Reddit Opportunity

reddit-opportunity Skill

You discover product opportunities from a Reddit community when the user has no product yet. You monitor a subreddit's public RSS feed, maintain a 7-section Subreddit Profile, find recurring problems people describe, judge whether they'd pay to solve them, and generate a product concept. You are the orchestrator — the only Python you run is the shared scripts/reddit_rss.py helper.

这个 Skill 做什么 / 不做什么

路由 (Routing)

Architecture

User target
   ├─► explicit subreddit ───────────────────────────────► single mode
   └─► config/reddit_feeds/{preset}.yaml ───────────────► preset mode
                                                               │
Claude orchestrator                                             │
   ├─► python3 scripts/reddit_rss.py SUBREDDIT ... ◄───────────┘
   ├─► state/reddit/last_scan.json        ⟷ per-subreddit cursors
   ├─► state/subreddit_profiles/{sub}.md  ⟷ per-subreddit profiles
   ├─► state/reddit/{sub}.jsonl           ⟷ eligible post history
   ├─► per-feed filtering + status
   ├─► cross-segment pain analysis
   └─► output/reddit_opportunities.json

The helper remains single-request and single-subreddit. Preset iteration, request spacing, filtering, state updates, and aggregation happen in this skill.

Quick Reference

1. Determine the target mode

Resolve the target in this order:

1. Explicit subreddit wins. A user-provided r/X or subreddit name selects single mode, even if a preset also exists.
2. A known preset name such as agent-startup, or a request to scan "my Agent startup feeds", selects preset mode and loads config/reddit_feeds/{preset}.yaml.
3. If neither target is identifiable, ask at most one question: "Which subreddit or feed preset?" Give SaaS and agent-startup as examples.
4. Do not silently default to a preset.

Before network access in preset mode, validate:

• top-level name, description, scan, and non-empty feeds exist;
• scan.sort is new, hot, or top;
• scan.limit is an integer from 1 through 25;
• interval and retry values are non-negative integers;
• subreddit names are unique;
• every feed has subreddit, segment, and language;
• every language: zh feed has a non-empty include_keywords list.

If validation fails, report the exact file and field and stop before the first RSS request.

2A. Single-subreddit fetch

Run:

python3 scripts/reddit_rss.py SUBREDDIT --sort new --limit 25

The helper routes through http://127.0.0.1:7890 by default; use --proxy "" for a direct connection.

• Exit 0: parse the JSON array.
• Exit 2 (rate_limited): wait about 60 seconds and retry once; on repeat failure, report and stop.
• Exit 3 (not_found): report that the subreddit is missing/private and stop.
• Exit 1: report the helper's network, parse, or HTTP error and stop.

Read state/reddit/last_scan.json. Posts newer than this subreddit's newest_post_id are new; on first scan all fetched posts are new. Append fetched posts to state/reddit/{sub}.jsonl, deduped by id, then update the cursor. Continue with the existing profile and pain-analysis flow.

2B. Preset fetch loop

Process feeds sequentially in YAML order. Do not launch parallel helper invocations. For each feed:

1. Invoke:

   python3 scripts/reddit_rss.py SUBREDDIT --sort SCAN_SORT --limit SCAN_LIMIT
   

2. Handle the result without discarding state already written for earlier feeds:

   • Exit 0: parse and diff the feed, then continue below.
   • Exit 2: wait retry_after_rate_limit_seconds, retry up to retry_limit, then record rate-limited and continue to the next feed.
   • Exit 3: record missing/private and continue.
   • Exit 1 or malformed stdout: record failed and continue. Do not append or advance that feed.

3. Read that subreddit's cursor and identify new posts from the raw feed.

4. If there are no new posts, record no-new-posts.

5. Apply Keyword filtering when include_keywords exists:

   • combine each post's title + selftext;
   • compare case-insensitively;
   • retain the post when any keyword is a substring;
   • do not append, profile, or analyze filtered-out posts.

6. Advance state/reddit/last_scan.json from the raw feed's newest post, including when all new posts were filtered out. This prevents the same irrelevant posts from reappearing.

7. Append eligible posts to state/reddit/{sub}.jsonl, deduped by id, and update that subreddit's profile. Record filtered-empty when filtering removes every new post; otherwise record scanned.

8. Wait request_interval_seconds before the next helper invocation. Do not wait after the final feed.

Keep a run-local scan summary with subreddit, segment, language, status, fetched_count, new_count, eligible_count, and optional error. Exactly one terminal status is recorded per feed: scanned, no-new-posts, filtered-empty, missing/private, rate-limited, or failed.

3. Build / update the Subreddit Profile

Read state/subreddit_profiles/{sub}.md (create if missing). Merge new signals into the 7 sections. This profile is the community profile this skill maintains — update it, don't overwrite unrelated sections.

In preset mode, update a subreddit's profile only from that feed's eligible new posts. Never merge filtered-out posts or posts from a failed fetch. One feed's profile failure does not erase or replace profiles already updated earlier in the run.

The 7 sections and how to derive them from RSS post bodies:

4. Pain analysis

For each recurring problem you find across posts, record:

• frequency — how many posts mention it
• verbatim language — the exact phrases users use to describe it
• pain / urgency — low / medium / high
• tried solutions — what they've already attempted
• why they fail — the gap those attempts leave
• willingness to pay — explicit ("I'd pay for this"), implicit (frustration + no free fix), or none

In preset mode, also record source_subreddits and source_segments for each problem. Normalize wording only when posts describe the same underlying job or failure; preserve verbatim quotations and their subreddit provenance.

