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agentifindagentifind 搜索

Agent Skill

agentifind 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

1,901

周安装

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下载量

666
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

3

许可证

MIT

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:agentifind(agentifind 搜索)
来源仓库:https://github.com/avivk5498/agentifind
仓库路径:skills/agentifind
安装命令:
npx skills add https://github.com/avivk5498/agentifind --skill agentifind
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。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/avivk5498/agentifind --skill agentifind

简介

agentifind 用于代码库智能分析,提取结构特征并生成带时效信息的导航指南。

  • 适合需要理解项目架构、追踪动态模式或维护代码知识库的场景。
  • 可检测静态分析无法捕获的动态行为,输出包含文件、函数、类统计信息的结构化报告。
  • 使用前需确认是否已存在现有指南,避免重复生成造成资源浪费。
  • 建议检查仓库权限和网络访问能力,确保能正常读取项目文件。

SKILL.md

Agentifind: Codebase Intelligence Setup

This skill sets up codebase intelligence by:

  1. Running agentifind CLI to extract code structure
  2. Detecting dynamic patterns that static analysis can't fully trace
  3. Synthesizing a navigation guide with staleness metadata

Procedure

Step 1: Check for existing guide (Staleness Detection)

If .claude/CODEBASE.md already exists, check if it's stale:

  1. Read the metadata header from CODEBASE.md: Source-Hash: {sha256 of codebase.json when guide was generated} Commit: {git commit when generated} Stats: {file count, function count, class count}
  2. Compare against current state:

- Run sha256sum.claude/codebase.json (or equivalent) - Run git rev-parse HEAD - Read current stats from codebase.json

  1. If metadata matches: Guide is fresh. Ask user if they want to regenerate anyway.
  2. If metadata differs or missing: Guide is stale. Proceed with regeneration.
  3. If no CODEBASE.md exists: Proceed with generation.

Step 2: Detect repo type and install LSP (if needed)

Check if this is a Terraform/IaC repository:

# Check for .tf files
find . -name "*.tf" -type f | head -1

If Terraform files are found:

Check if terraform-ls is installed. If not, install it for better parsing accuracy:

# Check if terraform-ls exists
which terraform-ls || echo "NOT_INSTALLED"

If NOT_INSTALLED, install terraform-ls:

# macOS (Homebrew)
brew install hashicorp/tap/terraform-ls

# Or via Go (cross-platform)
go install github.com/hashicorp/terraform-ls@latest

Why terraform-ls matters:

  • Proper HCL parsing (not regex)
  • Accurate module resolution
  • Cross-file reference tracking
  • Provider schema awareness

If installation fails, agentifind will fall back to regex parsing (still functional but less accurate).

Step 3: Run agentifind sync

Execute the CLI to extract code structure:

npx agentifind@latest sync

Extraction Method:

  • LSP first (if available): Uses language servers for accurate cross-file resolution

- Python: pyright-langserver (install: npm i -g pyright) - TypeScript: tsserver (bundled with TypeScript) - Terraform: terraform-ls (install: brew install hashicorp/tap/terraform-ls) - Note: LSP extraction can take 5-15 minutes on large codebases (building reference graph)

  • Regex/Tree-sitter fallback: Fast parsing when LSP unavailable (~30 seconds)

This creates .claude/codebase.json with:

  • Module imports/exports
  • Function and class definitions
  • Call graph relationships (more accurate with LSP)
  • Import dependencies

Options:

  • --skip-validate: Skip linting/type checks (faster)
  • --verbose: Show extraction method and progress
  • --if-stale: Only sync if source files changed

Step 4: Update.gitignore

Add the generated files to .gitignore (if not already present):

# Agentifind generated files
.claude/codebase.json
.claude/CODEBASE.md
.claude/.agentifind-checksum

These files are:

  • Regeneratable from source code
  • Large (codebase.json can be several MB)
  • Machine-specific (paths may differ)

Step 5: Read and analyze extracted data

Read .claude/codebase.json and analyze:

  • stats: File/function/class counts
  • modules: Per-file structure (imports, exports, classes, functions)
  • call_graph: What functions call what
  • import_graph: Module dependencies
  • analysis_gaps: Gaps in call graph (see Step 6)
  • validation: Lint/type issues (if present)

Step 6: Review analysis gaps

The CLI automatically detects gaps in the call graph that may indicate dynamic patterns. Read analysis_gaps from codebase.json:

