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Agent Skill · 研究检索

nm-abstract-skill-authoring(nm 抽象技能创作)

用于辅助安全审计、权限检查、凭据风险、认证流程和常见漏洞排查。它适合让 Agent 梳理敏感配置、检查依赖风险、分析鉴权逻辑或生成安全复核清单。使用时不能把工具输出直接当最终结论,涉及密钥、令牌、用户数据或生产系统时,应先确认最小权限、脱敏方式和操作边界。

nm-abstract-skill-authoring 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为需要联网;许可证为 MIT-0,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 24,002。

总安装 4,121周安装 177GitHub Stars 公开资料未说明下载 1,444核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
1.8.3

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-abstract-skill-authoring(nm 抽象技能创作)
来源仓库:https://github.com/athola/nm-abstract-skill-authoring
安装命令:
openclaw skills install nm-abstract-skill-authoring
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-abstract-skill-authoring

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

nm-abstract-skill-authoring 提供 TDD 方法和说服原则指导新技能开发。适合在创建 Claude Code 技能时遵循结构化流程和测试规范。包含模板、用例设计和评审清单,提升技能质量和可维护性。

安装命令:openclaw skills install nm-abstract-skill-authoring。涉及密钥或用户数据时必须脱敏处理,并遵守最小权限原则。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install nm-abstract-skill-authoring;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

nm-abstract-skill-authoring 怎么安装?

在终端执行 openclaw skills install nm-abstract-skill-authoring。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

nm-abstract-skill-authoring 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

nm-abstract-skill-authoring 需要什么权限?

权限级别是需要联网。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。

nm-abstract-skill-authoring 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

nm-abstract-skill-authoring 用的人多吗?

公开数据是累计安装 4,121 次,近一周安装 177 次,下载 1,444 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

nm-abstract-skill-authoring 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
nm-abstract-skill-authoring

nm 抽象技能创作 · 本页

4,121—需要联网MIT-0通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
skill-authoring
description
|
version
1.8.2
triggers
metadata
{"openclaw": {"homepage": "https://github.com/athola/claude-night-market/tree/master/plugins/abstract", "emoji": "\�\�\️", "requires": {"config": ["night-market.modular-skills"]}}}
source
claude-night-market
source_plugin
abstract
Night Market Skill — ported from claude-night-market/abstract. For the full experience with agents, hooks, and commands, install the Claude Code plugin.

Skill Authoring Guide

Overview

Writing effective Claude Code skills requires Test-Driven Development (TDD) and persuasion principles from compliance research. We treat skill writing as process documentation that needs empirical validation rather than just theoretical instruction. Skills are behavioral interventions designed to change model behavior in measurable ways.

By using TDD, we ensure skills address actual failure modes identified through testing. Optimized descriptions improve discovery, while a modular structure supports progressive disclosure to manage token usage. This framework also includes anti-rationalization patterns to prevent the assistant from bypassing requirements.

The Iron Law

NO SKILL WITHOUT A FAILING TEST FIRST

Every skill must begin with documented evidence of Claude failing without it. This validates that you are solving a real problem. No implementation should proceed without a failing test, and no completion claim should be accepted without evidence. Detailed enforcement patterns for adversarial verification and coverage gates are available in imbue:proof-of-work.

Skill Types

We categorize skills into three types: Technique skills for specific methods, Pattern skills for recurring solutions, and Reference skills for quick lookups and checklists. This helps organize interventions into the most effective format for the task.

Quick Start

Skill Analysis

\\\`bash

Analyze skill complexity

python scripts/analyze.py

Estimate tokens

python scripts/tokens.py \\\`

Validation

\\\`bash

Validate skill structure

python scripts/abstract_validator.py --check \\\`

Verification: Run analysis and review token estimates before proceeding.

Description Optimization

Skill descriptions must be optimized for semantic search and explicit triggering. Follow the formula [What it does] + [When to use it] + [Key triggers]. Use a third-person voice (e.g., "Guides...", "Provides...") and include specific, concrete use cases. Avoid marketing language or vague phrases like "helps with coding."

Skill Character Budget (Claude Code 2.1.32+)

Skill description character budgets now scale with context window at 2% of available context. This means:

Context WindowDescription Budget
200K (Sonnet/Haiku)~4,000 characters
1M (Opus 4.6 GA)~20,000 characters

Previously constrained skills can use more descriptive text on larger windows. However, keep descriptions concise regardless — longer is not better. The scaling primarily prevents truncation for skills with legitimately complex trigger conditions, not as an invitation to add verbose content.