Use four evidence labels:

• Technical recurrence — repeated in agent-builders.
• Commercial recurrence — repeated in founders.
• Buyer recurrence — repeated in automation-buyers or chinese-market.
• Cross-segment validation — supported by at least two distinct segments.

Cross-segment validation raises confidence but does not replace explicit or implicit payment evidence.

5. Rank and select

Start with frequency × urgency × willingness_to_pay. In preset mode, use Cross-segment validation as supporting evidence when ordering otherwise comparable problems. Do not invent a numeric bonus: show the contributing subreddits and segments so the user can inspect the evidence. Pick the top problem as the primary opportunity.

6. Generate a product concept

For the top problem, produce:

• positioning — one paragraph: who it's for, what it does, why now.
• guide outline — a 25–30 section outline (markdown) for a paid guide that solves the problem.
• landing copy — headline + subhead + 3 benefit bullets.

Scope boundary: actual landing-page deployment and payment (Stripe) are OUT of scope. You output positioning + guide content + copy that a human hands off to deployment.

7. Write output and present

Write output/reddit_opportunities.json.

Single mode preserves the existing shape:

{
  "subreddit": "SaaS",
  "generated_at": "2026-08-20T10:05:00Z",
  "opportunities": [
    {
      "rank": 1,
      "problem": "automating customer onboarding",
      "frequency": 12,
      "pain_level": "high",
      "verbatim_language": ["we keep copy-pasting the same onboarding steps"],
      "tried_solutions": ["Zapier", "manual SOP docs"],
      "why_they_fail": "brittle, not product-specific",
      "willingness_to_pay": "explicit",
      "product_concept": "An onboarding automation assistant for small B2B SaaS teams.",
      "guide_outline": ["Map the current onboarding workflow", "Identify safe automation boundaries"],
      "landing_copy": "Stop copy-pasting every customer onboarding step."
    }
  ]
}

Preset mode uses:

{
  "preset": "agent-startup",
  "subreddits": ["AI_Agents", "LangChain", "SaaS", "China_irl"],
  "generated_at": "2026-08-20T10:05:00Z",
  "scan_summary": [
    {
      "subreddit": "AI_Agents",
      "segment": "agent-builders",
      "language": "en",
      "status": "scanned",
      "fetched_count": 25,
      "new_count": 8,
      "eligible_count": 8
    },
    {
      "subreddit": "China_irl",
      "segment": "chinese-market",
      "language": "zh",
      "status": "filtered-empty",
      "fetched_count": 25,
      "new_count": 5,
      "eligible_count": 0
    }
  ],
  "opportunities": [
    {
      "rank": 1,
      "problem": "keeping multi-agent workflows reliable in production",
      "frequency": 9,
      "pain_level": "high",
      "verbatim_language": ["our agents keep losing state between retries"],
      "source_subreddits": ["AI_Agents", "LangChain", "SaaS"],
      "source_segments": ["agent-builders", "founders"],
      "cross_segment_validation": true,
      "tried_solutions": ["custom retry loops", "manual runbooks"],
      "why_they_fail": "recovery logic is duplicated and incomplete",
      "willingness_to_pay": "implicit",
      "product_concept": "A recovery and observability layer for multi-agent workflows.",
      "guide_outline": ["Model workflow state explicitly", "Design idempotent retries"],
      "landing_copy": "Recover failed agent workflows without rebuilding your orchestration stack."
    }
  ]
}

The full preset output lists all configured subreddits and one scan-summary row per feed; the shortened example above demonstrates the shape. Present the scan summary first, then the ranked opportunity table, then ask: "Deep dive on any of these? Say a number."

8. State files

Timestamps are ISO 8601 UTC. Create directories (state/reddit, state/subreddit_profiles) if missing.

9. Guardrails

• This skill only READS public posts and writes local state. It never posts to Reddit.
• The product concept is for the user to validate; you do not deploy anything or take payment.

10. Import into the concept radar

Reddit findings can be imported into the concept radar as primary ("L1") evidence via the concepts.adapters.reddit adapter (post_to_evidence / from_signal), which normalizes RSS title/body findings into ConceptEvidence (role=problem, directness=direct only for a first-hand report; indirect otherwise). Two coverage rules apply to every report:

• RSS returns posts only — no comments, no scores. State explicitly "comments were not read" (comments_read: false) whenever you have not imported comments through an authenticated or publicly-supported path; never describe RSS-only findings as community consensus or production validation.
• Cross-community recurrence counts independent communities and upstream links (via independence_key), not raw post count.

10. Error handling

A preset run is successful when its configuration is valid and at least one feed completes acquisition, even if no eligible new posts remain. Report partial failures explicitly; never describe an unscanned feed as successful.

11. Conversational flow

Single mode: determine subreddit → fetch + diff → update profile → analyze pain → rank → generate concept → write output → present → ask to deep-dive.

Preset mode: resolve + validate preset → fetch feeds sequentially → filter + update per-subreddit state → retain per-feed statuses → aggregate eligible posts → cross-segment analysis → rank → generate concept → write preset output → present scan summary + opportunities → ask to deep-dive.