Agent Skills: Models Config Skill

Model configuration editor for ~/.pi/agent/models.json with multi-protocol curl testing support.

UncategorizedID: Dwsy/agent/models-config

Install this agent skill to your local

pnpm dlx add-skill https://github.com/Dwsy/agent/tree/HEAD/skills/models-config

Skill Files

Browse the full folder contents for models-config.

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skills/models-config/SKILL.md

Skill Metadata

Name
models-config
Description
Model configuration editor for ~/.pi/agent/models.json with multi-protocol curl testing support.

Models Config Skill

功能

编辑和管理 ~/.pi/agent/models.json 配置文件,支持多种 API 协议的测试和验证,以及从 https://models.dev/api.json 自动获取模型价格信息。

配置结构

{
  "providers": {
    "provider-name": {
      "baseUrl": "https://api.example.com",
      "apiKey": "sk-xxx",
      "api": "anthropic-messages|openai-completions|openai-responses",
      "authHeader": true
    }
  }
}

使用方法

基本操作

# 编辑配置文件
bat ~/.pi/agent/models.json

# 验证 JSON 格式
python3 -m json.tool ~/.pi/agent/models.json

协议类型

| API 类型 | 用途 | 端点格式 | |---------|------|---------| | anthropic-messages | Claude 消息 API | /v1/messages | | openai-completions | OpenAI Completions API | /v1/chat/completions | | openai-responses | OpenAI Responses API | /v1/responses |

测试方法

1. Anthropic Messages API

export ANTHROPIC_BASE_URL=https://api.xairouter.com
export ANTHROPIC_AUTH_TOKEN=sk-XvsJhNdiXcDYA3e5hzD1AJP5ploMAaFuMTUxp3bHRfCiZRNt

curl $ANTHROPIC_BASE_URL/v1/messages \
  -H "x-api-key: $ANTHROPIC_AUTH_TOKEN" \
  -H "anthropic-version: 2023-06-01" \
  -H "content-type: application/json" \
  -d '{
    "model": "claude-sonnet-4-5",
    "max_tokens": 1024,
    "messages": [{"role": "user", "content": "Hello"}]
  }'

2. OpenAI Completions API (Chat)

export OPENAI_BASE_URL=http://127.0.0.1:8317/v1
export OPENAI_API_KEY=proxypal-local

curl $OPENAI_BASE_URL/chat/completions \
  -H "Authorization: Bearer $OPENAI_API_KEY" \
  -H "content-type: application/json" \
  -d '{
    "model": "glm-4.7",
    "max_tokens": 1024,
    "messages": [{"role": "user", "content": "Hello"}]
  }'

3. OpenAI Responses API

export OPENAI_BASE_URL=http://127.0.0.1:8317/v1
export OPENAI_API_KEY=proxypal-local

curl $OPENAI_BASE_URL/responses \
  -H "Authorization: Bearer $OPENAI_API_KEY" \
  -H "content-type: application/json" \
  -d '{
    "model": "glm-4.7",
    "input": "Hello"
  }'

4. 简化测试脚本

#!/usr/bin/env bash
# test-model.sh

PROVIDER=$1
BASE_URL=$2
API_KEY=$3
MODEL=$4

echo "Testing $PROVIDER with model $MODEL..."

case "$PROVIDER" in
  anthropic)
    curl -s "$BASE_URL/v1/messages" \
      -H "x-api-key: $API_KEY" \
      -H "anthropic-version: 2023-06-01" \
      -H "content-type: application/json" \
      -d "{\"model\":\"$MODEL\",\"max_tokens\":256,\"messages\":[{\"role\":\"user\",\"content\":\"Hi\"}]}" \
      | jq .
    ;;
  openai-chat)
    curl -s "$BASE_URL/chat/completions" \
      -H "Authorization: Bearer $API_KEY" \
      -H "content-type: application/json" \
      -d "{\"model\":\"$MODEL\",\"max_tokens\":256,\"messages\":[{\"role\":\"user\",\"content\":\"Hi\"}]}" \
      | jq .
    ;;
  openai-responses)
    curl -s "$BASE_URL/responses" \
      -H "Authorization: Bearer $API_KEY" \
      -H "content-type: application/json" \
      -d "{\"model\":\"$MODEL\",\"input\":\"Hi\"}" \
      | jq .
    ;;
esac

