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Agent Skill · 研究检索

enrich(enrich 搜索)

enrich 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 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。

enrich 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为执行命令;许可证信息还不明确,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 42,645。

总安装 1,053周安装 43GitHub Stars 12,507下载 337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
unknown

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:enrich(enrich 搜索)
来源仓库:https://github.com/garrytan/gbrain
仓库路径:skills/enrich
安装命令:
npx skills add https://github.com/garrytan/gbrain --skill enrich
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 npx skills 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。

skills.shnpx skills
npx skills add https://github.com/garrytan/gbrain --skill enrich

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。

用于查找、检索和筛选相关信息,支持关键词和任务场景匹配。适合快速定位候选结果,提升信息获取效率。可结合来源仓库和原始 README 核验具体用法。安装前建议确认权限范围和维护状态,避免触发不必要操作。

安装方式:npx skills add https://github.com/garrytan/gbrain --skill enrich

来源仓库内路径:skills/enrich

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 Codex、Claude、Cursor、Gemini CLI;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 npx skills add https://github.com/garrytan/gbrain --skill enrich;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

    它需要执行命令,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

enrich 怎么安装?

在终端执行 npx skills add https://github.com/garrytan/gbrain --skill enrich。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

enrich 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。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。

enrich 需要什么权限?

权限级别是执行命令。安装流程涉及命令执行,可能通过 npx skills add https://github.com/garrytan/gbrain --skill enrich 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

enrich 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

enrich 用的人多吗?

公开数据是累计安装 1,053 次,近一周安装 43 次,下载 337 次,GitHub 12,507 星。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。

enrich 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

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 来源仓库有 12,507 星,维护活跃度相对可查。

先想清楚的地方

  • 需要执行命令,装到常用环境前要先评估影响面。
  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 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 Codex,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

  • 不能接受 Skill 在你机器上执行命令的人。
  • 需要明确授权才能用到公司项目里的场景。
  • 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
enrich

enrich 搜索 · 本页

1,05312,507执行命令未明确有提醒

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

Enrich Skill

Enrich person and company pages from external sources. Scale effort to importance.

Contract

This skill guarantees:

  • Every enriched page has compiled truth (State section) with inline citations
  • Every enriched page has a timeline with dated entries
  • Back-links are created bidirectionally
  • Tiered enrichment: Tier 1 (full), Tier 2 (medium), Tier 3 (minimal) based on notability
  • No stubs: every new page has meaningful content from web search or existing brain context
Filing rule: Read skills/_brain-filing-rules.md before creating any new page.
Convention: See skills/conventions/quality.md for Iron Law back-linking.

Every mention of a person or company with a brain page MUST create a back-link FROM that entity's page TO the page mentioning them. An unlinked mention is a broken brain. See skills/_brain-filing-rules.md for format.

Philosophy

A brain page should read like an intelligence dossier, not a LinkedIn scrape. Facts are table stakes. Texture is the value -- what do they believe, what are they building, what makes them tick, where are they headed.

Citation Requirements (MANDATORY)

Convention: see skills/conventions/quality.md for citation formats and source precedence.

When sources conflict, note the contradiction with both citations.

When To Enrich

Primary triggers

  • User mentions an entity in conversation
  • Entity appears in a meeting transcript or email
  • New contact appears with significant context
  • Entity makes news or has a major event
  • Any ingest pipeline encounters a notable entity

Do NOT enrich

  • Random mentions with no relationship signal
  • Bot/spam accounts
  • Entities with no substantive connection to the user's work
  • Same page enriched within the past week (unless new signal warrants it)

Enrichment Tiers

Scale enrichment to importance. Don't waste API calls on low-value entities.

TierWhoEffortSources
1 (key)Inner circle, close collaborators, key contactsFull pipelineAll available APIs + deep web research
2 (notable)Occasional interactions, industry figuresModerateWeb research + social + brain cross-ref
3 (minor)Worth tracking, not criticalLightBrain cross-ref + social lookup if handle known

The Enrichment Protocol (7 Steps)

Step 1: Identify entities

Extract people, companies, concepts from the incoming signal.

