skill-authoring

skill-authoring is a skill for Claude Code, Codex from uvwt/agentdock. It costs 52 tokens per session (2,639 once invoked), scanned A, original, Apache-2.0.

A guide for creating and maintaining AgentDock skills, which are instruction packages that teach an agent how to handle a specific kind of work.

In plain words
What is it for?
Use it to create, modify, refactor, upgrade, test, package, and locally verify first-party skills and their supporting files.
Why use it?
It helps keep skills focused, portable, versioned, documented, tested, and safe to install and update.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to create, modify, refactor, upgrade, test, package, and locally verify first-party skills and their supporting files.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/uvwt/agentdock/skill-authoring
About the project

AgentDock is a runtime that gives AI agents controlled access to files, commands, Git, browsers, containers, and other tools on local computers and remote servers. It is used to let agents write and test code, manage services, inspect systems, and coordinate work across multiple machines within explicit permissions.

uvwt/agentdock · 1,268 stars · on GitHub · nexusdock.co

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add uvwt/agentdock --skill skill-authoring
Clone the repo
git clone --depth 1 https://github.com/uvwt/agentdock

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for skill-authoring

README.md
[![agentmods](https://agentmods.dev/badge/skills/uvwt/agentdock/skill-authoring/github.svg)](https://agentmods.dev/skills/uvwt/agentdock/skill-authoring)
Your own site
<a href="https://agentmods.dev/skills/uvwt/agentdock/skill-authoring"><img src="https://agentmods.dev/badge/skills/uvwt/agentdock/skill-authoring/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for skill-authoring

Your own site · 80×15
<a href="https://agentmods.dev/skills/uvwt/agentdock/skill-authoring"><img src="https://agentmods.dev/badge/skills/uvwt/agentdock/skill-authoring.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 52 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,639 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00052 $0.02639
Opus 5.5 $0.00021 $0.01056
Sonnet 5.5 $0.00010 $0.00528
Haiku 4.5 $0.00005 $0.00264

Measured 27d ago against content hash 1b739bac7851, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

skill-authoring scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 27d ago.

The scan reads SKILL.md. This mod also ships 2 executable files (run.py, tests/test_run.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

core-skills/skill-authoring/SKILL.md · 247 lines

How it starts

The opening of the file, as written. The whole thing — 247 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Skill Authoring

用于创建或维护 AgentDock Skill。Skill 的本体是模型可读取的说明文档;真实操作仍由命令、文件、浏览器、MCP 等工具完成。

AgentDock 不为 Skill 建立独立版本生命周期。Skill 的当前内容由来源与内容摘要识别;同名 managed Skill 更新时直接原子替换当前内容,不保留可选历史 revision,不提供 activate 或 rollback。

核心原则

  1. 先定义模型何时应该选择该 Skill,再写正文。
  2. Skill 核心应兼容 Agent Skills 的文档模型,不把 AgentDock 私有运行时当作通用契约。
  3. 最小 Skill 只有一个 SKILL.md;只有确有需要时才增加 references/、脚本或测试。
  4. 包内资源使用相对路径,业务环境变量由宿主注入当前进程。
  5. 秘密、缓存、会话、数据库、下载结果和设备私有状态不得进入 Skill 包。
  6. 修改后必须真实 lint、测试,并在需要时安装到 AgentDock 验证当前内容。
  7. 不创建或恢复 Skill 自有版本选择、激活、回滚或历史 revision 机制。

完整规范见 references/skill-package-spec.md。

目录

普通第一方和社区 Skill 默认放在独立 Skill 仓库:

skills/<skill-name>/
└── SKILL.md

按需扩展:

skills/<skill-name>/
├── SKILL.md
├── references/
├── scripts/
├── run.py
└── tests/

只有必须随 AgentDock runtime 一起交付的核心 Skill 放在:

core-skills/<skill-name>/

不要创建空目录。

SKILL.md Frontmatter

AgentDock 使用 Agent Skills 风格的字段:

---
name: example-skill
description: 清楚说明何时使用、解决什么问题
license: Apache-2.0
compatibility: Requires Python 3.11 or later.
metadata:
  owner: example-team
allowed-tools: exec_command
---

# Example Skill

AgentDock 真正依赖并严格校验的只有:

  • name 必填,长度 1–64,只允许小写 ASCII 字母、数字和 -,不能以 - 开头/结尾,也不能包含连续 --;
  • description 必填,最长 1024 个 Unicode 字符,并能让模型稳定判断何时使用;重要的 Use when、Do not use 和相邻 Skill 边界条件不要依赖正文补充,因为模型会先用 description 做候选路由;
  • Markdown 正文必须非空;
  • 其他 frontmatter(包括 license、compatibility、metadata、allowed-tools、version 以及第三方扩展字段)由作者生态定义,AgentDock 原样保留但不作为安装/运行前提;
  • 不设计 AgentDock 私有的 version、active_version、revision 或 rollback 契约。

AgentDock 路由索引

AgentDock 会先暴露轻量 description 索引,再按需读取完整 SKILL.md。不同来源的索引预算不同:

  • standalone managed 与 Plugin-owned Skill:agentdock_context.skills 返回 trim 后的完整 description;
  • workspace Skill:workspace_context.workspace_skills 返回 trim 后的完整 description,但最多列出 50 项;
  • shared/common Skill:agentdock_context.common_skills 面向数量不可控的 ~/.agents/skills,最多列出 50 项,并把每项 description 限制在 120 bytes。

因此 authoring 时应把 description 视为路由契约,而不是正文摘要的随意前缀。AgentDock 不提供可配置的 description 截断上限;如果未来 Skill 总量显著增长,应通过索引总预算或检索式路由解决,而不是静默裁掉每个已管理 Skill 的 description 后半段。

Read the full file on GitHub · 247 lines

Files

What ships with it

3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 27d ago Changed · +6 lines 1b739bac7851
  2. 28d ago Changed · +4 lines 87516ae57231
  3. 29d ago Changed · -110 lines · +6 tokens per session 801fe52d65c3
  4. 1mo ago First seen · 347 lines · 46 tokens per session scan A 153b67fcfba8

Subscribe to this mod's changes

skill-authoring is a skill published in the GitHub repository uvwt/agentdock (1,268 stars, last pushed 2d ago), licensed Apache-2.0. It adds 52 tokens to every session and 2,639 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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