{
  "analysis_gaps": {
    "uncalled_exports": [...],  // Exported functions with no callers
    "unused_imports": [...],    // Imports never referenced
    "orphan_modules": [...]     // Files never imported
  }
}

How to interpret gaps:

Gap TypeWhat It MeansLikely Cause
uncalled_exportsExported function has no detected callersEntry point, CLI command, API handler, test fixture, plugin hook, signal receiver, decorator-invoked
unused_importsImport never referenced in codeSide-effect import, re-export, type-only import, dynamically accessed
orphan_modulesFile never imported by anythingEntry point, script, config file, dynamically loaded plugin

Key insight: If something is exported but never called, or imported but never used, static analysis cannot trace it. These are the areas where the call graph is incomplete.

No manual scanning required - the CLI does this automatically by analyzing the call graph structure.

Step 7: Identify key components

From the data, determine:

  • Entry points: Files with many importers (check import_graph reverse)
  • Core modules: High export count, central in import graph
  • Utilities: Imported by many, import few themselves
  • Request flow: Trace call_graph from entry to output

Step 8: Write CODEBASE.md

First, check repo_type in codebase.json:

  • If repo_type is "terraform" → Use the Infrastructure Template below
  • If repo_type is missing or other → Use the Application Template below

Application Template (default)

Create .claude/CODEBASE.md with this structure:

# Codebase Guide

<!-- STALENESS METADATA - DO NOT EDIT -->
<!--
Generated: {ISO 8601 timestamp}
Source-Hash: {sha256 of codebase.json}
Commit: {git commit hash}
Stats: {files} files, {functions} functions, {classes} classes
-->

## ⚠️ Usage Instructions

This guide provides STARTING POINTS, not absolute truth.

**Before acting on any location:**
1. Verify the file exists with a quick Read
2. Confirm the symbol/function is still there
3. If something seems wrong, the guide may be stale - regenerate with `/agentifind`

**This guide CANNOT see:**
- Runtime behavior (dynamic imports, plugins, DI)
- Configuration-driven logic
- Database queries and their relationships
- External API integrations

## Quick Reference

| Component | Location |
|-----------|----------|
| {name} | `{path}` → `{symbol}` |

## Architecture

### Module Dependencies
{Key relationships from import_graph - focus on core modules}

### Data Flow
{Trace from call_graph if clear pattern exists}

## Analysis Gaps (Potential Dynamic Patterns)

{If analysis_gaps has items, list them here grouped by type}

### Uncalled Exports
{List from analysis_gaps.uncalled_exports - these are likely entry points, API handlers, or dynamically invoked}

| Symbol | File | Reason |
|--------|------|--------|
| {name} | `{file}:{line}` | {reason} |

### Orphan Modules
{List from analysis_gaps.orphan_modules - these are likely entry points or dynamically loaded}

| File | Reason |
|------|--------|
| `{file}` | {reason} |

**What this means:**
- Call graph is incomplete for these symbols/files
- They may be invoked via plugins, signals, decorators, CLI, or configuration
- Always trace execution manually when working in these areas
- Don't assume the call graph shows all callers

{If no gaps found, write: "No analysis gaps detected. Call graph appears complete."}

## Conventions
{Infer from naming patterns, file organization, directory structure}

## Impact Map

| If you change... | Also update... |
|------------------|----------------|
| `{high-dependency file}` | {N} dependent files |

## Known Issues
{From validation.linting/formatting/types if present, otherwise omit section}

Infrastructure Template (for Terraform/IaC repos)

When repo_type is "terraform", create .claude/CODEBASE.md with this structure:

# Infrastructure Guide

<!-- STALENESS METADATA - DO NOT EDIT -->
<!--
Generated: {ISO 8601 timestamp}
Source-Hash: {sha256 of codebase.json}
Commit: {git commit hash}
Stats: {files} files, {resources} resources, {modules} modules
-->

## ⚠️ Usage Instructions

This guide provides STARTING POINTS for infrastructure navigation.

