Agent skill

Analyzer

by iBigQiang in iBigQiang/feedgrab

Content Analyzer — any content (URL, text, transcript) into structured analysis report with actionable insights.

MITAuto-check passedWriting & Content

Install Analyzer

skills CLI
$ npx skills add iBigQiang/feedgrab --skill analyzer -a claude-code

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

GitHub CLI
$ gh skill install iBigQiang/feedgrab analyzer --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/iBigQiang/feedgrab.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/analyzer .claude/skills/analyzer && 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
analyzer
GitHub stars
614
Token cost
~1k tokens
SKILL.md length
245 words
Files
1
Skills in repo
5
Repo updated
First seen
Licence
MIT

At a glance

Content Analyzer — any content (URL, text, transcript) into structured analysis report with actionable insights.

  • Works in 3 steps: Get Content → Multi-Dimensional Analysis → Personalized Relevance (Customizable)
  • User asks to analyze
  • SKILL.md covers Trigger, Pipeline, Output Modes and Best Practices
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Analyzer is an agent skill from iBigQiang/feedgrab. Content Analyzer — any content (URL, text, transcript) into structured analysis report with actionable insights. Use when user asks to analyze, summarize, or extract key takeaways from content.

Its SKILL.md is about 1k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Writing & Content, covering Summarization. The repository describes itself as: Universal content grabber — fetch, normalize, and digest content from 7+ platforms (WeChat, XHS, X/Twitter, YouTube, Bilibili, Telegram, RSS). The licence is MIT.

When your agent uses it

  • User asks to analyze
  • Extract key takeaways from content

Example prompts

  • “/analyzer”

Workflow steps

3 steps, taken from the step headings in SKILL.md.

  1. Get Content
  2. Multi-Dimensional Analysis
  3. Personalized Relevance (Customizable)

What it can do on your machine

Read from SKILL.md and the folder at commit 04291ba. 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

    No scripts in the folder and no shell commands in SKILL.md (its code samples are markdown).

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

  • Network

    No URLs in SKILL.md.

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

  • Credentials

    Names no API keys, tokens, secrets or passwords.

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

Context cost

Analyzer loads about 1k tokens when it runs. Until then it costs about 51 tokens; SKILL.md has 245 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~51
When it runs · the whole SKILL.md, loaded when a task matches
~1k

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); files beside SKILL.md are not scanned.

SKILL.md

The full file from iBigQiang/feedgrab at commit 04291ba, republished under its MIT licence (© iBigQiang). 245 words, ~1,028 tokens.

Download SKILL.mdSave it as .claude/skills/analyzer/SKILL.md (or your agent's skills folder).
name
analyzer
description
Content Analyzer — any content (URL, text, transcript) into structured analysis report with actionable insights. Use when user asks to analyze, summarize, or extract key takeaways from content.

Content Analyzer Skill

Any content → structured analysis report with actionable insights

Trigger

When user sends content (URL, text, or transcript) with analysis intent:

  • /analyze [URL]
  • "Analyze this article"
  • "What are the key takeaways?"
  • Auto-triggered after video/podcast transcription (from video skill)

Pipeline

Step 1: Get Content

Choose tool based on input type:

InputTool
Tweet URLfetch_tweet or Jina Reader
Web URLWebFetch or Jina Reader
Local fileRead file directly
Transcript from video skillUse directly
Step 2: Multi-Dimensional Analysis

Scan content across these dimensions. Only output dimensions with actual content — skip empty ones.

markdown
## 📖 Summary

[1-3 sentence core thesis]

**Source**: [author/publisher] · [date]
**Type**: [tweet/article/video/podcast/report]

---

## 💡 Key Insights

### 🎯 Core Arguments
- **Thesis**: [Main argument or finding]
- **Evidence**: [Supporting data or reasoning]
- **Strength**: [How convincing? What's missing?]

### 🤖 Tools & Methods
- **What**: [Tools, frameworks, or techniques mentioned]
- **How**: [How they're used or applied]
- **Relevance**: [Could you use this?]

### ⚙️ Workflow Ideas
- **Optimization**: [Process improvements mentioned]
- **Automation**: [What could be automated]
- **Integration**: [How to fit into existing workflow]

### 📊 Data & Numbers
- **Key metrics**: [Important numbers mentioned]
- **Trends**: [Patterns in the data]
- **Gaps**: [What data is missing]

### ⚠️ Risks & Warnings
- **Pitfalls**: [Explicitly mentioned risks]
- **Blind spots**: [What the author might be missing]
- **Counter-arguments**: [Alternative perspectives]

### 🔗 Resources
- **Tools/APIs**: [Mentioned tools or data sources]
- **People**: [Worth following or referencing]
- **Further reading**: [Related content]

### 🧠 Mental Model Shifts
- **Before**: [Common assumption]
- **After**: [New understanding from this content]
- **Impact**: [How this changes decisions]

