research-on-zhihu

research-on-zhihu is a skill for Claude Code, Codex from alizeeblack-code/zhihu-mcp. It costs 55 tokens per session (1,041 once invoked), scanned A, original, MIT.

A research tool for Zhihu, a Chinese question-and-answer website. Given a topic or keyword, it finds relevant questions, reads selected highly rated answers, and can examine comments.

In plain words
What is it for?
Use it to research a topic on Zhihu, find important questions, summarize leading answers, examine user comments, and organize the resulting viewpoints.
Why use it?
It helps gather a broad view of how a topic is discussed instead of relying on a single answer. It can support competitor research, opinion gathering, and public-discussion analysis.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to research a topic on Zhihu, find important questions, summarize leading answers, examine user comments, and organize the resulting viewpoints.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/alizeeblack-code/zhihu-mcp/research-on-zhihu
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add alizeeblack-code/zhihu-mcp --skill research-on-zhihu
Clone the repo
git clone --depth 1 https://github.com/alizeeblack-code/zhihu-mcp

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for research-on-zhihu

README.md
[![agentmods](https://agentmods.dev/badge/skills/alizeeblack-code/zhihu-mcp/research-on-zhihu/github.svg)](https://agentmods.dev/skills/alizeeblack-code/zhihu-mcp/research-on-zhihu)
Your own site
<a href="https://agentmods.dev/skills/alizeeblack-code/zhihu-mcp/research-on-zhihu"><img src="https://agentmods.dev/badge/skills/alizeeblack-code/zhihu-mcp/research-on-zhihu/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for research-on-zhihu

Your own site · 80×15
<a href="https://agentmods.dev/skills/alizeeblack-code/zhihu-mcp/research-on-zhihu"><img src="https://agentmods.dev/badge/skills/alizeeblack-code/zhihu-mcp/research-on-zhihu.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 55 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,041 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00055 $0.01041
Opus 5 $0.00028 $0.00521
Sonnet 5 $0.00011 $0.00208
Haiku 4.5 $0.00006 $0.00104

Measured 10d ago against content hash 0570560ad706, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

research-on-zhihu scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/research-on-zhihu/SKILL.md · 135 lines

What it actually says

知乎话题研究

根据用户提供的关键词或话题,在知乎上进行系统性研究,输出结构化报告。

适用场景

  • 用户说"帮我研究一下 XXX"、"知乎上怎么看 XXX"、"XXX 的口碑如何"
  • 用户想了解某个话题在知乎上的讨论情况
  • 竞品分析、舆情调研、观点收集

工作流程

用户输入关键词/话题
    │
    ├─ Step 1: 搜索知乎内容
    │
    ├─ Step 2: 筛选高质量问题
    │
    ├─ Step 3: 逐个获取问题详情和高赞回答
    │
    ├─ Step 4: 读取关键回答的评论(可选)
    │
    └─ Step 5: 综合分析,输出研究报告

Step 1: 搜索内容

使用 search_content 搜索关键词,获取相关内容列表。

search_content(keyword="用户关键词", sort="relevance", count=10)
  • 默认按相关性排序
  • 如果用户关心最新讨论,改用 sort="newest"
  • 如果用户关心最热讨论,改用 sort="most_upvoted"

检查搜索结果,如果结果太少或不相关,尝试:

  1. 调整关键词(同义词、更宽泛/更具体的表述)
  2. 切换排序方式
  3. 告知用户搜索结果有限

Step 2: 筛选高质量问题

从搜索结果中筛选出最相关的 2-3 个问题(type 为 "question" 或 "answer")。

筛选标准:

  • 标题与用户关心的话题高度相关
  • 优先选择有较多回答的问题
  • 忽略明显偏题或过于宽泛的问题

Step 3: 获取问题详情和高赞回答

对筛选出的每个问题,使用 get_question_detail 获取详情:

get_question_detail(question_id="问题ID")

返回内容包含:

  • 问题标题、描述、话题标签
  • 关注数、浏览数、回答数
  • Top 回答列表(作者、摘要、点赞数、answer_id、url)

对于高赞回答(点赞数较高的前 2-3 个),使用 get_answer_detail 获取完整内容:

get_answer_detail(question_id="问题ID", answer_id="回答ID")

Step 4: 读取评论(可选)

如果需要更深入的分析,或用户明确要求,对关键回答获取评论:

get_comments(url="回答的完整URL", count=10)

评论可以揭示:

  • 对回答观点的补充和反驳
  • 真实用户的使用体验
  • 争议焦点

仅在以下情况读取评论:

  • 用户明确要求看评论
  • 回答的评论数很高(>50),说明有争议
  • 需要验证回答中的说法

Step 5: 输出研究报告

综合所有收集的信息,输出结构化报告:

## 知乎研究报告:{话题}

### 概览
- 搜索关键词:XXX
- 相关问题数:X 个
- 分析回答数:X 个
- 总浏览量:约 X 万

### 主流观点
1. **观点一**(来源:问题标题 / 作者名,X 赞)
   - 核心论点摘要
2. **观点二** ...

### 争议与分歧
- 争议点 A:正方观点 vs 反方观点
- 争议点 B ...

### 关键洞察
- 洞察 1
- 洞察 2

### 数据来源
- [问题标题1](URL) — X 个回答,X 关注
- [问题标题2](URL) — X 个回答,X 关注

注意事项

  • 如果搜索结果为空,先告知用户,建议换个关键词
  • 不要一次性获取太多回答详情,2-3 个高赞回答通常足够
  • 保持客观,如实呈现不同观点,不要过度总结或偏向某一方
  • 注明数据来源(问题链接、作者、点赞数),方便用户验证
  • 如果话题敏感或涉及专业领域,提醒用户知乎观点仅供参考
Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 10d ago First seen · 135 lines · 55 tokens per session scan A 0570560ad706

Subscribe to this mod's changes

research-on-zhihu is a skill published in the GitHub repository alizeeblack-code/zhihu-mcp (4 stars, last pushed 6mo ago), licensed MIT. It adds 55 tokens to every session and 1,041 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

Related

Other skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

local-ai-agents

Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…

microsoft/ai-agents-for-beginners · 200 tokens

next-cache-components-adoption

Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…

vercel/next.js · 95 tokens

insight-error-page

Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…

vercel/next.js · 83 tokens

next-cache-components-optimizer

Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…

vercel/next.js · 170 tokens

next-partial-prefetching-adoption

Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…

vercel/next.js · 103 tokens