**Before making changes:**
1. Verify the resource/module exists
2. Check the blast radius (what depends on this?)
3. Review variable dependencies
4. Consider state implications

**This guide CANNOT see:**
- Remote state data
- Dynamic values from data sources
- Provider-specific behaviors
- Secrets in tfvars files

## Infrastructure Overview

| Provider | Resources | Modules |
|----------|-----------|---------|
{For each provider in stats.providers, count resources}

## Module Structure

{List from modules array, show source and dependencies}

modules/ ├── {module.name}/ → {module.source} │ └── inputs: {list key variables}

## Resource Inventory

{Group resources by type from resources object}

### {Provider} Resources
| Type | Name | File | Dependencies |
|------|------|------|--------------|
| {type} | {name} | `{file}:{line}` | {dependencies.length} deps |

## Variable Flow

{List from variables array}

| Variable | Type | Used By | Default |
|----------|------|---------|---------|
| {name} | {type} | {used_by.length} resources | {default or "required"} |

## Blast Radius (High Risk)

{List from blast_radius where severity is "high" or "medium"}

⚠️ **Changing these resources affects many dependents:**

| Resource | Affected | Severity |
|----------|----------|----------|
| {target} | {affected_resources.length} resources | {severity} |

**Before modifying high-risk resources:**
- Run `terraform plan` to preview changes
- Consider using `terraform state mv` for refactoring
- Check if changes will force recreation

## Outputs

{List from outputs array}

| Output | Value | Referenced |
|--------|-------|------------|
| {name} | {value} | {references} |

## Dependency Graph

{Describe key relationships from dependency_graph}

Key dependencies:
- `{resource A}` → depends on → `{resource B}`

Step 9: Confirm completion

For application repos, report:

  • Files analyzed (from stats.files)
  • Symbols extracted (from stats.functions + stats.classes)
  • Extraction method used (LSP or tree-sitter)
  • Key entry points identified
  • Analysis gaps detected (count of uncalled_exports, orphan_modules)
  • Any validation issues found
  • Guide staleness metadata recorded

For Terraform/IaC repos, report:

  • Files analyzed (from stats.files)
  • Resources extracted (from stats.resources)
  • Modules detected (from stats.modules)
  • Providers used (from stats.providers)
  • High-risk resources (count from blast_radius with severity "high")
  • Variables defined vs used
  • Guide staleness metadata recorded

Step 10: Offer to update agent instructions

Check if CLAUDE.md or AGENTS.md exists in the project root.

Ask the user:

"Would you like me to add an instruction to your {CLAUDE.md/AGENTS.md} file so the agent automatically uses the CODEBASE.md for navigation?"

If user accepts:

Append this section to the file (or create AGENTS.md if neither exists):

## Codebase Navigation

Before exploring the codebase, read `.claude/CODEBASE.md` for architecture overview, key files, and conventions. This file is auto-generated by agentifind and provides:
- Quick reference to key components
- Module dependencies and data flow
- Dynamic patterns that static analysis can't trace
- Coding conventions
- Impact map for changes

**Important:** The guide provides starting points. Always verify locations before making changes.

If both CLAUDE.md and AGENTS.md exist, update CLAUDE.md (takes precedence).

If user declines:

Respond with:

"No problem! If you change your mind, add this to your CLAUDE.md or AGENTS.md file:" ``markdown ## Codebase Navigation Before exploring the codebase, read .claude/CODEBASE.md for architecture overview, key files, and conventions. ``

Output

.claude/
├── codebase.json         # Structured extraction (CLI output)
├── CODEBASE.md           # Navigation guide (this skill's output)
└── .agentifind-checksum  # Staleness detection

Notes

  • Ground ALL claims in the extracted data - do not hallucinate relationships
  • Keep the guide concise - focus on navigation over explanation
  • Prioritize "what" and "where" over "why" and "how"
  • If codebase.json already exists and is recent, skip Step 2
  • LSP extraction is slower but more accurate for cross-file references
  • Tree-sitter is faster but uses heuristic-based resolution
  • Always include the staleness metadata header - it enables future freshness checks
  • Always include the analysis gaps section - even if none found, document that the call graph is complete

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

04

需要参考平台分布和安装热度时

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

补充不同宿主或平台的使用分布数据

能力 5

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

Claude Code

29.84%
按下载量换算199

Cursor

26.33%
按下载量换算175

Gemini CLI

18.26%
按下载量换算122

Antigravity

12.97%
按下载量换算86

Codex

7.45%
按下载量换算50

OpenCode

3.99%
按下载量换算27

安全审计

Gen Agent Trust Hub

可疑

Socket

通过

Snyk

通过

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/avivk5498/agentifind --skill agentifind;npx skills add avivk5498/agentifind --skill "agentifind" 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

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