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Agent skill

Youtube Comments API Skill

by browser-act in browser-act/skills

This skill helps users extract structured video list data and comment data from YouTube using the BrowserAct API.

MITAuto-check passedMarketing & SEO

Install Youtube Comments API Skill

skills CLI
$ npx skills add browser-act/skills --skill youtube-comments-api-skill -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install browser-act/skills youtube-comments-api-skill --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/browser-act/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/solutions/video-platforms/youtube-comments-api-skill .claude/skills/youtube-comments-api-skill && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
youtube-comments-api-skill
GitHub stars
6.1k
Used in
1 other repo
Token cost
~1.7k tokens
SKILL.md length
758 words
Files
2 (incl. scripts)
Skills in repo
87
Repo updated
First seen
Licence
MIT

At a glance

This skill helps users extract structured video list data and comment data from YouTube using the BrowserAct API.

  • Works in 5 steps: Zero Hallucination, Ensuring Stable and… → No CAPTCHA Issues: No need to handle… → No IP Access Restrictions or… → …
  • Tasks that involve Web scraping
  • SKILL.md covers 📖 Introduction, ✨ Features, 🔑 API Key Guidance Process and 🛠️ Input Parameters, plus 4 more sections
  • Runs Python scripts from its folder; calls python; needs BROWSERACT_API_KEY

What it does

Youtube Comments API Skill is an agent skill from browser-act/skills. This skill helps users extract structured video list data and comment data from YouTube using the BrowserAct API. The Agent should proactively apply this skill when users request searching for YouTube videos and their comments, analyzing viewer sentiment for a specific video topic, gathering audience feedback on AI or automation, extracting a list of top videos and their viewer reactions, compiling YouTube video data along with user opinions, retrieving competitor video titles and related audience discussions…

Its SKILL.md is about 1.7k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including scripts (for example `scripts/youtube_comments_api.py`).

It sits in Marketing & SEO, covering Web scraping, Market research and Product metrics. It works with YouTube. The repository describes itself as: Browser automation CLI built for AI agents. Break through anti-bot walls, hand off to humans across platforms when stuck. Parallel multi-task execution, independent multi-session… The licence is MIT.

When your agent uses it

  • Tasks that involve Web scraping
  • Tasks that involve Market research
  • Tasks that involve Product metrics

Example prompts

  • “/youtube-comments-api-skill”

Requirements

  • Python 3
  • A credential in BROWSERACT_API_KEY

Workflow steps

5 steps, taken from the first numbered list in SKILL.md.

  1. Zero Hallucination, Ensuring Stable and Accurate Data Extraction: Pre-configured workflows avoid AI generative hallucinations.
  2. No CAPTCHA Issues: No need to handle reCAPTCHA or other verification challenges.
  3. No IP Access Restrictions or Geo-fencing: No need to deal with regional IP limits.
  4. More Agile Execution Speed: Faster task execution compared to pure AI-driven browser automation solutions.
  5. Extremely High Cost-Efficiency: Significantly reduces data acquisition costs compared to AI solutions that consume a large number of tokens.

What it can do on your machine

Read from SKILL.md and the folder at commit 11c057b. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 1 file in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Links to these hosts (documentation or services it may open):

    • browseract.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • BROWSERACT_API_KEY

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Youtube Comments API Skill loads about 1.7k tokens when it runs. Until then it costs about 223 tokens; SKILL.md has 758 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~223
When it runs · the whole SKILL.md, loaded when a task matches
~1.7k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from browser-act/skills at commit 11c057b, republished under its MIT licence (© browser-act). 758 words, ~1,667 tokens.

Download SKILL.mdSave it as .claude/skills/youtube-comments-api-skill/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
youtube-comments-api-skill
description
This skill helps users extract structured video list data and comment data from YouTube using the BrowserAct API. The Agent should proactively apply this skill when users request searching for YouTube videos and their comments, analyzing viewer sentiment for a specific video topic, gathering audience feedback on AI or automation, extracting a list of top videos and their viewer reactions, compiling YouTube video data along with user opinions, retrieving competitor video titles and related audience discussions, monitoring public response to specific YouTube search keywords, summarizing comments from search results for market research, tracking viewer engagement metrics and replies for trending topics, collecting YouTube video URLs and author details alongside community discussions, or automating the extraction of YouTube comments without manual scraping.

