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integrate-playground综合游乐场

Agent Skill

integrate-playground 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

190

周安装

8

GitHub Stars

1

下载量

67
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:integrate-playground(综合游乐场)
来源仓库:https://github.com/dudusoar/vrp-toolkit
仓库路径:skills/integrate-playground
安装命令:
npx skills add https://github.com/dudusoar/vrp-toolkit --skill integrate-playground
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/dudusoar/vrp-toolkit --skill integrate-playground

简介

用于查找、检索和筛选相关信息。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。

  • 适合根据关键词或任务场景快速定位候选结果。
  • 通过 npx skills add 命令从指定仓库安装并使用。
  • 建议确认权限范围、维护状态及是否触发联网或文件读写操作。
  • integrate-playground 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

Integrate Playground with VRP-Toolkit

Token-efficient workflow for connecting Streamlit playground UI to vrp-toolkit backend APIs.

Core Problem

Developing playground features requires knowing exact API signatures of vrp-toolkit modules. Without reference documentation, this requires repeatedly reading source code (consuming thousands of tokens per integration) and leads to API mismatch errors.

Solution

This skill provides:

  1. Interface Mapping Table - Playground needs → vrp-toolkit APIs
  2. API Quick Reference - Exact signatures with usage examples
  3. Contract Test Integration - Automated verification of interfaces
  4. Common Error Patterns - Troubleshooting guide

Workflow

Step 1: Check Interface Mapping

Before writing any integration code:

  1. Open interface_mapping.md
  2. Find the workflow you're implementing (e.g., "Generate synthetic map")
  3. Note the exact API signature
  4. Check for common mistakes marked with ⚠️

Example:

Need: Generate synthetic map
API: RealMap(n_r: int, n_c: int, dist_function: Callable, dist_params: Dict)
Common mistake: ❌ Don't use num_customers, use n_c

Step 2: Verify with Contract Test (Optional)

If uncertain about API behavior:

  1. Check if contract test exists in contracts/ directory
  2. Run the test: pytest contracts/test_<feature>.py -v
  3. Read test code to see usage examples
  4. Test validates: parameters accepted, attributes available, reproducibility

Example:

pytest contracts/test_realmap_api.py -v
# See test_realmap_initialization() for usage example

Step 3: Write Integration Code

Follow the mapping table exactly:

# ✅ Correct: Use exact signature from mapping table
np.random.seed(seed)  # For reproducibility
real_map = RealMap(
    n_r=num_restaurants,
    n_c=num_customers,
    dist_function=np.random.uniform,
    dist_params={'low': 0, 'high': 100}
)

# ❌ Wrong: Assumed API
real_map = RealMap(
    num_customers=num_customers,
    num_restaurants=num_restaurants,
    area_size=100,
    seed=seed
)

Data access pattern:

  • Most generators create data in __init__, not via .generate() method
  • Access via attributes: .demand_table, .order_table, .time_matrix
  • See interface_mapping.md for each API's pattern

Step 4: Add Error Handling

Common error patterns:

try:
    instance = PDPTWInstance(
        order_table=order_table,
        distance_matrix=real_map.distance_matrix,
        time_matrix=order_gen.time_matrix,
        robot_speed=1.0
    )
except TypeError as e:
    st.error(f"API mismatch: {e}")
    st.info("Check interface_mapping.md for correct parameters")

Step 5: Add Contract Test (For New Integrations)

When adding new playground feature:

  1. Create test in contracts/test_<feature>.py
  2. Test should verify:

- API signature matches mapping table - Reproducibility (same seed → same result) - Feasibility (results meet constraints) - Objective values are consistent

  1. Add test reference to interface_mapping.md

Template:

# contracts/test_new_feature.py
def test_api_signature():
    """Verifies API matches interface_mapping.md"""
    # Test exact parameters...

def test_reproducibility():
    """Same seed produces same result"""
    np.random.seed(42)
    result1 = generate_feature()

    np.random.seed(42)
    result2 = generate_feature()

    assert result1 == result2

Quick Reference Files

For Complete API Details

See api_signatures.md for:

  • Full parameter lists with types
  • Return types and attributes
  • Usage examples
  • Import statements

For Contract Testing

See contract_tests.md for:

  • How to write contract tests
  • Test organization patterns
  • Running and maintaining tests
  • Linking tests to mapping table

For Troubleshooting

See troubleshooting.md for:

  • Common error messages and fixes
  • Module caching issues (need to restart Streamlit)
  • Attribute vs method access patterns
  • Missing parameter errors

Anti-Patterns to Avoid

Don't assume API signatures

  • Always check mapping table first
  • Don't guess parameter names

Don't repeatedly read source code

  • Use this skill's mapping table (< 1000 tokens)
  • Avoid re-reading vrp-toolkit source (several thousand tokens each time)

Don't call non-existent methods

  • Check if it's an attribute or method
  • Most generators use attributes: .demand_table, not .generate()

Don't skip contract tests for complex integrations

  • Tests catch issues early
  • Tests document expected behavior
  • Tests prevent regressions

Maintenance

When vrp-toolkit API changes:

  1. Update interface_mapping.md
  2. Update affected contract tests in contracts/
  3. Run tests to verify: pytest contracts/ -v
  4. Update playground code
  5. Update troubleshooting.md if new error patterns emerge

When adding new playground features:

  1. Add API to interface_mapping.md
  2. Add detailed signature to api_signatures.md
  3. Create contract test in contracts/
  4. Reference test in mapping table

Token Efficiency

Without this skill:

  • Read RealMap source: ~1500 tokens
  • Read DemandGenerator source: ~1200 tokens
  • Read OrderGenerator source: ~1800 tokens
  • Read PDPTWInstance source: ~2000 tokens
  • Total: ~6500 tokens per integration

With this skill:

  • Read interface_mapping.md: ~800 tokens
  • Total: ~800 tokens per integration

Savings: ~5700 tokens (87% reduction)

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

27.99%
按下载量换算19

windsurf

22.32%
按下载量换算15

trae

17.86%
按下载量换算12

OpenCode

11.73%
按下载量换算8

Codex

8.05%
按下载量换算5

github-copilot

2.95%
按下载量换算2

安全审计

Gen Agent Trust Hub

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。

来源信息

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