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Agent Skill · 研究检索

neta-suggest(内塔建议)

neta-suggest 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

neta-suggest 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为接触敏感数据;许可证为 MIT-0,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 18,296。

总安装 6,162周安装 262GitHub Stars 公开资料未说明下载 2,159核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
0.1.0

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:neta-suggest(内塔建议)
来源仓库:https://github.com/huxiuhan/neta-suggest
安装命令:
openclaw skills install neta-suggest
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install neta-suggest

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

neta-suggest 用于提供关键字、标签和类别推荐建议。适合在 OpenClaw 中需要根据关键词快速定位候选结果时使用。支持分类路径验证与多模式内容提要。安装前建议确认权限范围、维护状态,以及是否会触发联网或命令执行。可结合来源仓库和原始 README 继续核验具体用法和接口细节。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install neta-suggest;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要接触敏感数据,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

neta-suggest 怎么安装?

在终端执行 openclaw skills install neta-suggest。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

neta-suggest 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

neta-suggest 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

neta-suggest 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

neta-suggest 用的人多吗?

公开数据是累计安装 6,162 次,近一周安装 262 次,下载 2,159 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

neta-suggest 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
neta-suggest

内塔建议 · 本页

6,162—接触敏感数据MIT-0有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
neta-suggest
description
Neta API research and recommendation skill — provide keyword/tag/category suggestions, validate taxonomy paths, and power multi‑mode content feeds, supporting progressive exploration from broad to precise. Use this skill when the user has no clear goal, wants topic/idea suggestions, or needs systematic content filtering by keywords/categories. It does not directly generate media (handled by neta-creative); community interactions are handled by neta-community.

Neta Suggest Skill

Instructions

  1. For research‑type tasks like “find me some ideas”, “what’s trending now”, or “filter content by a theme/category”, follow this flow:
  2. Recommended path: browse categories → discover tags → validate paths → fetch content (the “Progressive Exploration” section below contains full command examples).
  3. Before content creation, use this skill to research topics/tags/categories, then hand off to neta-creative for concrete creation.
  4. When the user wants to like/comment or otherwise interact with specific works, switch to neta-community.

Prerequisites

Make sure the NETA_TOKEN environment variable is set.

Install the latest version of the Neta CLI:

neta-cli --version
0.8.0
npm i @talesofai/neta-skills@latest -g
pnpm add -g @talesofai/neta-skills@latest

Core capabilities

1. suggest_keywords — keyword suggestions

Provide popular search keyword suggestions based on an input prefix, helping users discover directions of interest.

neta-cli suggest_keywords --prefix "game" --size 20

Parameters

  • --prefix: keyword prefix (required)
  • --size: number of results, recommended 10–20 (optional)

Use cases

  • User only has a vague idea.
  • Explore trending topics and themes.
  • Prepare for later precise filtering.

2. suggest_tags — related tag suggestions

Recommend related taxonomy tags based on a full keyword.

neta-cli suggest_tags --keyword "character design" --size 15

Parameters

  • --keyword: full keyword (required)
  • --size: number of results, recommended 10–20 (optional)

Use cases

  • Understand which tags surround a topic.
  • Discover popular tags in a vertical domain.
  • Choose suitable tags for publishing content.

3. suggest_categories — category navigation

Provide navigation suggestions in a 3‑level category hierarchy, supporting step‑by‑step exploration.

# Level 1 (top‑level categories)
neta-cli suggest_categories --level 1

# Level 2 (requires parent path)
neta-cli suggest_categories --level 2 --parent_path "Derivative Creation"

# Level 3 (most granular)
neta-cli suggest_categories --level 3 --parent_path "Derivative Creation>Fan Works"

Parameters

  • --level: category level (1/2/3) (required)
  • --parent_path: parent category path, required when level > 1 (optional)

Example taxonomy

Level 1
├─ Derivative Creation
│  ├─ Fan Works (Level 2)
│  │  ├─ Honkai: Star Rail (Level 3)
│  │  └─ Genshin Impact (Level 3)
│  └─ Digital Art
├─ Lifestyle
└─ ...

Use cases

  • Systematically understand the platform’s category structure.
  • Navigate by following the tree to find specific domains.
  • Validate candidate category paths.

4. validate_tax_path — validate taxonomy path

Validate that a taxonomy path string is valid before using it.

neta-cli validate_tax_path --tax_path "Derivative Creation>Fan Works>Honkai: Star Rail"

Parameters

  • --tax_path: full taxonomy path (required)

Use cases

  • Validate paths before using them in filters.
  • Ensure taxonomy paths are accurate.

5. suggest_content — intelligent content feed

Powerful content recommendation tool supporting three modes: recommend, search, and exact.

