compete

name	compete
description	Genre and category competitive analysis — identify oversaturated genres, opportunity gaps, and content positioning
argument-hint	<dataset-folder-name>
risk	safe
user-invocable	true
allowed-tools	["Read","Write","Edit","Bash","Glob","Grep"]
model	claude-sonnet-4-6
context	fork
agent	general-purpose

Compete — Content Competition Analysis

You are executing the :compete skill for the 10x-content-intel plugin.

What This Skill Does

Performs competitive analysis across genres and categories — identifies which content areas are oversaturated, which have opportunity gaps, and how to position content strategically.

Instructions

Step 1: Load Cleaned Data

• Check if output/{argument}/{argument}_cleaned.csv exists
• If NOT, first run the Content Profiler to clean the data
• Load the cleaned CSV

Step 2: Read Agent Instructions

• Read agents/content-strategist.md for strategic analysis approach

Step 3: Genre Competition Analysis

import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
import numpy as np
from pathlib import Path

dataset = "{argument}"
df = pd.read_csv(f"output/{dataset}/{dataset}_cleaned.csv")
out_dir = Path(f"output/{dataset}/compete")
out_dir.mkdir(parents=True, exist_ok=True)

# Handle multi-genre (listed_in) column
genre_col = None
for col in ['listed_in', 'genre', 'genres', 'category']:
    if col in df.columns:
        genre_col = col
        break

if genre_col:
    df_genres = df.dropna(subset=[genre_col]).copy()
    df_genres[genre_col] = df_genres[genre_col].str.split(',')
    df_genres = df_genres.explode(genre_col)
    df_genres[genre_col] = df_genres[genre_col].str.strip()

Step 4: Generate Analysis & Charts (minimum 5):

1. Genre Volume Ranking — Top 20 genres by total content count (horizontal bar)
2. Genre Growth Rate — Compare recent 3 years vs all-time for each genre (% change)
3. Genre × Content Type Matrix — Heatmap showing genre distribution across Movies vs Shows
4. Opportunity Matrix — Scatter plot: X = current volume, Y = growth rate (identify quadrants)
   • High volume + High growth = Stars
   • High volume + Low growth = Cash Cows
   • Low volume + High growth = Rising Stars (OPPORTUNITY)
   • Low volume + Low growth = Niche
5. Rating Distribution by Top Genres — Box plot or grouped bar

Step 5: Strategic Insights

For each chart, provide:

• What the data shows
• What it means strategically
• Actionable recommendation

Step 6: Save Outputs

• Save charts to output/{argument}/compete/chart_*.png
• Write output/{argument}/compete/competitive_analysis.md

Output

• output/{argument}/compete/competitive_analysis.md
• output/{argument}/compete/chart_01_genre_ranking.png
• output/{argument}/compete/chart_02_genre_growth.png
• output/{argument}/compete/chart_03_genre_type_matrix.png
• output/{argument}/compete/chart_04_opportunity_matrix.png
• output/{argument}/compete/chart_05_rating_by_genre.png