使用示例:

# 测试 Anthropic
bash test-model.sh anthropic \
  https://api.xairouter.com \
  sk-XvsJhNdiXcDYA3e5hzD1AJP5ploMAaFuMTUxp3bHRfCiZRNt \
  claude-sonnet-4-5

# 测试 OpenAI Chat
bash test-model.sh openai-chat \
  http://127.0.0.1:8317/v1 \
  proxypal-local \
  glm-4.7

常见配置

本地服务 (ProxyPal)

{
  "proxypal": {
    "baseUrl": "http://127.0.0.1:8317/v1",
    "apiKey": "proxypal-local",
    "api": "openai-completions",
    "authHeader": true
  }
}

Cloud 服务 (xAIRouter)

{
  "xairouter": {
    "baseUrl": "https://api.xairouter.com",
    "apiKey": "sk-xxx",
    "api": "anthropic-messages",
    "authHeader": true
  }
}

Ngrok 隧道

{
  "ngrok": {
    "baseUrl": "https://xxx.ngrok-free.dev/v1",
    "apiKey": "proxypal-local",
    "api": "openai-responses",
    "authHeader": true
  }
}

价格更新功能

从 https://models.dev/api.json 获取模型价格并更新到配置文件。

使用方法

# 更新所有模型价格
bun ~/.pi/agent/skills/models-config/update-prices.ts

工作原理

  1. 从 https://models.dev/api.json 获取最新价格数据
  2. 读取 ~/.pi/agent/models.json 配置文件
  3. 按 model ID 智能匹配价格信息
  4. 更新 cost 字段(input/output/cacheRead/cacheWrite)
  5. 显示更新摘要

匹配规则

优先级(从高到低):

  1. 精确匹配:model ID 完全相同
  2. 标准化匹配:去除前缀、版本号后相同
    • anthropic/claude-sonnet-4-5claude-sonnet-4-5
    • claude-sonnet-4-5-20250929claude-sonnet-4-5
  3. 模糊匹配:基于 Levenshtein 距离的相似度匹配(≥70%)
    • 自动匹配最佳相似度的模型
    • 显示匹配相似度百分比

支持的别名映射:

| 你的模型 ID | 匹配到 | |------------|--------| | opus4.5 | claude-opus-4-5 | | claude-sonnet-4-5-20250929 | claude-sonnet-4-5 | | claude-haiku-4-5-20251001 | claude-haiku-4-5 | | z-ai/glm4.7 | glm-4.7 | | minimaxai/minimax-m2.1 | minimax-m2.1 |

模糊匹配示例

即使你的供应商不在 models.dev 中,只要模型名称相似,也会自动匹配:

bun ~/.pi/agent/skills/models-config/update-prices.ts

# 输出示例:
✓ Updated: claude-sonnet-4-5
  Old: {"input":0,"output":0,"cacheRead":0,"cacheWrite":0}
  New: {"input":2.6,"output":13,"cacheRead":0.26,"cacheWrite":3.2}
✓ Updated: glm-4.7
  Fuzzy matched "glm-4.7" -> "zai-glm-4.7" (85.7% similarity)
  Old: {"input":0,"output":0,"cacheRead":0,"cacheWrite":0}
  New: {"input":0,"output":0,"cacheRead":0,"cacheWrite":0}

=== Summary ===
Updated: 15 models
Not found: 3 models

Models without price data:
  - custom-model-x
  - experimental-beta

注意事项

  1. baseUrl 格式

    • anthropic-messages: 不需要 /v1 后缀
    • openai-*: 通常需要 /v1 后缀
  2. 认证方式

    • Anthropic: x-api-key header
    • OpenAI: Authorization: Bearer header
  3. 测试前检查

    • 确认服务端口已启动(如 curl http://127.0.0.1:8317
    • 检查 API Key 有效性
    • 验证网络连通性
  4. 价格更新

    • 模糊匹配阈值:70% 相似度
    • 匹配成功会显示相似度百分比
    • 未匹配的模型会在摘要中列出
    • 价格单位:美元/百万 tokens ($/1M tokens)