# Mode 1: recommend (broad exploration)
neta-cli suggest_content \
  --page_index 0 \
  --page_size 20 \
  --scene agent_intent \
  --intent recommend

# Mode 2: search (keyword‑based)
neta-cli suggest_content \
  --page_index 0 \
  --page_size 20 \
  --scene agent_intent \
  --intent search \
  --search_keywords "character,creativity"

# Mode 3: exact (category filtering)
neta-cli suggest_content \
  --page_index 0 \
  --page_size 20 \
  --scene agent_intent \
  --intent exact \
  --tax_paths "Derivative Creation>Fan Works"

# Combined filters
neta-cli suggest_content \
  --page_index 0 \
  --page_size 20 \
  --scene agent_intent \
  --intent search \
  --search_keywords "AI,painting" \
  --tax_paths "Digital Art>Concept Art" \
  --exclude_keywords "test,discarded"

Parameters

  • --page_index: page index, starting from 0 (default 0)
  • --page_size: items per page, 1–40 (default 20)
  • --scene: scene identifier (default "agent_intent")
  • --biz_trace_id: session trace ID (optional)
  • --intent: recommend \| search \| exact (default recommend)
  • --search_keywords: search keywords, separated by commas (optional)
  • --tax_paths: taxonomy paths, separated by commas (optional)
  • --tax_primaries: level‑1 categories (optional)
  • --tax_secondaries: level‑2 categories (optional)
  • --tax_tertiaries: level‑3 categories (optional)
  • --exclude_keywords: excluded keywords (optional)
  • --exclude_tax_paths: excluded taxonomy paths (optional)

Progressive exploration

Standard path (broad → narrow)

graph LR
    A[Browse categories] --> B[Discover tags]
    B --> C[Validate paths]
    C --> D[Fetch content]
Step 1: browse category system
# View all level‑1 categories
neta-cli suggest_categories --level 1
# Example output: ["Derivative Creation", "Digital Art", "Lifestyle"]

# Dive into an interesting category
neta-cli suggest_categories --level 2 --parent_path "Derivative Creation"
# Example: ["Fan Works", "Original Stories", "Interactive Fiction"]
Step 2: discover related tags
# Find tags from a keyword
neta-cli suggest_tags --keyword "Fan Works" --size 15
# Example: ["Honkai: Star Rail", "Genshin Impact", "Arknights"]

# Use keyword suggestions to help
neta-cli suggest_keywords --prefix "Hon" --size 10
Step 3: validate taxonomy path
neta-cli validate_tax_path \
  --tax_path "Derivative Creation>Fan Works>Honkai: Star Rail"
Step 4: fetch recommended content
# Exact mode: filter by taxonomy only
neta-cli suggest_content \
  --intent exact \
  --tax_paths "Derivative Creation>Fan Works>Honkai: Star Rail" \
  --page_size 20

# Search mode: combine keyword and taxonomy
neta-cli suggest_content \
  --intent search \
  --search_keywords "Honkai: Star Rail,fan art" \
  --tax_paths "Derivative Creation>Fan Works" \
  --page_size 20

Common scenarios

Scenario 1: exploration without a clear goal

User is just browsing with no specific goal.

neta-cli suggest_content \
  --intent recommend \
  --page_size 20

Tips:

  • Avoid constraints at first.
  • Let the system recommend based on popularity.
  • Good for serendipitous discovery.

Scenario 2: vague interest direction

User has a rough topic in mind but not specific content.

# Step 1: keyword suggestions
neta-cli suggest_keywords --prefix "game" --size 15

# Step 2: tag suggestions
neta-cli suggest_tags --keyword "game" --size 15

# Step 3: search mode
neta-cli suggest_content \
  --intent search \
  --search_keywords "Genshin Impact" \
  --page_size 20

Scenario 3: clear category goal

# Step 1: confirm taxonomy path
neta-cli suggest_categories --level 1
neta-cli suggest_categories --level 2 --parent_path "Derivative Creation"

# Step 2: validate path
neta-cli validate_tax_path \
  --tax_path "Derivative Creation>Fan Works>Honkai: Star Rail"

# Step 3: exact filter
neta-cli suggest_content \
  --intent exact \
  --tax_paths "Derivative Creation>Fan Works>Honkai: Star Rail" \
  --page_size 20

Scenario 4: pre‑creation research

# Step 1: understand popular tags
neta-cli suggest_tags --keyword "character writing" --size 20

# Step 2: inspect related categories
neta-cli suggest_categories --level 2 --parent_path "Derivative Creation"

# Step 3: view popular content under that category
neta-cli suggest_content \
  --intent search \
  --search_keywords "character,setting" \
  --tax_paths "Derivative Creation>Fan Works" \
  --page_size 30

