| name | reddit-research |
| description | Reddit research workflow for finding, scoring, shortlisting, and learning from subreddit posts and comments for brand or lead discovery. Use when building or operating a Reddit research pipeline, tuning discovery/scoring rules, organizing brand-specific heuristics, or packaging repeatable Reddit research into a reusable skill. |
Reddit Research
Use this skill to turn Reddit into a repeatable signal pipeline.
Workflow
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Discover
- Pull from target subreddits first.
- Keep discovery broad enough to capture candidates, but narrow enough to avoid Reddit-wide noise.
- Apply freshness and subreddit filters early.
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Filter
- Remove obvious junk before scoring.
- Apply hard filters for job posts, irrelevant domains, avoid-list topics, and duplicates.
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Score
- Score candidates by brand fit, intent, capability match, and risk.
- Keep brand-specific weights separate from shared rules.
- Emit a reason trail for every score.
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Shortlist
- Select the best candidates after filtering.
- Do not let raw top-score ranking bypass hard filters.
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Learn
- Record what converted, what was ignored, and what was false-positive noise.
- Update brand profiles and weights from outcomes.
- Prefer profile updates over ad hoc rule churn.
Operating rules
- Keep discovery, scoring, and learning separate.
- Prefer brand-specific profiles over global heuristics.
- Explain every shortlist decision.
- Treat filters as safety rails, not the learning system.
Resources
references/brand-profiles.md — brand-specific behavior, weights, and profile shapereferences/scoring-rules.md — scoring dimensions and hard filter orderreferences/intent-patterns.md — common Reddit intent buckets and signalsreferences/examples.md — examples of good, bad, and borderline postsscripts/discover.py — discovery helperscripts/score.py — scoring and ranking helperscripts/cleanup.py — dedupe and inbox cleanup helperscripts/report.py — summary and reason-trail output helper
