v1.0.0 to v1.0.0

---

name: auto-context

display-name: Auto Context

description: 智能上下文检测 - 自动识别AI所需的文件、函数和上下文，优化token使用

version: 1.0.0

category: ai

user-invocable: true

tags: [context, auto-detect, files, tokens, optimization]

capabilities: [intent-detection, file-scoring, token-budgeting]

tools:

- file_reader

- code_analyzer

os: [win32, darwin, linux]

handler: ./handler.js

instructions: |

Use this skill when the AI needs to automatically detect which files and functions are

relevant to a user's query. For --detect mode, extract keywords from the query, score

files by relevance (path match, import chain, recent modification), and return a ranked

list within a token budget. For --budget mode, set the maximum token budget for context.

For --files mode, list files related to a query with scores. Always respect token limits

and prioritize the most relevant files.

examples:

- input: "/auto-context --detect fix the WebRTC connection timeout"

output: "Detected 5 relevant files (2,400 tokens): webrtc-data-channel.js (score: 9.2), P2PClient.kt (7.8), signaling-handlers.js (6.5). Budget: 4096 tokens, used: 2400."

- input: "/auto-context --budget 8000"

output: "Token budget set to 8,000. Context will be trimmed to fit."

- input: "/auto-context --files permission system"

output: "Found 6 files: permission-engine.js (core), team-manager.js, delegation-manager.js, approval-workflow-manager.js, permission-ipc.js, tests/permission.test.js."

input-schema:

type: object

properties:

mode:

type: string

enum: [detect, budget, files]

description: Detection mode

query:

type: string

description: Query to detect context for

tokenBudget:

type: number

description: Maximum token budget

output-schema:

type: object

properties:

files: { type: array }

totalTokens: { type: number }

budget: { type: number }

keywords: { type: array }

model-hints:

preferred: [claude-opus-4-6, gpt-4o]

cost: free

author: ChainlessChain

license: MIT

homepage: https://github.com/nicekid1/ChainlessChain

repository: https://github.com/nicekid1/ChainlessChain

---

# Auto Context 技能

## 描述

智能检测 AI 需要的文件、函数和上下文。通过意图关键词提取、文件相关度评分和 Token 预算管理，自动为 AI 提供最相关的代码上下文。灵感来自 Cursor 的 Auto-context 和 Cline 的上下文管理。

## 使用方法

```

/auto-context [选项]

```

## 模式

### 检测模式 (--detect)

自动检测相关文件和上下文

### 预算模式 (--budget)

设置 Token 预算上限

### 文件模式 (--files)

列出相关文件及评分