Scenario 5: excluding unwanted content

neta-cli suggest_content \
  --intent search \
  --search_keywords "AI,painting" \
  --tax_paths "Digital Art" \
  --exclude_keywords "tutorial,ad" \
  --exclude_tax_paths "Digital Art>Courses" \
  --page_size 20

Parameter combination tips

Combination 1: keyword + taxonomy

neta-cli suggest_content \
  --intent search \
  --search_keywords "video,editing" \
  --tax_paths "Digital Art>Video Production" \
  --page_size 20

Combination 2: multi‑level taxonomy

neta-cli suggest_content \
  --intent exact \
  --tax_paths "Derivative Creation>Fan Works>Honkai: Star Rail" \
  --page_size 20

Combination 3: recommend + exclusions

neta-cli suggest_content \
  --intent recommend \
  --exclude_keywords "tutorial, repost" \
  --exclude_tax_paths "Courses" \
  --page_size 20

Combination 4: pagination continuity

# Page 1
neta-cli suggest_content \
  --page_index 0 \
  --page_size 20 \
  --intent search \
  --search_keywords "ideas" > /tmp/page0.json

# Extract biz_trace_id
BIZ_TRACE_ID=$(cat /tmp/page0.json | jq -r '.page_data.biz_trace_id')

# Page 2 (reuse same biz_trace_id)
neta-cli suggest_content \
  --page_index 1 \
  --page_size 20 \
  --intent search \
  --search_keywords "ideas" \
  --biz_trace_id "$BIZ_TRACE_ID"

Output formats

suggest_keywords / suggest_tags / suggest_categories

{
  "suggestions": ["Suggestion 1", "Suggestion 2", "Suggestion 3"]
}

validate_tax_path

Valid path:

{
  "valid": true,
  "message": "Path is valid"
}

Invalid path:

{
  "valid": false,
  "message": "Error message"
}

suggest_content

{
  "module_list": [
    {
      "data_id": "module id",
      "module_id": "module type",
      "template_id": "template id",
      "json_data": {}
    }
  ],
  "page_data": {
    "has_next_page": true,
    "page_index": 0,
    "page_size": 20,
    "biz_trace_id": "trace id"
  }
}

Performance tips

  1. Choose page_size wisely

- Exploration: 10–15 for quick iteration. - Deep browsing: 20–30 to reduce page switches. - Precise lookup: 20–40 to fetch enough content at once.

  1. Cache suggestions

- Cache taxonomy and tag suggestions to avoid repeated calls.

  1. Preload next‑level categories

- While the user is viewing level‑1 categories, preload level‑2 categories in the background.

  1. Batch‑validate taxonomy paths

- Validate multiple candidate paths in parallel or via a simple script.

Debugging tips

  1. Turn on debug logs for suggest_content to verify parameters.
  2. Use exact mode with only taxonomy to test whether a path actually returns content.
  3. Compare recommend, search, and exact with the same topic to understand their differences.

FAQ

Q1: What’s the difference between suggest_keywords and suggest_tags?

  • suggest_keywords: prefix‑based fuzzy matching, good for early exploration.
  • suggest_tags: relevance‑based matching on full keywords, more precise.

Q2: Why does validate_tax_path succeed but suggest_content return empty?

Possible reasons:

  1. The taxonomy path is valid but currently has no content.
  2. Wrong intent mode (e.g., using recommend instead of exact).
  3. Other filters conflict.

Q3: How to choose the right intent?

IntentUse caseRequired params
recommendBrowsing without clear goalNone
searchKeyword‑driven searchsearch_keywords
exactStrict category filteringtax_paths or taxonomy params

Q4: How to use exclude_keywords and exclude_tax_paths?

Use them to aggressively filter noise content, but note they can significantly reduce result count.

Q5: How to maintain biz_trace_id across pages?

Always keep and reuse the first biz_trace_id returned for a given query instead of chaining from page to page.

Summary

Key points for using the exploration skill:

  1. Progressive exploration: Categories → Tags → Validation → Content.
  2. Intent selection: recommend for aimless browsing, search for keyword queries, exact for strict taxonomy.
  3. Combination filters: combine keywords with taxonomy for precise control.
  4. Exclusions: use exclude_* parameters judiciously to filter noise.
  5. Session continuity: maintain a consistent biz_trace_id for stable paging behavior.

By following these practices, you can explore and discover high‑quality content on the platform efficiently.

平台分布

OpenClaw

91.17%
按下载量换算1,968

安全审计

VirusTotal

通过

ClawScan

可疑

Static analysis

通过

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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