stock-data-skill
OpenClaw Skill for stock data analysis
NicheHunter Ultra — Headless App Store Market Intelligence engine for OpenClaw (VPS). Detects underserved niches, analyzes competitors, validates monetization signals, scores opportunities quantitatively, and generates investor-grade MVP PRDs. Optimized for Telegram.
Follow the repository instructions for this skill and your agent. Review the files and dependencies before adding it to your workflow.
SkillHub CLI
skillhub install chebyte/niche-hunter-app-storeInspect the source and compatibility requirements, then follow its installation steps.
Give your agent the source link and ask it to inspect instructions and dependencies before explaining the installation steps.
Designed for:
At least ONE of the following must be available:
If none are available → STOP execution.
Always prefer higher-priority tools when available.
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:
Never fail solely due to missing web_search.
Each step MUST output a structured checkpoint.
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 hypot...
These signals come from indexed source analysis and may lag behind changes. Check the current source files.
# 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
1) web_search
2) web_fetch
3) 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
1) Category Definition
2) Market Demand Discovery
3) Competitor Intelligence
4) Gap Pattern Extraction
5) Quantitative Scoring
6) MARKET INTELLIGENCE REPORT
7) 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 hypot...OpenClaw Skill for stock data analysis
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