How do I install the Authoring App Skills skill?

Run npx skillmds@latest add prostdev/authoring-app-skills in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Authoring App Skills safe to use?

This skill has not completed SkillMD's automated safety review yet. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Authoring App Skills?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Authoring App Skills free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Authoring App Skills?

ProstDev (@prostdev) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Authoring App Skills by prostdev — Agent Skill

Name: Authoring App Skills
Author: ProstDev

Authoring App Skills

Environment specifics for authoring skills that run in the Claude app, Cowork, cloud sessions, or the code-execution sandbox — bundled scripts, package dependencies, evals, and the account-sync loading model. Use when a skill targets the Claude desktop/web app or Cowork rather than a local Claude Code checkout. Assumes the craft in writing-skills.

ProstDev 95c069b 3.1 KB Updated Sep 17, 2026

File contents

Authoring Skills for the Claude App & Cowork

The skill format is identical everywhere. What differs in the app/Cowork/sandbox is the runtime and how skills load. This covers only those differences — the craft lives in writing-skills. For local Claude Code config instead, see claude-md-and-folder-standards.

How skills load here (the gotcha)

Cowork and cloud sessions do NOT read your local ~/.claude. They load skills enabled on your claude.ai account (synced from the desktop app's Customize config) plus skills committed to the repo's .claude/skills/. A skill that only lives on your machine won't reach them — enable it on the account or commit it to the repo.
There is no CLAUDE.md, settings.json, or hooks layer to lean on. The skill must carry its own context; don't reference machine-local config that won't exist in the session.

The sandbox is real — use it

Skills here run in a code-execution environment with a filesystem, bash, and code execution.

Bundle scripts instead of asking the model to regenerate code. A committed scripts/foo.py is more reliable, consistent, and cheaper (only its output enters context) than generated code. Tell the model whether to run it or read it as reference.
Solve in the script; don't defer to the model. Handle the missing file, the bad input — return a sane default with a clear message rather than throwing for the model to untangle.
No voodoo constants. Justify every timeout/retry in a comment; if you can't, neither can the model.
Bundled reference files cost nothing until read — ship complete API docs, datasets, examples, and let progressive disclosure pull them in on demand.

Dependencies differ by surface

claude.ai / desktop app: can install from npm and PyPI at runtime — list required packages in the skill so they get installed.
Claude API: no network, no runtime install — assume nothing beyond the base image.
Never assume a package is present; state the install step.

Prove it works

Write evals before prose. Run the task without the skill, capture where it fails, and build a few concrete scenarios that pin those gaps. The skill's job is to pass them — nothing more.
Author with one model, test with a fresh one. Iterate the skill in one session; verify it in a clean session that only has the skill loaded. Fix what the fresh session actually gets wrong.
Test on every model tier you'll ship to — Haiku may need detail Opus would find redundant.

Portable hygiene

Forward-slash paths only (scripts/x.py), never backslashes.
Fully-qualify MCP tools as ServerName:tool_name, or the model may not find them.

---name: authoring-app-skillsdescription: Environment specifics for authoring skills that run in the Claude app, Cowork, cloud sessions, or the code-execution sandbox — bundled scripts, package dependencies, evals, and the account-sync loading model. Use when a skill targets the Claude desktop/web app or Cowork rather than a local Claude Code checkout. Assumes the craft in writing-skills.---# Authoring Skills for the Claude App & CoworkThe skill *format* is identical everywhere. What differs in the app/Cowork/sandbox is the runtime andhow skills load. This covers only those differences — the craft lives in[`writing-skills`](../writing-skills/SKILL.md). For local Claude Code config instead, see[`claude-md-and-folder-standards`](../claude-md-and-folder-standards/SKILL.md).## How skills load here (the gotcha)- **Cowork and cloud sessions do NOT read your local `~/.claude`.** They load skills enabled on your `claude.ai` account (synced from the desktop app's Customize config) plus skills committed to the repo's `.claude/skills/`. A skill that only lives on your machine won't reach them — enable it on the account or commit it to the repo.- There is no `CLAUDE.md`, `settings.json`, or hooks layer to lean on. The skill must carry its own context; don't reference machine-local config that won't exist in the session.## The sandbox is real — use itSkills here run in a code-execution environment with a filesystem, bash, and code execution.- **Bundle scripts instead of asking the model to regenerate code.** A committed `scripts/foo.py` is more reliable, consistent, and cheaper (only its output enters context) than generated code. Tell the model whether to **run** it or **read** it as reference.- **Solve in the script; don't defer to the model.** Handle the missing file, the bad input — return a sane default with a clear message rather than throwing for the model to untangle.- No voodoo constants. Justify every timeout/retry in a comment; if you can't, neither can the model.- **Bundled reference files cost nothing until read** — ship complete API docs, datasets, examples, and let progressive disclosure pull them in on demand.## Dependencies differ by surface- **claude.ai / desktop app:** can install from npm and PyPI at runtime — list required packages in the skill so they get installed.- **Claude API:** no network, no runtime install — assume nothing beyond the base image.- Never assume a package is present; state the install step.## Prove it works- **Write evals before prose.** Run the task without the skill, capture where it fails, and build a few concrete scenarios that pin those gaps. The skill's job is to pass them — nothing more.- **Author with one model, test with a fresh one.** Iterate the skill in one session; verify it in a clean session that only has the skill loaded. Fix what the fresh session actually gets wrong.- Test on every model tier you'll ship to — Haiku may need detail Opus would find redundant.## Portable hygiene- Forward-slash paths only (`scripts/x.py`), never backslashes.- Fully-qualify MCP tools as `ServerName:tool_name`, or the model may not find them.

Frequently asked questions