Agent skill

Zhihu Search API Skill

by browser-act in browser-act/skills

This skill helps users automatically extract structured article details and full content from Zhihu via the BrowserAct API.

MITAuto-check passedMarketing & SEO

Install Zhihu Search API Skill

skills CLI
$ npx skills add browser-act/skills --skill zhihu-search-api-skill -a claude-code

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

GitHub CLI
$ gh skill install browser-act/skills zhihu-search-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/social-listening/zhihu-search-api-skill .claude/skills/zhihu-search-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
zhihu-search-api-skill
GitHub stars
6.1k
Used in
1 other repo
Token cost
~1.6k tokens
SKILL.md length
752 words
Files
2 (incl. scripts)
Skills in repo
87
Repo updated
First seen
Licence
MIT

At a glance

This skill helps users automatically extract structured article details and full content from Zhihu via the BrowserAct API.

  • Works in 5 steps: No hallucinations, ensuring stable and… → No CAPTCHA issues: No need to handle… → No IP access restrictions and… → …
  • Tasks that involve Schema markup
  • SKILL.md covers 📖 Brief, ✨ Features, 🔑 API Key Guide and 🛠️ Input Parameters, plus 4 more sections
  • Runs Python scripts from its folder; calls python; needs BROWSERACT_API_KEY

What it does

Zhihu Search API Skill is an agent skill from browser-act/skills. This skill helps users automatically extract structured article details and full content from Zhihu via the BrowserAct API. Agent should proactively apply this skill when users express needs like: searching for Zhihu articles on a specific topic, tracking industry trends on Zhihu, monitoring public relations or sentiment on Zhihu, collecting competitor updates, getting the latest reports on specific keywords, monitoring brand exposure in Zhihu media, researching market hot topics, summarizing daily Zhihu industry…

Its SKILL.md is about 1.6k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including scripts (for example `scripts/zhihu_search_api.py`).

It sits in Marketing & SEO, covering Schema markup, Market research and Social media marketing. 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 Schema markup
  • Tasks that involve Market research
  • Tasks that involve Social media marketing

Example prompts

  • “/zhihu-search-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. No hallucinations, ensuring stable and precise data extraction: Pre-set workflows avoid AI generative hallucinations.
  2. No CAPTCHA issues: No need to handle reCAPTCHA or other verification challenges.
  3. No IP access restrictions and geo-fencing: No need to deal with regional IP limits.
  4. Faster execution speed: Compared to pure AI-driven browser automation solutions, task execution is much faster.
  5. Extremely high cost-effectiveness: Significantly reduces data acquisition costs compared to AI solutions that consume a large number of…

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

Zhihu Search API Skill loads about 1.6k tokens when it runs. Until then it costs about 182 tokens; SKILL.md has 752 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~182
When it runs · the whole SKILL.md, loaded when a task matches
~1.6k

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). 752 words, ~1,584 tokens.

Download SKILL.mdSave it as .claude/skills/zhihu-search-api-skill/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
zhihu-search-api-skill
description
This skill helps users automatically extract structured article details and full content from Zhihu via the BrowserAct API. Agent should proactively apply this skill when users express needs like: searching for Zhihu articles on a specific topic, tracking industry trends on Zhihu, monitoring public relations or sentiment on Zhihu, collecting competitor updates, getting the latest reports on specific keywords, monitoring brand exposure in Zhihu media, researching market hot topics, summarizing daily Zhihu industry news, retrieving hot events from the past week, extracting structured data for market research, finding full Zhihu articles for AI agents, extracting full article body from Zhihu links.

Zhihu Search API Automated Extraction Skill

📖 Brief

This skill uses BrowserAct's Zhihu Search API template to provide a one-stop article extraction service. It extracts structured article details and full content from Zhihu article search results based on keywords and publication date filters.

✨ Features

  1. No hallucinations, ensuring stable and precise data extraction: Pre-set workflows avoid AI generative hallucinations.
  2. No CAPTCHA issues: No need to handle reCAPTCHA or other verification challenges.
  3. No IP access restrictions and geo-fencing: No need to deal with regional IP limits.
  4. Faster execution speed: Compared to pure AI-driven browser automation solutions, task execution is much faster.
  5. Extremely high cost-effectiveness: Significantly reduces data acquisition costs compared to AI solutions that consume a large number of tokens.

