mcpbeat

Sentiment Analysis

google/sentiment-analysis

Extracts the true audience mood and key feedback by analyzing comment sentiment and keyword frequency.

227 tokens
context cost
the whole folder, loaded on every use
1
files
instructions only
0
copies elsewhere
how many repositories repackaged it
10025
stars on the repo
on the repository, not the skill itself

Install

one command, takes just this skill from the repository 
npx skills add https://github.com/google/adk-samples --skill sentiment-analysis

The instruction itself

1 sections, as written by the author

Skill: Sentiment Analysis Workflow

Objective: Understand the true audience reaction to a video, product, or creator by analyzing comment sentiment.

Execution Steps:

  • Fetch Comments: Use get_video_comments to pull the top 20-50 comments for the target video.
  • Analyze:
  • Use your own semantic understanding combined with analyze_sentiment_heuristic to gauge the overall mood (Positive/Neutral/Negative).
  • Extract the most frequently mentioned keywords, complaints, or praises.
  • Synthesize: Do not just list the comments. Write a cohesive executive summary of *what the audience actually cares about*.

Next Actions: Ask the user if they would like to visualize this sentiment data or publish it as a report.

How to use it

Copy the folder

Take google/sentiment-analysis from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.