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nm-pensive-api-reviewNM pensive API 审查

Agent Skill

用于辅助 API 设计、接口文档、请求响应结构和服务集成说明。它适合让 Agent 梳理 endpoint、生成 OpenAPI 草稿、检查字段命名、整理错误码或辅助前后端联调。使用时需要确认真实业务语义、鉴权方式、分页和错误处理规则;涉及生成接口文档时,应避免凭空补字段,最好从现有代码、schema 或接口样例中提取事实。

总安装

2,206

周安装

91

GitHub Stars

公开资料未说明

下载量

721
OpenClaw

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

MIT-0

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:nm-pensive-api-review(NM pensive API 审查)
来源仓库:https://github.com/athola/nm-pensive-api-review
安装命令:
openclaw skills install nm-pensive-api-review
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 OpenClaw 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。

ClawHubOpenClaw
openclaw skills install nm-pensive-api-review

简介

用于辅助 API 设计、接口文档和服务集成说明。

  • 适合梳理 endpoint、生成 OpenAPI 草稿或检查字段命名。
  • 使用时需确认业务语义、鉴权方式和错误处理规则。
  • 安装命令:openclaw skills install nm-pensive-api-review。
  • 建议确认权限范围和维护状态,避免凭空补字段。

SKILL.md

name
api-review
description
Evaluate API surface design, consistency, documentation, and exemplar alignment
version
1.8.2
triggers
metadata
{"openclaw": {"homepage": "https://github.com/athola/claude-night-market/tree/master/plugins/pensive", "emoji": "\�\�", "requires": {"config": ["night-market.pensive:shared", "night-market.imbue:proof-of-work"]}}}
source
claude-night-market
source_plugin
pensive
Night Market Skill — ported from claude-night-market/pensive. For the full experience with agents, hooks, and commands, install the Claude Code plugin.

API Review Workflow

Table of Contents

  1. Usage
  2. Required Progress Tracking
  3. Workflow

Usage

Use this skill to review public API changes, design new surfaces, audit consistency, and validate documentation completeness. Run it before any API release to confirm alignment with project guidelines.

Required Progress Tracking

  1. api-review:surface-inventory
  2. api-review:exemplar-research
  3. api-review:consistency-audit
  4. api-review:docs-governance
  5. api-review:evidence-log

Workflow

Step 1: Surface Inventory

Catalog all public APIs by language. Record stability levels, feature flags, and versioning metadata. Use tools like rg to find public symbols (e.g., pub in Rust or non-underscored def in Python). Confirm the working tree state with git status before starting.

Step 2: Exemplar Research

Identify at least two high-quality API references for the relevant language, such as pandas, requests, or tokio. Document their patterns for namespacing, pagination, error handling, and structure to serve as a baseline for the audit.

Step 3: Consistency Audit

Compare the project's API against the identified exemplar patterns. Analyze naming conventions, parameter ordering, return types, and error semantics. Identify duplication, leaky abstractions, missing feature gates, and documentation gaps.

Step 4: Documentation Governance

Validate that documentation includes entry points, quickstarts, and a complete API reference. Verify that changelogs and migration notes are maintained. Check for SemVer compliance, stability promises, and clear deprecation timelines. Confirm that documentation is generated automatically using tools like rustdoc, Sphinx, or OpenAPI.

Step 5: Evidence Log

Record all executed commands and findings. Summarize the final recommendation as Approve, Approve with actions, or Block. Include specific action items with assigned owners and due dates.

API Quality Checklist

Naming

Confirm consistent conventions and descriptive names that follow language-specific idioms.

Parameters

Verify consistent ordering and ensure optional parameters have explicit defaults. Check that type annotations are complete.

Return Values

Analyze return patterns for consistency. Confirm that error cases are documented and that pagination follows a uniform structure.

Documentation

Verify that all public APIs include usage examples and that the changelog reflects current changes.

Output Format

The final report must include a summary of the API surface, a numerical inventory of endpoints and public types, and an alignment analysis against researched exemplars. Document consistency issues and documentation gaps with precise file and line references. Conclude with a clear decision and a timed action plan.

Technical Integration

Use imbue:proof-of-work for reproducible command capture and imbue:structured-output for formatting findings. Reference imbue:diff-analysis/modules/risk-assessment-framework when assessing breaking changes.

Module Reference

  • See modules/surface-inventory.md for API cataloging patterns
  • See modules/exemplar-research.md for researching API standards
  • See modules/consistency-audit.md for cross-API consistency checks

Troubleshooting

If the audit command is missing, verify that dependencies are installed and accessible in the system PATH. Check file permissions if access errors occur. Use the --verbose flag to inspect execution logs if the tool behaves unexpectedly.

适合场景

01

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02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

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

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

OpenClaw

73.24%
按下载量换算528

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

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。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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