requesthunt
Generate user demand research reports from real user feedback. Scrape and analyze feature requests, complaints, and questions from Reddit, X, and GitHub. Use when user wants to do demand research, find feature requests, analyze user demand, or run RequestHunt queries.
Install with Tessl CLI
npx tessl i github:resciencelab/opc-skills --skill requesthunt95
Does it follow best practices?
Agent success when using this skill
Validation for skill structure
Evaluation results
73%
60%Remote Work Productivity Tools — User Demand Report
Research report structure
Report title format
50%
87%
Overview section present
0%
100%
Data Sources in Overview
30%
50%
Top Feature Requests table
40%
60%
Representative Quote column
0%
0%
Pain Points section
25%
100%
Opportunities section
0%
100%
Key Findings grouping
0%
100%
Methodology section present
0%
100%
Methodology feedback count
0%
30%
Methodology platforms listed
0%
100%
Without context: $0.2603 · 1m 31s · 9 turns · 10 in / 4,448 out tokens
With context: $0.3769 · 1m 32s · 14 turns · 45 in / 4,679 out tokens
74%
65%Automate AI Code Review Tools Demand Research
Data collection workflow scripting
API usage check step
0%
0%
Scrape topic step
0%
100%
Search with expand flag
0%
100%
List requests step
0%
100%
Get topics step
0%
0%
Platform filtering used
0%
100%
Sort by top used
0%
100%
Scrape includes github
0%
100%
Limit flag used
0%
100%
Output captured to files
100%
100%
Rate limit awareness
0%
0%
Without context: $0.5199 · 1m 33s · 25 turns · 610 in / 4,950 out tokens
With context: $0.3434 · 1m 1s · 17 turns · 1,563 in / 3,325 out tokens
100%
57%Team Communication Tools — Research Planning
Scope clarification and research planning
Research goal question
66%
100%
Specific products question
100%
100%
Platform preference question
0%
100%
Time range question
14%
100%
Report purpose question
22%
100%
Scrape topic in collection plan
0%
100%
Search with expand in plan
0%
100%
List requests in plan
0%
100%
Report outline has Overview
100%
100%
Report outline has Key Findings
71%
100%
Report outline has Methodology
100%
100%
Competitive Comparison section
50%
100%
Without context: $0.2398 · 1m 33s · 9 turns · 10 in / 4,271 out tokens
With context: $0.3353 · 1m 47s · 13 turns · 15 in / 5,076 out tokens
- Evaluated
- Agent
- Claude Code
Table of Contents
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