON, no auth required for read access.

Source	Best for
Hacker News (Algolia)	Tech news, launch announcements, practitioner debates
Reddit	Long-form practitioner discussion, subreddit-specific expertise
Stack Exchange	Concrete technical Q&A with vetted answers

---

Hacker News (via Algolia)

Base: https://hn.algolia.com/api/v1

Auth: none. Generous rate limits (~10k/hour shared).

Search

GET /search?query=<topic>&tags=story&hitsPerPage=25
GET /search?query=<topic>&tags=(story,comment)&numericFilters=created_at_i>1735689600
GET /search_by_date?query=<topic>&tags=story  # most recent first

Tags:

• story — submissions
• comment — comments
• poll, pollopt, show_hn, ask_hn
• author_<username> — by author
• (story,poll) — OR within parens

Response shape:

{
  "hits": [
    {
      "objectID": "12345678",
      "title": "...",
      "url": "https://...",
      "author": "pg",
      "points": 234,
      "num_comments": 89,
      "created_at_i": 1735689600,
      "story_text": "...",  // for Ask/Show HN
      "_highlightResult": {...}
    }
  ],
  "nbHits": 4567,
  "page": 0
}

Companion URLs

For story objectID=12345678:

• HN page: https://news.ycombinator.com/item?id=12345678
• Algolia thread (with comments): https://hn.algolia.com/api/v1/items/12345678 — full nested comment tree

Useful filters

• numericFilters=points>50 — only well-upvoted
• numericFilters=num_comments>20 — only discussed
• numericFilters=created_at_i>1735689600 — date floor (Unix timestamp)

---

Reddit

Base: https://www.reddit.com (or https://old.reddit.com)

Auth: optional. Without auth: ~60 req/min; MUST send a User-Agent header like User-Agent: claude-code-research/1.0 (by [e-mail]). Without UA you get blocked.

Search across all subreddits

GET /search.json?q=<query>&sort=relevance&limit=25&t=year

sort: relevance | hot | top | new | comments t (when sort=top): hour | day | week | month | year | all

Search within a subreddit

GET /r/<subreddit>/search.json?q=<query>&restrict_sr=on&sort=top&t=year&limit=25

Curated CS subreddits (by topic)

Subreddit	Best for
r/MachineLearning	ML/AI papers, models, debates (academic-leaning)
r/LocalLLaMA	Open-source LLMs, quantization, inference
r/programming	General programming news
r/ExperiencedDevs	Senior-eng practitioner perspective
r/AskComputerScience	Educational Q&A
r/cscareerquestions	Industry signal, hiring, salaries
r/learnprogramming	Beginner pain points (useful for "what's confusing?")
r/rust	Rust-specific
r/cpp	C++-specific
r/golang	Go-specific
r/Python	Python-specific
r/javascript / r/node	JS/Node
r/devops	Infra, CI/CD, observability
r/kubernetes	K8s
r/databases	DB engineering
r/PostgreSQL	Postgres
r/sysadmin	Ops, real-world deployments
r/netsec	Security research
r/ReverseEngineering	RE, malware analysis
r/compsci	Theory, algorithms
r/algorithms	Algo discussion
r/embedded	Embedded systems
r/MachineLearningResearch	More technical than r/ML

Response shape

{
  "data": {
    "children": [
      {
        "data": {
          "id": "abc123",
          "title": "...",
          "selftext": "...",
          "subreddit": "MachineLearning",
          "author": "...",
          "score": 234,
          "num_comments": 89,
          "created_utc": 1735689600,
          "permalink": "/r/MachineLearning/comments/abc123/title/",
          "url": "https://..."
        }
      }
    ]
  }
}

Comments for a thread

GET /r/<subreddit>/comments/<id>.json?limit=50&depth=2

Returns array [post, comments_tree]. Walk data.children[].data.body for top-level + replies.

Filtering anti-noise

• score > 20 filters out un-engaged threads.
• num_comments > 5 filters out solo-posts.
• Skip subreddits with over18: true if topic is general.

---

Stack Exchange API

Base: https://api.stackexchange.com/2.3

Auth: API key optional (key gets 10k req/day; no key gets 300/day per IP). No key needed for casual use; if hitting limits, register an app.

Query parameter site= is required.

Search questions

GET /search/advanced?order=desc&sort=votes&q=<topic>&site=stackoverflow&pagesize=25&filter=withbody

Filters control which fields come back. withbody includes the question body. Custom filter strings are pre-built — withbody is the safe default.

Sites that matter for CS

site=	Topic
stackoverflow	Programming Q&A (the big one)
serverfault	Sysadmin / infra
superuser	Power users
cs.stackexchange	CS theory and education
cstheory.stackexchange	Theoretical CS research
math.stackexchange	Math (often touches CS theory)
security.stackexchange	InfoSec
reverseengineering.stackexchange	RE
codereview.stackexchange	Code quality
softwareengineering.stackexchange	SE practices
ai.stackexchange	AI/ML Q&A
datascience.stackexchange	Data science

For multi-site sweeps, run the same query across 3–5 relevant sites and merge by canonical question URL.

Response shape

{
  "items": [
    {
      "question_id": 12345,
      "title": "...",
      "body": "...",  // when filter=withbody
      "tags": ["python", "asyncio"],
      "score": 87,
      "answer_count": 4,
      "view_count": 12345,
      "is_answered": true,
      "accepted_answer_id": 67890,
      "creation_date": 1735689600,
      "owner": {"display_name": "..."},
      "link": "https://stackoverflow.com/questions/12345/..."
    }
  ],
  "has_more": true,
  "quota_remaining": 9876
}

Get answers for a question

GET /questions/{ids}/answers?site=stackoverflow&filter=withbody&order=desc&sort=votes

Useful filters

• min=10 (with sort=votes) — only well-voted questions
• tagged=python;asyncio (semicolons OR; commas AND)
• accepted=True — only questions with accepted answers (signal for quality consensus)
• fromdate= / todate= — Unix timestamps

---

jq snippets

# HN: extract well-engaged stories
jq '.hits[] | select(.points > 50) | {title, url, points, comments: .num_comments}'

# Reddit: top threads with score and url
jq '.data.children[].data | {title, score, comments: .num_comments, url, permalink: ("https://www.reddit.com" + .permalink)}'

# Stack Exchange: questions with accepted answers, sorted by score
jq '.items[] | select(.is_answered) | {title, score, link, answers: .answer_count, tags: (.tags | join(","))}'

---

Output format expectation (research-community subagent writes these)

Per source-hit, write a findings/<source>-<id>.md with:

• Frontmatter: id, source, url, title, score_or_points, engagement (comment count), created_at, tags (if applicable), relevance_self_score
• Body: 2-4 sentence summary of what the thread/question is asserting + 1-3 quoted/paraphrased key claims with author attribution

These then feed into stage 5 critique alongside paper-derived findings.