skill-ugc-discovery · Brand UGC Discovery
skill-ugc-discovery finds user-generated content about a brand or account: it searches fan posts, reviews, mentions, and community discussions, and delivers a list of high-value UGC with source links, sentiment, and suggested engagement actions — plus a separate section for negative feedback with response strategies.
Three discovery paths cover platform search, topic/hashtag monitoring, and community discussion scans. Results are ranked by engagement and quality; when nothing is found, the report says so honestly instead of inventing content.
Example invocation: "Find recent reviews of my product."
Full brief
Positioning
skill-ugc-discovery is the reputation radar for a brand or account: it searches fan content, reviews, mentions, and community discussions tied to the brand, and outputs an actionable UGC list. It answers "who mentioned me, what did they say, and what's worth responding to."
Core capabilities
- Three discovery paths: platform search (keyword combinations across Xiaohongshu, Bilibili, Weibo, Zhihu, Douyin), topic/hashtag monitoring (brand topics and related tags), and community discussion scans (purchase-decision and complaint threads on Zhihu, Tieba).
- Sentiment classification: positive / neutral / negative; separates factual mentions from evaluative content.
- High-value UGC shortlist: ranked by engagement and quality, each with a source link and suggested action.
- Negative feedback, separate: sorted by severity with constructive response strategies — never swept aside.
- Engagement advice: concrete moves per item (repost with thanks, comment, collaboration outreach).
- Profile-aware: auto-expands account/brand/product keywords from the creator profile; prioritizes active platforms and flags UGC from the target audience.
- Honesty rules: every item carries a source link; empty searches report "no UGC found" — never fabricated; search scope and data limits are stated explicitly.
Workflow
- Confirm keywords:
brand_keywords; expand from profile when available - Set scope: platforms and content-type keyword emphasis
- Run the three paths: platform search → topic/tag monitoring → community scan
- Collect: summaries and engagement data from high-relevance links
- Deduplicate and classify by sentiment
- Rank: shortlist high-value UGC; list negatives separately
- Output the report to
outputs/
Inputs & outputs
| Input | Required | Notes |
|---|---|---|
| brand_keywords | Yes | Brand/account name(s), comma-separated |
| platforms | No | Focus platforms (Xiaohongshu/Bilibili/Weibo/Zhihu/Douyin); default: all |
| content_type | No | reviews / mentions / fan_art / complaints / all; default: all |
| time_range | No | recent / this_month / this_quarter; default: recent |
Output: UGC discovery report (overview, high-value table, negative-feedback table, engagement advice) in outputs/.
Boundaries with adjacent skills
- skill-news-intelligence: aggregates industry media — the industry view; this skill covers content directly tied to the brand itself.
- skill-algorithm-updates: tracks platform mechanics; this skill tracks brand mentions and reputation.
Fit
- Brands and accounts listening to real fan reviews and community sentiment
- Post-launch monitoring of user discussion
- Support and PR teams catching and responding to negative feedback
- Content ops mining fan posts worth reposting or collaborating on
Before you start
- No API key needed; runs on web search and fetching.
- Provide the brand/account name (auto from a profile when available).
- Web search has freshness and coverage limits — the report states its scope explicitly; sentiment labels are analytical, kept separate from the sourced facts.
skill-ugc-discovery is part of the Aiglade Skill library. Invoke it from the Aiglade chat box in plain language.