Plugin Name Auto-Display (Claude Code 2.1.33+)

Plugin names are now automatically shown alongside skill descriptions in the /skills menu. Do not repeat the plugin name in skill descriptions — it is redundant and wastes character budget. Focus descriptions on what the skill does and when to use it.

The TDD Cycle for Skills

RED Phase: Document Baseline Failures

Establish empirical evidence that an intervention is needed. Create at least three pressure scenarios that combine time pressure and ambiguity. Run these in a fresh instance without the skill active and document the exact failures, such as skipped error handling or missing validation.

GREEN Phase: Minimal Skill Implementation

Create the smallest intervention that addresses the documented failures. Write the SKILL.md with required frontmatter and content that directly counters the baseline failures. Include one example of correct behavior and verify that the same pressure scenarios now show measurable improvement.

REFACTOR Phase: Anti-Rationalization

Eliminate the ability for Claude to explain away requirements. Run pressure scenarios with the skill active to identify common rationalizations, such as claiming a task is "too simple" for the full process. Add explicit counters, such as exception tables and red flag lists, until rationalizations stop.

Anti-Rationalization

Skills must explicitly counter patterns where Claude attempts to bypass requirements. Common excuses include claiming a task is "too simple" or that a "spirit vs letter of the law" approach is sufficient. Skills should include red flag lists for self-checking, such as "Stop if you think: this is too simple for the full process." When exceptions are necessary, document them explicitly to prevent unauthorized shortcuts.

Module References

For detailed implementation guidance:

  • TDD Methodology: See modules/tdd-methodology.md for RED-GREEN-REFACTOR cycle details
  • Persuasion Principles: See modules/persuasion-principles.md for compliance research and techniques
  • Description Writing: See modules/description-writing.md for discovery optimization
  • Progressive Disclosure: See modules/progressive-disclosure.md for file structure patterns
  • Anti-Rationalization: See modules/anti-rationalization.md for bulletproofing techniques
  • Graphviz Conventions: See modules/graphviz-conventions.md for process diagram standards
  • Testing with Subagents: See abstract:subagent-testing skill for pressure testing methodology
  • Deployment Checklist: See modules/deployment-checklist.md for final validation

Deployment and Quality Gates

Before deploying, verify that the RED, GREEN, and REFACTOR phases are complete and documented. Frontmatter must be valid, descriptions optimized, and line counts kept under 500 lines. Ensure all module references are valid and at least one concrete example is included.

Scribe Validation

All markdown files must pass scribe validation. This includes a slop scan to ensure a score under 2.5 and doc verification to confirm all file paths and command examples work. Bullet-to-prose ratios must remain under 60% to maintain readability. Use Skill(scribe:slop-detector) and Agent(scribe:doc-verifier) for these checks.

Integration and Best Practices

Individual skills are created using skill-authoring, while modular-skills handles the architecture of larger structures. skills-eval provides ongoing quality assessment. Avoid the common pitfall of writing skills based on theoretical behavior; always use documented failures to guide development. Use progressive disclosure to prevent monolithic files and ensure that each intervention remains focused and token-efficient.

Skill Directory Variable (2.1.69+)

Skills can reference their own directory using ${CLAUDE_SKILL_DIR} in SKILL.md content. This variable resolves to the absolute path of the directory containing the SKILL.md file. Use it for referencing sibling files, data assets, or module paths without hardcoding absolute paths:

See `${CLAUDE_SKILL_DIR}/modules/advanced.md`
for detailed patterns.

Run: `python3 ${CLAUDE_SKILL_DIR}/scripts/check.py`

This is especially useful for skills that ship alongside scripts or data files and need portable path references that work regardless of where the plugin is installed.

Description Colon Fix (2.1.69+)

Skill descriptions containing colons (e.g., description: "Triggers include: X, Y, Z") previously failed to load from SKILL.md frontmatter. This is fixed in 2.1.69. Skills without a description: field also now appear in the available skills list (previously they were silently excluded).

Troubleshooting

Common Issues

Skill not loading Check YAML frontmatter syntax and required fields. As of 2.1.69, skills without a description: field still appear in the skills list, but descriptions with colons must be quoted in YAML frontmatter.

Token limits exceeded Use progressive disclosure - move details to modules

Modules not found Verify module paths in SKILL.md are correct

平台分布

OpenClaw

92.28%
按下载量换算1,333

安全审计

VirusTotal

未展示

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。目前只有一个公开来源,建议同时核对源仓库。

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