---

## ✅ Action Items

### Quick Wins (< 30 min)
- [ ] [Action 1] — Impact: ★★★★ | Effort: Easy
- [ ] [Action 2] — Impact: ★★★ | Effort: Easy

### Deeper Work (1-3 hours)
- [ ] [Action 3] — Impact: ★★★ | Effort: Medium
- [ ] [Action 4] — Impact: ★★ | Effort: Medium

### Exploration (needs validation)
- [ ] [Action 5] — Impact: ★★★ | Effort: Hard | Nature: Exploratory
Step 3: Personalized Relevance (Customizable)

Map insights to YOUR context. Edit the dimensions below to match your own projects, interests, and systems.

markdown
## 🔄 How This Applies to Me

### My Projects
- **[Project A]**: [How this insight connects]
- **[Project B]**: [What I could apply]

### My Knowledge Base
- **Update**: [Which notes/docs to update]
- **New entry**: [What to add to my knowledge system]

### My Decision Log
- **Changed my mind about**: [what and why]
- **Confirmed my belief that**: [what]

Customization: Edit the dimensions in Step 2 and Step 3 to match your own domain. A trader might add "Market Impact" and "Risk Assessment". A developer might add "Architecture Patterns" and "Tech Debt". Make it yours.

Output Modes

ModeTriggerOutput
Full (default)/analyze [URL]All dimensions
Sparse/analyze [URL] --sparseOnly hit dimensions, skip empty
Brief/analyze [URL] --briefAction items only

Best Practices

  1. Scan all dimensions, but don't force-fill — skip empty dimensions cleanly
  2. Actions must be specific — not "learn about X" but "read X docs chapter Y"
  3. Distinguish fact from opinion — mark the author's claims vs verified facts
  4. Source everything — tag where each insight comes from in the original content
  5. ROI awareness — not every action is worth doing, assess effort vs impact

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

Files

Just SKILL.md in skills/analyzer of iBigQiang/feedgrab.

Open the folder on GitHubat commit 04291ba

Compare with similar skills

Analyzer 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.

Analyzer compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Analyzer this skilliBigQiang/feedgrab614—~1kAutomated safety check: PassMIT
News Aggregator Skillcclank/news-aggregator-skill1.3k—~2.1kAutomated safety check: PassNone
AI Daily Newsgeekjourneyx/ai-daily-skill235—~2.3kAutomated safety check: PassNone
Vss Search ArchiveNVIDIA-AI-Blueprints/video-search-and-summarization1.9k—~3.6kAutomated safety check: PassApache-2.0
Reportmicrosoft/data-formulator18k—~1.5kAutomated safety check: PassMIT
Tldrearlyaidopters/claudeclaw173—~953Automated safety check: PassNone

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More from iBigQiang/feedgrab

  • Feedgrab

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  • Video

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  • Feedgrab Setup

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    614 GitHub stars~1.4k tokensUpdated 1 mo ago
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Questions about Analyzer

What does Analyzer do?

Content Analyzer — any content (URL, text, transcript) into structured analysis report with actionable insights. Analyzer is an agent skill from iBigQiang/feedgrab. Content Analyzer — any content (URL, text, transcript) into structured analysis report with actionable insights.

When should I use Analyzer?

Analyzer fits situations like: user asks to analyze; extract key takeaways from content.

How do I install Analyzer in Claude Code?

Run `npx skills add iBigQiang/feedgrab --skill analyzer -a claude-code`. Or copy the skill folder (skills/analyzer in iBigQiang/feedgrab) into .claude/skills/analyzer in your project. Claude Code loads it when a task matches its description.

How do I install Analyzer in Codex?

Run `npx skills add iBigQiang/feedgrab --skill analyzer -a codex`. Or copy the skill folder (skills/analyzer in iBigQiang/feedgrab) into .agents/skills/analyzer in your project. Codex loads it when a task matches its description.

Can I use Analyzer 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 iBigQiang/feedgrab --skill analyzer -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/analyzer, .gemini/skills/analyzer, .github/skills/analyzer and .opencode/skills/analyzer in your project.

What does Analyzer need to run?

SKILL.md names no scripts, command-line tools or credentials: Analyzer is instructions for the agent only.

Does Analyzer access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Analyzer 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. Review the folder before installing.

What licence does Analyzer use?

Analyzer 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 Analyzer use?

About 1k tokens (SKILL.md is roughly 4.1k 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 Analyzer?

Skills that share tags, products or a category with Analyzer: News Aggregator Skill (cclank/news-aggregator-skill, 1.3k stars), AI Daily News (geekjourneyx/ai-daily-skill, 235 stars), Vss Search Archive (NVIDIA-AI-Blueprints/video-search-and-summarization, 1.9k stars) and Report (microsoft/data-formulator, 18k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Analyzer?

iBigQiang (a GitHub user) maintains it in iBigQiang/feedgrab, which has 614 GitHub stars. The repository holds 5 skills in this directory. The repository was last updated on September 8, 2026.

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