🔑 API Key Guide

Before running, you need to check the BROWSERACT_API_KEY environment variable. If it is not set, do not take other actions; wait for the user to provide it. The Agent must inform the user at this time:

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

🛠️ Input Parameters

The Agent should flexibly configure the following parameters according to user needs when calling the script:

  1. keyword (Search Keywords)

    • Type: string
    • Description: Search keywords used to find Zhihu articles. Can be company name, industry term, etc.
    • Example: AI agent, openclaw
  2. Publish_date (Publication Date Range)

    • Type: string
    • Description: Filter articles by publication date.
    • Options:
      • 7d: Past 7 days
      • 30d: Past 30 days
      • 90d: Past 90 days
      • 1y: Past year
      • all: Any time
    • Default: 7d
  3. Date_limit (Extraction Limit)

    • Type: number
    • Description: Maximum number of articles to extract.
    • Default: 10

The Agent should execute the following independent script to achieve "one command gets results":

bash
# Example call
python -u ./scripts/zhihu_search_api.py "keyword" "Publish_date" limit
⏳ Execution Status Monitoring

Because this task involves automated browser operations, it may take a long time (several minutes). The script will continuously output status logs with timestamps (e.g., [14:30:05] Task Status: running) while running. Agent Must Know:

  • While waiting for the script to return a result, 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 mistake it for a deadlock or unresponsiveness.
  • If the status remains unchanged for a long time or the script stops outputting without returning a result, then consider triggering the retry mechanism.

📊 Data Output

Upon successful execution, the script will directly parse and print the result from the API response. The result includes:

  • title: Full article title
  • body_content: Full body content of the article
  • image_url: Main image URL or article cover image URL
  • author: Article author or publishing account name
  • publication_date: Article publication date
  • url_link: Original article URL
Show full SKILL.md (304 more words)Show less

⚠️ Error Handling & Retry

During the execution of the script, if an error is encountered (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. Do not retry at this time, and guide the user to check and provide the correct API Key.
    • If the output does not contain "Invalid authorization" but the task execution fails (for example, the output starts with Error: or the return result is empty), the Agent should automatically try to execute the script once more.
  2. Retry limits:

    • Automatic retry is limited to one time. If the second attempt still fails, stop retrying and report the specific error information to the user.

🌟 Typical Use Cases

  1. Industry Trend Tracking: Find the latest industry dynamics on specific topics like "low-altitude economy" or "generative AI" on Zhihu.
  2. Public Relations Monitoring: Monitor the media exposure of a specific brand or company on Zhihu over the past 30 days.
  3. Competitor Intelligence Gathering: Collect recent product information or market activities published by competitors on Zhihu.
  4. Market Hotspot Research: Get popular Zhihu reports on specific keywords across different time dimensions.
  5. Character Dynamics Tracking: Retrieve the latest Zhihu articles and interviews of industry leaders or public figures.
  6. Daily Briefing Summary: Automatically extract and summarize daily industry news briefings from Zhihu.
  7. Global Event Monitoring: Real-time access to major breaking news and discussions on Zhihu.
  8. Structured Data Extraction: Extract structured information such as article titles, authors, and links from Zhihu for market research analysis.
  9. Media Exposure Analysis: Evaluate the spread and popularity of a specific project or event on Zhihu.
  10. Long-term Thematic Research: Retrieve in-depth reports and discussions on a specific technical topic from the past year.

© 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/social-listening/zhihu-search-api-skill of browser-act/skills.

  • SKILL.md
  • scripts/zhihu_search_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

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Zhihu Search API Skill compared with similar skills
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Categories

Questions about Zhihu Search API Skill

What does Zhihu Search API Skill do?

This skill helps users automatically extract structured article details and full content from Zhihu via the BrowserAct API. Zhihu Search API Skill is an agent skill from browser-act/skills. This skill helps users automatically extract structured article details and full content from Zhihu via the BrowserAct API.

When should I use Zhihu Search API Skill?

Zhihu Search API Skill fits situations like: tasks that involve Schema markup; tasks that involve Market research; tasks that involve Social media marketing.

How do I install Zhihu Search API Skill in Claude Code?

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

How do I install Zhihu Search API Skill in Codex?

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

Can I use Zhihu Search 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 zhihu-search-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/zhihu-search-api-skill, .gemini/skills/zhihu-search-api-skill, .github/skills/zhihu-search-api-skill and .opencode/skills/zhihu-search-api-skill in your project.

What does Zhihu Search API Skill need to run?

Going by SKILL.md and its folder, Zhihu Search 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 Zhihu Search 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 Zhihu Search 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 Zhihu Search API Skill use?

Zhihu Search 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 Zhihu Search API Skill use?

About 1.6k tokens (SKILL.md is roughly 6.3k 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 Zhihu Search API Skill?

Skills that share tags, products or a category with Zhihu Search API Skill: 08 Nghien Cuu Doi Thu (minhnv0807/ai-business-skills, 608 stars), Social Strategy (social-media-skills/skills, 125 stars), Blog Discourse (AgriciDaniel/claude-blog, 2.3k stars) and Audience Analyst (holaboss-ai/holaOS, 11k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Zhihu Search 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.