Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub · Data Analysis
Niche Hunter App Store
NicheHunter Ultra — Headless App Store Market Intelligence engine for OpenClaw (VPS). Detects underserved niches, analyzes competitors, validates monetizatio...
skill openclawclawhub Free
NicheHunter Ultra — Headless App Store Market Intelligence engine for OpenClaw (VPS). Detects underserved niches, analyzes competitors, validates monetizatio...
⬇ 0 downloads ★ 0 stars Unverified but indexed
Install for OpenClaw
Quick setup
- Download the package from Yavira.
- Extract the archive and review SKILL.md first.
- Import or place the package into your OpenClaw setup.
Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- SKILL.md
Validation
- Use the Yavira download entry.
- Review SKILL.md after the package is downloaded.
- Confirm the extracted package contains the expected setup assets.
Install with your agent
Agent handoff
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
- Download the package from Yavira.
- Extract it into a folder your agent can access.
- Paste one of the prompts below and point your agent at the extracted folder.
New install
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
Upgrade existing
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.
Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 0.1.4
Provenance
- Publisher
- chebyte
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
NicheHunter Ultra — Market Intelligence Mode
Designed for: OpenClaw running in a VPS (headless) Telegram interaction No interactive browser required
TOOL REQUIREMENTS
At least ONE of the following must be available: web_search web_fetch curl (HTTP request capability) If none are available → STOP execution.
TOOL PRIORITY ORDER
web_search web_fetch curl (last fallback) Always prefer higher-priority tools when available.
TOOL ADAPTATION LOGIC
If web_search is available: → Use for discovery (charts, competitors, reviews, revenue signals). If web_fetch is available: → Use for structured extraction. If ONLY web_fetch is available: → Fetch official App Store category pages directly. → Extract app listings and derive competitors. If ONLY curl is available: → Perform raw HTTP GET requests. → Parse HTML manually for: App names Rating counts Pricing info → Confirm signals using multiple sources when possible. Never fail solely due to missing web_search.
EXECUTION DISCIPLINE
Max 18 web_search calls Max 20 total URLs analyzed Max 8 competitors per niche Max 20 reviews per app (prioritize 1★ and 3★) No duplicate queries Proxy revenue must be labeled with confidence level No speculation presented as fact
PIPELINE
Category Definition Market Demand Discovery Competitor Intelligence Gap Pattern Extraction Quantitative Scoring MARKET INTELLIGENCE REPORT PRD (after user selection) Each step MUST output a structured checkpoint.
CHECKPOINT FORMAT (STRICT STATE FORMAT)
Checkpoints are for STATE only. No conclusions. No scoring. No hype. Must use this exact structure: --- CHECKPOINT --- Step: {number} Category: {category} Micro-niches identified: • {niche 1} • {niche 2} Competitors analyzed ({count}/{max}): • {App} — {ratings} — {core feature} • {App} — {ratings} — {core feature} Observed signals: • {signal 1} • {signal 2} Gap hypotheses (not conclusions): • {hypothesis 1} • {hypothesis 2} Confidence (intermediate): {Low | Medium | High} Next Step: {next} --- END CHECKPOINT --- The checkpoint must NOT contain: Revenue estimates Final ranking Absolute claims ("NO EXISTE") Scoring values
REVENUE ESTIMATION MODEL
If direct revenue found → use it. If not: Freemium: Estimated installs ≈ ratings × 100 Paid: Estimated installs ≈ ratings × 40 Revenue estimate: installs × 3% × subscription_price Confidence levels: High (direct source) Medium (strong proxy) Low (weak signal) Proxy must always be labeled.
QUANTITATIVE SCORING MODEL
Score each opportunity 0–10: Demand Strength (35%) Gap Clarity (30%) Monetization Viability (20%) Build Simplicity (15%) Weighted Score = (demand × 0.35) + (gap × 0.30) + (monetization × 0.20) + (build × 0.15) Scores must be justified with evidence.
STRICT FORMAT ENFORCEMENT
The assistant is STRICTLY FORBIDDEN from: Using ASCII tables Using column separators like "|" Using monospaced grid layouts Using star-only scoring (⭐⭐⭐) Formatting in horizontal table style No ASCII tables are allowed under any circumstance. Do not use "|" separators. All output must be vertical structured blocks. If a table or ASCII grid appears, the assistant must immediately rewrite the output in vertical structured format.
OUTPUT ENFORCEMENT — TELEGRAM ULTRA FORMAT
Final report MUST use this structure: ════════════════════════════ 📊 MARKET INTELLIGENCE REPORT Category: {Category} Research Confidence: {High | Medium | Low} Competitors Analyzed: {Number} ════════════════════════════ 🥇 OPPORTUNITY #1 — {Name} 🎯 Strategic Positioning {One concise positioning sentence} ━━━━━━━━━━━━━━━━━━━━━━ 📈 Demand Analysis • Top competitors analyzed: {names} • Rating range observed: {range} • Saturation level: {Low | Medium | High} • Demand summary: {1–2 lines} ━━━━━━━━━━━━━━━━━━━━━━ 💰 Monetization Analysis • Pricing benchmark: {range} • Revenue signals: {direct or proxy explanation} • Install estimate logic: {formula used} • Conversion assumption: {percentage} • Estimated revenue range: {range} • Confidence: {High | Medium | Low} ━━━━━━━━━━━━━━━━━━━━━━ 🧩 Gap Intelligence • Repeated complaint themes: {theme 1} {theme 2} • Missing feature overlap: {feature 1} {feature 2} • Structural competitor weakness: {brief explanation} Primary Wedge: {1–2 differentiators} ━━━━━━━━━━━━━━━━━━━━━━ ⚙️ Build Assessment Complexity: {Low | Medium | High} Reasoning: {brief explanation} Risk Level: {Low | Medium | High} Primary Risk: {brief explanation} ━━━━━━━━━━━━━━━━━━━━━━ 📊 Quantitative Scoring Demand Strength: X/10 Gap Clarity: X/10 Monetization Viability: X/10 Build Simplicity: X/10 Weighted Score: X.X / 10 Overall Attractiveness: {Strong | Moderate | Speculative} ════════════════════════════ 🥈 OPPORTUNITY #2 — {Name} (Condensed but same analytical structure) ════════════════════════════ 🥉 OPPORTUNITY #3 — {Name} (Condensed but same analytical structure) ════════════════════════════ 🏁 STRATEGIC CONCLUSION • Why #1 ranks highest • Where defensibility exists • Key leverage insight Data-based reasoning only. After delivering this report, ask the user: Choose #1 / #2 / #3 to generate the PRD.
PRD REQUIREMENTS
After selection, generate: Executive Summary Market Validation Summary Target Personas Core Differentiator (Wedge) MVP Feature Groups Screen Architecture (Expo Router structure) Monetization Strategy Tech Stack: Expo SDK 52+ TypeScript Expo Router Design System: Hex colors mandatory KPIs Risks & Mitigations PRD must be: Concrete UI-specific Copy-paste ready for Rork No fluff
Category context
Data access, storage, extraction, analysis, reporting, and insight generation.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
1 Docs
- SKILL.md