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secondbrain-search第二脑搜索

Agent Skill

secondbrain-search 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。

总安装

759

周安装

31

GitHub Stars

12

下载量

243
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

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:secondbrain-search(第二脑搜索)
来源仓库:https://github.com/sergio-bershadsky/ai
仓库路径:skills/secondbrain-search
安装命令:
npx skills add https://github.com/sergio-bershadsky/ai --skill secondbrain-search
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/sergio-bershadsky/ai --skill secondbrain-search

简介

secondbrain-search 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。

  • 它可协助基于关键词或上下文生成检索策略,筛选相关资源或内容,支持研究类任务的信息组织。
  • 通过 npx skills add 命令从指定仓库安装,具体用法请参考原始 README 和项目文档。
  • 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操作。
  • 适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

SKILL.md

Semantic Search

Search your secondbrain knowledge base using semantic similarity (meaning-based) and full-text search.

Prerequisites

  1. qmd installed: Check with which qmd

- Install: bun install -g qmd or npm install -g qmd - First run downloads ~1.5GB models

  1. Search initialized: Check for .claude/search/ directory

- If not initialized, suggest running /secondbrain-search-init

Usage

/secondbrain-search "your natural language query"
/secondbrain-search --entity=adrs "database migration"
/secondbrain-search --recent=30d "authentication"
/secondbrain-search --status=active --tag=kubernetes "deployment"

Workflow

Step 1: Validate Environment

# Check qmd is installed
which qmd

# Check search is initialized
ls .claude/search/

If qmd not installed:

qmd is not installed. Install it with:
  bun install -g qmd
  # or
  npm install -g qmd

Then initialize search with: /secondbrain-search-init

If search not initialized:

Search not initialized for this project.
Run: /secondbrain-search-init

Step 2: Parse Query and Filters

Extract from user input:

FilterSyntaxExample
Entity--entity=<type>--entity=adrs,notes
Recent--recent=<period>--recent=7d, --recent=2w, --recent=1m
Date from--from=<date>--from=2025-01-01
Date to--to=<date>--to=2025-12-31
Status--status=<status>--status=active, --status=!archived
Tag--tag=<tag>--tag=kubernetes
Limit--limit=<n>--limit=10 (default: 5)
Format--format=<fmt>--format=brief, --format=detailed, --format=json

Step 3: Execute Search

Run qmd search command:

cd <project_root>
qmd query "<user_query>" --json --limit=<limit>

Parse JSON output:

{
  "results": [
    {
      "id": "docs/adrs/ADR-0012-kubernetes-deployment.md",
      "score": 0.92,
      "title": "Kubernetes Deployment Strategy",
      "excerpt": "We decided to use Blue-Green deployment for stateless services...",
      "metadata": {
        "frontmatter": {
          "status": "implemented",
          "created": "2025-12-15"
        }
      }
    }
  ]
}

Step 4: Enrich with Metadata

Load YAML records to add entity-specific metadata:

For each result:

  1. Determine entity type from file path (e.g., docs/adrs/ → ADRs)
  2. Load corresponding records from .claude/data/<entity>/records.yaml
  3. Match by file path and enrich with status, tags, dates, etc.

Step 5: Apply Post-Filters

Filter results based on user criteria:

# Pseudocode
for result in results:
    if entity_filter and result.entity not in entity_filter:
        skip
    if status_filter and result.status != status_filter:
        skip
    if tag_filter and tag_filter not in result.tags:
        skip
    if date_filter and not in_date_range(result.date, from_date, to_date):
        skip

Step 6: Format Output

Brief Format (default for >3 results)

## Search Results

**Query:** "kubernetes deployment"
**Results:** 4 matches

1. **[ADR-0012] Kubernetes Deployment Strategy** (0.92)
   Status: implemented | Updated: 2025-12-15

2. **[Note] Kubernetes Scaling Best Practices** (0.87)
   Tags: kubernetes, scaling | Created: 2025-11-20

3. **[Discussion] Platform Team - Deployment Pipeline** (0.79)
   Date: 2025-10-05 | Participants: Alice, Bob

4. **[Task] Implement Canary Deployments** (0.71)
   Status: in_progress | Priority: high

Detailed Format (default for ≤3 results)

## Search Results

**Query:** "kubernetes deployment"
**Results:** 2 matches

---

### 1. [ADR-0012] Kubernetes Deployment Strategy
**Score:** 0.92 | **Status:** implemented | **Category:** infrastructure

**File:** [ADR-0012-kubernetes-deployment.md](docs/adrs/ADR-0012-kubernetes-deployment.md)

**Excerpt:**
> We decided to use Blue-Green deployment for stateless services
> and Rolling updates for stateful workloads. This approach provides
> zero-downtime deployments while minimizing resource overhead...

**Metadata:**
- Created: 2025-12-15
- Author: sergey
- Category: infrastructure

---

### 2. [Note] Kubernetes Scaling Best Practices
**Score:** 0.87 | **Tags:** kubernetes, scaling

**File:** [2025-11-20-kubernetes-scaling.md](docs/notes/2025-11-20-kubernetes-scaling.md)

**Excerpt:**
> Key considerations for scaling Kubernetes deployments:
> 1. Horizontal Pod Autoscaler configuration
> 2. Resource requests and limits
> 3. Pod disruption budgets...

**Metadata:**
- Created: 2025-11-20
- Status: active

JSON Format

{
  "query": "kubernetes deployment",
  "total": 4,
  "results": [
    {
      "entity": "adrs",
      "id": "ADR-0012",
      "title": "Kubernetes Deployment Strategy",
      "file": "docs/adrs/ADR-0012-kubernetes-deployment.md",
      "score": 0.92,
      "excerpt": "We decided to use Blue-Green deployment...",
      "metadata": {
        "status": "implemented",
        "category": "infrastructure",
        "created": "2025-12-15",
        "author": "sergey"
      }
    }
  ]
}

Search Tips

Display helpful tips when no results found:

## No Results Found

**Query:** "foobar nonexistent"

### Tips

1. **Try broader terms** — Use general concepts instead of specific jargon
2. **Check spelling** — Semantic search handles typos but exact terms may miss
3. **Remove filters** — Try without --entity or --status filters first
4. **Use related concepts** — "authentication" instead of "OAuth2"

### Alternative Actions

- `/secondbrain-freshness` — See all recent content
- Run without filters: `/secondbrain-search "foobar"`

Refine Search

After showing results, offer refinement options:

### Refine Search

- `--entity=adrs` — Filter to ADRs only
- `--recent=30d` — Limit to last 30 days
- `--status=active` — Exclude archived items
- `"kubernetes AND deployment"` — Boolean operators

Related Skills

  • secondbrain-search-init — Initialize search for this project
  • secondbrain-freshness — View items by freshness/staleness

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

35.91%
按下载量换算87

Claude

29.27%
按下载量换算71

Cursor

19.88%
按下载量换算48

Gemini CLI

9.18%
按下载量换算22

安全审计

Gen Agent Trust Hub

未通过

Socket

通过

Snyk

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

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 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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