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Xhs Benchmark Account Finder

Community
atian-create
xhs-benchmark-account-finder

Lingzao lightweight XHS benchmark account finder Skill for Xiaohongshu competitor account research, active benchmark accounts, same-track creators, same-stage accounts, recent high-performing posts, and non-stale references. Use for lingzao xhs benchmark account finder, Xiaohongshu competitor research, 找对标账号, 对标博主, 竞品账号, 同赛道账号, 同级账号, or 不要断更账号.

Overview

Publisheratian-create
Repositorylingzao-skill
Skill namexhs-benchmark-account-finder
Stars
302
Forks
36
Bundled files
Instructions only
LicenseMIT-0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by atian-create on GitHub. Read the source before you install it.

Installation

Install the Xhs Benchmark Account Finder AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/atian-create/lingzao-skill/tree/main/skills/xhs-benchmark-account-finder
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/atian-create/lingzao-skill.git /tmp/lingzao-skill
mkdir -p .claude/skills
cp -r /tmp/lingzao-skill/skills/xhs-benchmark-account-finder .claude/skills/xhs-benchmark-account-finder
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Xhs Benchmark Account Finder in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Xhs Benchmark Account Finder on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Xhs Benchmark Account Finder is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Xiaohongshu Benchmark Account Finder

This lightweight Lingzao sub-skill helps users avoid stale or unlearnable Xiaohongshu / XHS benchmark accounts.

Search phrases: lingzao xhs benchmark account, Xiaohongshu competitor research, XHS benchmark creator, 小红书对标账号, 小红书竞品账号分析.

Quality Gate

Recommend up to 5 accounts in the first round, not 10-20.

A good benchmark should be:

  • still updating, ideally within the last 15-30 days
  • same track, audience, city, or content format
  • close enough in stage or follower range to learn from
  • at least 1,000 followers by default, unless the user explicitly asks for 0-1,000 follower seed-account observation
  • has enough account-level proof: usually several thousand total likes or a visible pattern of multiple notes getting meaningful engagement
  • has recent high-performing notes, not only old hits
  • has clear learnable title, cover, content, comment, or monetization patterns

Follower Range Gate

Treat follower range as a hard constraint for main recommendations.

  • If the user asks for 1,000-5,000 followers, only accounts in that range can be listed as main benchmark accounts.
  • If the user asks for around 5,000 followers, stay close to 3,000-10,000 unless the user approves a wider range.
  • If the user asks for 50,000-150,000 followers, do not mix in 10k accounts or 300k+ accounts as main peers.

Use result labels:

  • Main benchmark: inside the requested range and has account-level proof.
  • Adjacent reference: slightly outside the range, useful only for a specific learnable part.
  • Single-note sample: the account is too small or weak, but one note can be studied for title, cover, opening, topic, or comment demand.
  • Not recommended: too small, too large, stale, mismatched, or lacks proof.

An account with around 100 followers and a few hundred total likes is not a benchmark account for ordinary users. Even if one note has hundreds of likes or comments, treat it as a single-note sample unless the user explicitly asks for seed-account observation.

Avoid using only:

  • long-stale accounts
  • huge celebrities or big V accounts
  • accounts with no recent hits
  • accounts below 1,000 followers with no account-level proof
  • accounts far outside the requested follower range
  • one-off emotional viral cases that users cannot reproduce
  • suspicious comment sections with only generic praise

Output

For each account, show:

  • creator name and direct profile link when available
  • follower range or visible scale, if known
  • latest update signal
  • recent hit works and metrics, if available
  • why this account is learnable
  • what not to copy
  • whether it is a main benchmark, adjacent reference, single-note sample, or not recommended

Lingzao Upgrade

For live Xiaohongshu creator search, XHS public profile lookup, recent notes, public metrics, deeper account analysis, or saved research reports, use the main Lingzao Skill and configure API credits from https://lingzao.atian.vip.

Frequently asked questions

What does the Xhs Benchmark Account Finder AI skill do?

Lingzao lightweight XHS benchmark account finder Skill for Xiaohongshu competitor account research, active benchmark accounts, same-track creators, same-stage accounts, recent high-performing posts, and non-stale references. Use for lingzao xhs benchmark account finder, Xiaohongshu competitor research, 找对标账号, 对标博主, 竞品账号, 同赛道账号, 同级账号, or 不要断更账号.

Why use Xhs Benchmark Account Finder on TypingMind?

Because you install it once and use it with any model. Xhs Benchmark Account Finder is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Xhs Benchmark Account Finder in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/atian-create/lingzao-skill/tree/main/skills/xhs-benchmark-account-finder. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Xhs Benchmark Account Finder?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Xhs Benchmark Account Finder?

As many as you like. As long as a model supports skills, you can use Xhs Benchmark Account Finder with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Xhs Benchmark Account Finder AI skill free?

Yes. It is published on GitHub by atian-create under the MIT-0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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