Step 2: Check brain state

For each entity:

  • gbrain search "name" -- does a page already exist?
  • If yes: UPDATE path (add new signal, update compiled truth if material)
  • If no: CREATE path (check notability gate first, then create)

Step 3: Extract signal from source

Don't just capture facts. Capture texture:

Signal TypeWhat to Extract
Opinions, beliefsWhat They Believe section
Current projects, features shippedWhat They're Building section
Ambition, career arc, motivationWhat Motivates Them section
Topics they return to obsessivelyHobby Horses section
Who they amplify, argue with, respectNetwork / Relationships
Ascending, plateauing, pivoting?Trajectory section
Role, company, funding, locationState section (hard facts)

Step 4: External data source lookups

Priority order -- stop when you have enough signal for the entity's tier.

4a. Brain cross-reference (always, all tiers)

  • gbrain search "name" and gbrain query "what do we know about name"
  • Check related pages: company pages for person enrichment and vice versa
  • This is free and often the richest source

4b. Web research (Tier 1 and 2)

  • Use Perplexity, Brave Search, Exa, or equivalent web research tool
  • Key pattern: Send existing brain knowledge as context so the search returns DELTA (what's new vs what you already know), not a rehash
  • Opus-class models for Tier 1 deep research, lighter models for Tier 2

4c. Social media lookup (all tiers when handle known)

  • Pull recent posts/tweets for tone, interests, current focus
  • Social media is the highest-texture signal for what someone actually thinks

4d. People enrichment APIs (Tier 1)

  • LinkedIn data, career history, connections, education

4e. Company enrichment APIs (Tier 1)

  • Company data, financials, headcount, key hires, recent news
Data NeedExample SourcesTier
Web researchPerplexity, Brave, Exa1-2
LinkedIn / careerCrustdata, Proxycurl, People Data Labs1
Career historyHappenstance, LinkedIn1
Funding / company dataCrunchbase, PitchBook, Clearbit1
Social mediaPlatform APIs, web scraping1-3
Meeting historyCalendar/meeting transcript tools1-2

Step 5: Save raw data (preserves provenance)

Store raw API responses via put_raw_data in gbrain:

{
  "source": "crustdata",
  "fetched_at": "2026-04-11T...",
  "query": "jane doe",
  "data": { ... }
}

Raw data preserves provenance. If the compiled truth is ever questioned, the raw data shows exactly what the API returned.

Step 6: Write to brain

CREATE path
  1. Check notability gate (see skills/_brain-filing-rules.md)
  2. Check filing rules -- where does this entity go?
  3. Create page with the appropriate template (below)
  4. Fill compiled truth with citations
  5. Add first timeline entry
  6. Leave empty sections as [No data yet] (don't fill with boilerplate)
UPDATE path
  1. Add new timeline entries (reverse-chronological, append-only)
  2. Update compiled truth ONLY if the new signal materially changes the picture
  3. Update State section with new facts
  4. Flag contradictions between new signal and existing compiled truth
  5. Don't overwrite user-written assessments with API boilerplate
Person page template
---
title: Full Name
type: person
created: YYYY-MM-DD
updated: YYYY-MM-DD
tags: []
company: Current Company
relationship: How the user knows them
email:
linkedin:
twitter:
location:
---

# Full Name

> 1-paragraph executive summary: HOW do you know them, WHY do they matter,
> what's the current state of the relationship.

## State
Role, company, key context. Hard facts only.

## What They Believe
Ideology, first principles, worldview. What hills do they die on?

## What They're Building
Current projects, recent launches, what they're focused on.

## What Motivates Them
Ambition, career arc, what drives them.

## Hobby Horses
Topics they return to obsessively. Recurring themes in their work/posts.

## Assessment
Your read on this person. Strengths, gaps, trajectory.

## Trajectory
Ascending, plateauing, pivoting, declining? Where are they headed?

## Relationship
History of interactions, shared context, relationship quality.

## Contact
Email, social handles, preferred communication channel.

## Network
Key connections, mutual contacts, organizational relationships.

## Open Threads
Active conversations, pending items, things to follow up on.

---

## Timeline
Reverse chronological. Every entry has a date and [Source: ...] citation.
- **YYYY-MM-DD** | Event description [Source: ...]
Company page template
---
title: Company Name
type: company
created: YYYY-MM-DD
updated: YYYY-MM-DD
tags: []
---

# Company Name

> 1-paragraph executive summary.

