user-layer

Use this skill when the user wants a UserLayer report for an App Store or Google Play app, including full analysis, polling, and follow-up questions grounded in real reviews. Trigger it for competitor review analysis, user pain point extraction, segment discovery, and opportunity validation tasks.

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Install skill "user-layer" with this command: npx skills add houyongsheng/userlayer

UserLayer

UserLayer turns App Store and Google Play reviews into structured research outputs:

  • pain points
  • user segments
  • market opportunities
  • follow-up answers grounded in cited reviews

Use the bundled wrappers in scripts/main.py. Do not hand-roll raw HTTP requests when this skill is available.

Use This Skill When

  • The user gives you an App Store or Google Play URL and wants review-backed insights.
  • The user wants to ask follow-up questions about a completed full analysis.

Prerequisites

  • API_KEY must be set to a valid UserLayer API key.
  • LAUNCHBASE_API_URL is optional. Default: https://lb-api.workflowhunt.com

Credentials and Host

  • Primary credential: API_KEY
  • Default API host: https://lb-api.workflowhunt.com
  • API_KEY should be scoped only for UserLayer API access and treated as a paid production credential.

Available Wrappers

  • analyze(app_url: str, max_reviews: int | None = None)
  • check_status(analysis_id: str)
  • query(pain_point_id: str, question: str)

Typical Flow

  1. Call analyze() to start a full async run.
  2. Poll with check_status() until the report is complete.
  3. Read the returned pain_points.
  4. Use a pain_point.id with query() for targeted follow-up questions.

You do not need a separate preview step. analyze() is the main public entry point.

Pricing Baseline

  • One analyze() run costs $2.99 and includes retrieval plus full analysis of the latest 100 reviews.
  • If max_reviews is raised above 100, extra reviews are billed as add-ons at $0.01 per extra review.
  • query() is billed at $0.01 / 1K tokens.

Key Response Shapes

  • analyze() starts an async job and returns a lightweight payload with:
    • success
    • data.analysis_id
    • data.status
  • check_status() returns the full completed report when ready, including:
    • data.pain_points
    • data.user_segments
    • data.opportunities
    • sources
    • usage
  • query() returns a follow-up answer for a specific pain point, including:
    • data.answer
    • data.confidence
    • sources
    • usage

Treat pain_points[].id from a completed analysis as the required input for query().

Operating Rules

  • Default review count is 100 latest reviews.
  • analyze() includes retrieval and analysis of 100 latest reviews by default.
  • If max_reviews is raised above 100, extra reviews are billed as add-ons.
  • analyze() is asynchronous and returns an analysis_id; poll with check_status().
  • Use query() only after a completed full analysis returns a valid pain_point_id.
  • Treat sources and cited review evidence as the source of truth.
  • If DATA_INDEX_NOT_FOUND is returned, rerun a full analysis before querying again.

Source Transparency

This detail page is rendered from real SKILL.md content. Trust labels are metadata-based hints, not a safety guarantee.

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