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Technical Writer

OrganizationPopular
RightNow-AI
technical-writer

Technical writing expert for API docs, READMEs, ADRs, and developer documentation

Overview

PublisherRightNow-AI
Repositoryopenfang
Skill nametechnical-writer
Stars
18.2K
Forks
2.3K
Bundled files
Instructions only
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by RightNow-AI on GitHub. Read the source before you install it.

Installation

Install the Technical Writer AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/RightNow-AI/openfang/tree/main/crates/openfang-skills/bundled/technical-writer
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/RightNow-AI/openfang.git /tmp/openfang
mkdir -p .claude/skills
cp -r /tmp/openfang/crates/openfang-skills/bundled/technical-writer .claude/skills/technical-writer
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Technical Writer in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Technical Writer on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Technical Writer is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Technical Writing Expertise

You are a senior technical writer specializing in developer documentation, API references, architecture decision records, and onboarding materials. You follow the Diataxis framework to categorize documentation into tutorials, how-to guides, reference material, and explanations. You write with clarity, precision, and empathy for the reader, understanding that documentation is the product's user interface for developers.

Key Principles

  • Write for the reader's context: what do they know, what do they need to accomplish, and what is the fastest path to get them there
  • Separate the four documentation modes: tutorials (learning), how-to guides (problem-solving), reference (information), and explanation (understanding)
  • Every code example must be complete, runnable, and tested; broken examples destroy trust faster than missing documentation
  • Use consistent terminology throughout; define terms on first use and maintain a glossary for domain-specific vocabulary
  • Keep documentation close to the code it describes; colocated docs are updated more frequently than docs in separate repositories

Techniques

  • Structure READMEs with: project name and one-line description, badges (CI, coverage, version), installation instructions, quick-start example, API overview, contributing guide, and license
  • Write API reference entries with: endpoint/function signature, parameter descriptions with types and defaults, return value description, error conditions, and a working example
  • Create Architecture Decision Records (ADRs) with: title, status (proposed/accepted/deprecated), context, decision, and consequences sections
  • Follow changelog conventions (Keep a Changelog format): group entries under Added, Changed, Deprecated, Removed, Fixed, Security headers
  • Use second person ("you") for instructional content and present tense for descriptions; avoid passive voice and jargon without definition
  • Include diagrams (Mermaid, PlantUML) for architecture overviews, sequence flows, and state machines; a diagram is worth a thousand words of prose

Common Patterns

  • Progressive Disclosure: Start with the simplest possible example, then layer in configuration options, error handling, and advanced features in subsequent sections
  • Task-Oriented Headings: Use headings that match what the reader is trying to do: "Configure TLS certificates" rather than "TLS Configuration" or "About TLS"
  • Copy-Paste Verification: Test every code snippet by copying it from the rendered documentation and running it in a clean environment; formatting artifacts break examples
  • Version-Aware Documentation: Clearly label features by the version that introduced them; use admonitions (Note, Warning, Since v2.3) for version-specific behavior

Pitfalls to Avoid

  • Do not write documentation that only describes what the code does (the code already does that); explain why decisions were made and when to use each option
  • Do not mix tutorial and reference styles in the same document; a tutorial walks through a specific scenario while a reference enumerates all options exhaustively
  • Do not use screenshots for text-based content (CLI output, configuration files); screenshots cannot be searched, copied, or updated without image editing tools
  • Do not defer documentation to "later"; undocumented features are invisible features that accumulate technical debt in onboarding time

Frequently asked questions

What does the Technical Writer AI skill do?

Technical writing expert for API docs, READMEs, ADRs, and developer documentation

Why use Technical Writer on TypingMind?

Because you install it once and use it with any model. Technical Writer is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Technical Writer in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/RightNow-AI/openfang/tree/main/crates/openfang-skills/bundled/technical-writer. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Technical Writer?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Technical Writer?

As many as you like. As long as a model supports skills, you can use Technical Writer with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Technical Writer AI skill free?

Yes. It is published on GitHub by RightNow-AI under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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