## State
What they do, stage, key people, key metrics, your connection.

## Open Threads
Active items, pending decisions, things to track.

---

## Timeline
- **YYYY-MM-DD** | Event description [Source: ...]

Step 7: Cross-reference

  • Update company pages from person enrichment (and vice versa)
  • Update related project/deal pages if relevant context surfaced
  • Check index files if the brain uses them

Note (v0.10.1): Links between brain pages are auto-created on every put_page call (auto-link post-hook). Step 7 focuses on content cross-references (updating related pages' compiled truth with new signal from this enrichment), not on creating links. Verify via the auto_links field in the put_page response ({created, removed, errors}). Timeline entries still need explicit gbrain timeline-add calls.

Bulk Enrichment Rules

  • Test on 3-5 entities first. Read actual output. Check quality.
  • Only proceed to bulk after test shots pass your quality bar.
  • 3+ entities from one source -> batch process or spawn sub-agent
  • Throttle API calls. Respect rate limits.
  • Commit every 5-10 entities during bulk runs.
  • Save a report after bulk enrichment (see Report Storage below).

Validation Rules

  • Connection count < 20 on LinkedIn = likely wrong person, skip
  • Name mismatch between brain and API = skip, flag for review
  • Joke profiles or obviously wrong data = save to raw, don't update page
  • Don't overwrite user-written assessments with API boilerplate
  • When in doubt: save raw data but don't update brain page

Report Storage

After enrichment sweeps, save a report:

  • Number of entities processed
  • New pages created vs existing updated
  • Data sources called and results quality
  • Notable discoveries or contradictions
  • Validation flags or API failures

This creates an audit trail for brain enrichment over time.

Anti-Patterns

  • Creating stub pages with no content
  • Enriching without checking brain first
  • Overwriting user's direct statements with API data
  • Creating pages for non-notable entities

Output Format

An enriched person page contains:

  • Frontmatter with type, tags, company, relationship, and contact fields
  • Executive summary (1 paragraph: how you know them, why they matter, relationship state)
  • State section with hard facts and inline [Source:...] citations
  • Texture sections (What They Believe, What They're Building, What Motivates Them, Hobby Horses)
  • Assessment with trajectory read
  • Relationship history and contact info
  • Network connections and mutual contacts
  • Timeline in reverse chronological order, every entry dated with source citation

An enriched company page contains:

  • Frontmatter with type and tags
  • Executive summary (1 paragraph)
  • State section (what they do, stage, key people, metrics, your connection)
  • Open Threads (active items, pending decisions)
  • Timeline in reverse chronological order with dated, cited entries

Both page types have bidirectional back-links to every entity they mention.

Tools Used

  • Read a page from gbrain (get_page)
  • Store/update a page in gbrain (put_page)
  • Add a timeline entry in gbrain (add_timeline_entry)
  • List pages in gbrain by type (list_pages)
  • Store raw API data in gbrain (put_raw_data)
  • Retrieve raw data from gbrain (get_raw_data)
  • Link entities in gbrain (add_link)
  • Check backlinks in gbrain (get_backlinks)

平台分布

Codex

33.33%
按下载量换算112

Claude

31.33%
按下载量换算106

Cursor

20.31%
按下载量换算68

Gemini CLI

10.09%
按下载量换算34

安全审计

Gen Agent Trust Hub

可疑

Socket

可疑

Snyk

可疑

权限和风险

执行命令

安装流程涉及命令执行,可能通过 npx skills add https://github.com/garrytan/gbrain --skill enrich 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

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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