YouTube Comments API Automation Skill

📖 Introduction

This skill provides a one-stop extraction service for YouTube video and comment data through the BrowserAct YouTube Comments API template. It can extract structured video results along with their respective comments directly from YouTube. By simply providing search keywords, comment limits, and scroll counts, you can acquire clean and ready-to-use video and comment datasets directly.

✨ Features

  1. Zero Hallucination, Ensuring Stable and Accurate Data Extraction: Pre-configured workflows avoid AI generative hallucinations.
  2. No CAPTCHA Issues: No need to handle reCAPTCHA or other verification challenges.
  3. No IP Access Restrictions or Geo-fencing: No need to deal with regional IP limits.
  4. More Agile Execution Speed: Faster task execution compared to pure AI-driven browser automation solutions.
  5. Extremely High Cost-Efficiency: Significantly reduces data acquisition costs compared to AI solutions that consume a large number of tokens.

🔑 API Key Guidance Process

Before running, you must first check the BROWSERACT_API_KEY environment variable. If it is not set, do not take any other actions; you should request and wait for the user to provide it. At this point, the Agent must inform the user:

"Since you have not configured the BrowserAct API Key yet, please go to the BrowserAct Console first to get your Key."

🛠️ Input Parameters

When invoking the script, the Agent should flexibly configure the following parameters based on user needs:

  1. keywords

    • Type: string
    • Description: Search keywords used to find videos on YouTube. Can be any keyword or phrase.
    • Example: AI, automation, web scraping
    • Default: AI

  2. Comments_limit

    • Type: number
    • Description: Maximum number of comments to extract per video.
    • Example: 10, 20, 50
    • Default: 10

  3. Scroll_count

    • Type: number
    • Description: Number of times to scroll in the comments section to load more comments before extraction.
    • Example: 1, 2, 5, 10
    • Default: 2

The Agent should execute the following standalone script to achieve "one command, get results":

bash
# Example invocation
python -u ./scripts/youtube_comments_api.py "keywords" "Comments_limit" "Scroll_count"
⏳ Running Status Monitoring

Since this task involves automated browser operations, it may take a long time (several minutes). While running, the script will continuously output timestamped status logs (e.g., [14:30:05] Task Status: running). Agent Instructions:

  • While waiting for the script to return a result, please keep monitoring the terminal output.
  • As long as the terminal is still outputting new status logs, it means the task is running normally. Do not misjudge it as a deadlock or unresponsiveness.
  • Only if the status remains unchanged for a long time or the script stops outputting without returning a result, should you consider triggering the retry mechanism.

📊 Data Output Description

Upon successful execution, the script will directly parse and print the results from the API response. The results include two linked datasets:

Video fields:

  • video_name: Video title shown in the list
  • video_url: Video URL
  • video_publication_time: Published time
  • video_view_count: View count

Comment fields:

  • commenter_name: Comment author display name
  • commenter_url: Comment author channel URL
  • comment_text: Comment content
  • comment_publish_date: Comment publish time
  • comment_likes: Like count for the comment
  • reply_count: Number of replies
Show full SKILL.md (270 more words)Show less

⚠️ Error Handling & Retry

During the execution of the script, if an error occurs (such as network fluctuations or task failure), the Agent should follow this logic:

  1. Check the Output Content:

    • If the output contains "Invalid authorization", it means the API Key is invalid or expired. At this time, do not retry; you should guide the user to recheck and provide the correct API Key.
    • If the output does not contain "Invalid authorization" but the task fails (e.g., the output starts with Error: or returns an empty result), the Agent should automatically try to execute the script one more time.

  2. Retry Limit:

    • Automatic retries are limited to one time only. If the second attempt still fails, stop retrying and report the specific error message to the user.

