comment_analysis
Analyze video comment sections to discover recommended content and gauge content quality.
Skill by whiteguo233
Chalk Labs
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Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/whiteguo233-comment-analysis
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
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About
Use cases: writing, social-media, data-analysis
Reviews
Write a reviewNo reviews yet. Installed it? Reviews come from verified installers only. How reviews work
Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/comment-analysis
What's inside
- Skill name
comment_analysis- Description
- Analyze video comment sections to discover recommended content and gauge content quality.
- License
- MIT
- Instructions
- 31 lines in SKILL.md · view on GitHub
Agent Skills spec issues
- name: only lowercase letters, digits and single hyphens allowed
Files (1)
- SKILL.md
SKILL.md (first lines)
# Comment Analysis Skill Mine video comment sections for content recommendations and quality signals. ## When to Use - As part of the content discovery cycle - To evaluate the quality and reception of discovered content - To find user-recommended content and UP主 from comments ## How It Works 1. Fetches comments from a video via API or agent-browser 2. Uses LLM to identify: - Other video/UP主 recommendations mentioned in comments - Overall content quality sentiment - Common viewer reactions and highlights 3. Returns structured analysis ## Parameters - `bvid` (str): Video BV ID to analyze comments for - `max_comments` (int, optional): Maximum comments to analyze (default: 100) ## Output - Recommended content/UP主 found in comments - Quality sentiment score - Key highlights and reactions
From whiteguo233/OpenBiliClaw, MIT.
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- 0.838score
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用户希望探索口味时，通过有限的假设与澄清形成可用结论，沉淀已确认的记忆
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CLAUDE.md · whiteguo233/OpenBiliClaw
whiteguo233
CLAUDE.md from whiteguo233/OpenBiliClaw: 247 lines covering Project Overview, Build & Development Commands, Architecture, Configuration and more.
TemplateAFreshness: A★ 3.6KClaude Code
Signals
- Stars
- 3,567
- Forks
- 195
- Open issues
- 19
- Last commit (this folder)
- Mar 7, 2026 (7 months ago)
- Last release
- Oct 22, 2026 (8 days ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Repository
- github.com/whiteguo233/OpenBiliClaw
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
More from whiteguo233
- 0.838score
release
whiteguo233
Use when releasing a version, bumping project versions, or pushing release tags.
SkillAFreshness: A★ 3.6KClaude Code +9 - 0.836score
openbiliclaw-adapter
whiteguo233
Use OpenBiliClaw's versioned Agent Bridge CLI to read multi-source recommendations, profile state, dialogue, probes, saved lists, and submit explicit feedback.
SkillAFreshness: A★ 3.6KClaude Code +9 - 0.836score
add-platform-source
whiteguo233
Add, repair, or validate an OpenBiliClaw platform source across fetching, account signals, discovery, and user surfaces.
SkillAFreshness: A★ 3.6KClaude Code +9 - 0.834score
writing-specs
whiteguo233
Use when authoring a spec or implementation plan, or planning multi-task work.
SkillAFreshness: A★ 3.6KClaude Code +9 - 0.832score
verify
whiteguo233
Drive a real serve-api process against isolated project roots to verify backend/web changes end-to-end
SkillAFreshness: A★ 3.6KClaude Code +9 - 0.829score
taste-companion
whiteguo233
默认对话伙伴，陪聊口味与推荐，可读写记忆、查询推荐与观看数据
SkillAFreshness: A★ 3.6KClaude Code +9
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Cite this page
comment_analysis skill. Agent Mart. https://agentmart.dev/skills/whiteguo233-comment-analysis (last updated 2026-10-24)