🌟 Typical Use Cases

  1. Audience Insight: Turning comments into product feedback and sentiment signals based on specific keywords.
  2. Content Research: Understanding what viewers are discussing under popular video topics.
  3. Competitive Monitoring: Tracking comments and feedback on competitors' YouTube channels.
  4. Community Insight: Analyzing what users care about in a specific niche like automation or AI.
  5. Topic Tracking: Monitoring the public response and interaction for trending search terms.
  6. Sentiment Analysis: Gathering raw text data from comments to evaluate viewer opinions.
  7. Objections and Feature Requests: Identifying user pain points from product-related video comments.
  8. Automated Data Integration: Sending video and comment data directly into CRM or BI tools via API.
  9. Engagement Metrics Collection: Tracking likes and reply counts for top comments.
  10. Market Research: Extracting a large set of video metadata combined with user discussions for market studies.

© browser-act, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file (scripts) in solutions/video-platforms/youtube-comments-api-skill of browser-act/skills.

  • SKILL.md
  • scripts/youtube_comments_api.py

Open the folder on GitHubat commit 11c057b

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in browser-act/skills, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Youtube Comments API Skill next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Youtube Comments API Skill compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Youtube Comments API Skill this skillbrowser-act/skills6.1k1 repos~1.7kAutomated safety check: PassMIT
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Apify Influencer Discoverymajiayu000/claude-skill-registry6663 repos~1.1kAutomated safety check: NotesMIT
Apify Market Researchmajiayu000/claude-skill-registry6663 repos~1.2kAutomated safety check: NotesMIT
Scrapecreators APIScrapeCreators/social-media-research-skills3.3k1 repos~4kAutomated safety check: NotesMIT
SEO DataforseoAgriciDaniel/codex-seo7912 repos~4.6kAutomated safety check: PassMIT

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Works with

Categories

Questions about Youtube Comments API Skill

What does Youtube Comments API Skill do?

This skill helps users extract structured video list data and comment data from YouTube using the BrowserAct API. Youtube Comments API Skill is an agent skill from browser-act/skills. This skill helps users extract structured video list data and comment data from YouTube using the BrowserAct API.

When should I use Youtube Comments API Skill?

Youtube Comments API Skill fits situations like: tasks that involve Web scraping; tasks that involve Market research; tasks that involve Product metrics.

How do I install Youtube Comments API Skill in Claude Code?

Run `npx skills add browser-act/skills --skill youtube-comments-api-skill -a claude-code`. Or copy the skill folder (solutions/video-platforms/youtube-comments-api-skill in browser-act/skills) into .claude/skills/youtube-comments-api-skill in your project. Claude Code loads it when a task matches its description.

How do I install Youtube Comments API Skill in Codex?

Run `npx skills add browser-act/skills --skill youtube-comments-api-skill -a codex`. Or copy the skill folder (solutions/video-platforms/youtube-comments-api-skill in browser-act/skills) into .agents/skills/youtube-comments-api-skill in your project. Codex loads it when a task matches its description.

Can I use Youtube Comments API Skill in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add browser-act/skills --skill youtube-comments-api-skill -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/youtube-comments-api-skill, .gemini/skills/youtube-comments-api-skill, .github/skills/youtube-comments-api-skill and .opencode/skills/youtube-comments-api-skill in your project.

What does Youtube Comments API Skill need to run?

Going by SKILL.md and its folder, Youtube Comments API Skill needs Python for the scripts in its folder, the command-line tools its instructions call (python) and credentials named BROWSERACT_API_KEY. Our summary lists: Python 3; A credential in BROWSERACT_API_KEY.

Does Youtube Comments API Skill access the network?

SKILL.md names 1 domain. As links in the text: browseract.com. This is read from the text; nothing was executed.

Is Youtube Comments API Skill safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Youtube Comments API Skill use?

Youtube Comments API Skill is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Youtube Comments API Skill use?

About 1.7k tokens (SKILL.md is roughly 6.7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Youtube Comments API Skill?

Skills that share tags, products or a category with Youtube Comments API Skill: Apify Content Analytics (majiayu000/claude-skill-registry, 666 stars), Apify Influencer Discovery (majiayu000/claude-skill-registry, 666 stars), Apify Market Research (majiayu000/claude-skill-registry, 666 stars) and Scrapecreators API (ScrapeCreators/social-media-research-skills, 3.3k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Youtube Comments API Skill?

browser-act (a GitHub organization) maintains it in browser-act/skills, which has 6,114 GitHub stars. The repository holds 87 skills in this directory. The repository was last updated on August 24, 2026.

Source: browser-act/skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.