Agent skill

Technical Writing Workflow

by tokenbender in tokenbender/agent-guides

A skill your agent uses for planning, researching, drafting, revising, or auditing technical write-ups, textbooks, papers, reports, READMEs, research notes, PR narratives, and public technical prose.

Apache-2.0Auto-check passedWriting & Content

Install Technical Writing Workflow

skills CLI
$ npx skills add tokenbender/agent-guides --skill technical-writing-workflow -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install tokenbender/agent-guides technical-writing-workflow --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/tokenbender/agent-guides.git skills-src && mkdir -p .claude/skills && cp -r skills-src/claude-skills/technical-writing-workflow .claude/skills/technical-writing-workflow && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
technical-writing-workflow
GitHub stars
367
Token cost
~1.3k tokens
SKILL.md length
599 words
Files
6 (incl. scripts)
Skills in repo
11
Repo updated
First seen
Licence
Apache-2.0

At a glance

A skill your agent uses for planning, researching, drafting, revising, or auditing technical write-ups, textbooks, papers, reports, READMEs, research notes, PR narratives, and public technical prose.

  • Works in 10 steps: Intake → Source audit → Ontology table → …
  • Auditing technical write-ups
  • SKILL.md covers Core rule, Serial before parallel, The workflow and Scripts
  • Runs Python scripts from its folder; calls python

What it does

Technical Writing Workflow is an agent skill from tokenbender/agent-guides. Use for planning, researching, drafting, revising, or auditing technical write-ups, textbooks, papers, reports, READMEs, research notes, PR narratives, and public technical prose. Applies a full workflow, not only style rules: reader need, source audit, ontology, outline contracts, parallel research packets, serial synthesis, claim-boundary checks, plain-English rewrite, anti-LLM prose audit, citation audit, and final render or publication readiness.

Its SKILL.md is about 1.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 7 other files, including scripts (for example `agents/openai.yaml`, `scripts/anti_llm_pattern_audit.py` and `scripts/citation_audit.py`).

It sits in Writing & Content, covering Plain language and style rules, Technical writing and Technical documentation. The repository describes itself as: one page guides that i let my subscribed/customised agents consume to perform actions. The licence is Apache-2.0.

When your agent uses it

  • Auditing technical write-ups
  • Public technical prose

Example prompts

  • “/technical-writing-workflow”

Requirements

  • Python 3

Workflow steps

10 steps, taken from the step headings in SKILL.md.

  1. Intake
  2. Source audit
  3. Ontology table
  4. Outline contracts
  5. Draft
  6. Rigor pass
  7. Plain-English pass
  8. Anti-LLM prose pass
  9. Citation and source pass
  10. Final readiness

What it can do on your machine

Read from SKILL.md and the folder at commit a74dd9d. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 4 files in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Technical Writing Workflow loads about 1.3k tokens when it runs. Until then it costs about 120 tokens; SKILL.md has 599 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~120
When it runs · the whole SKILL.md, loaded when a task matches
~1.3k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from tokenbender/agent-guides at commit a74dd9d, republished under its Apache-2.0 licence (© tokenbender). 599 words, ~1,274 tokens.

Download SKILL.mdSave it as .claude/skills/technical-writing-workflow/SKILL.md (or your agent's skills folder). This skill also uses 5 other files; get the full folder from GitHub.
name
technical-writing-workflow
description
Use for planning, researching, drafting, revising, or auditing technical write-ups, textbooks, papers, reports, READMEs, research notes, PR narratives, and public technical prose. Applies a full workflow, not only style rules: reader need, source audit, ontology, outline contracts, parallel research packets, serial synthesis, claim-boundary checks, plain-English rewrite, anti-LLM prose audit, citation audit, and final render or publication readiness.

Technical writing workflow

Use this skill when the user asks to write, rewrite, improve, audit, explain, teach, document, or publish technical material. Treat it as a workflow with checks, not as a prose vibe.

Core rule

Open the subject up without making it shallow.

Every important explanation must name:

  1. the object or behavior being described
  2. the method, mechanism, or actor that changes it
  3. the evidence that supports the claim
  4. the boundary the claim is allowed to cover

Serial before parallel

Serialize meaning. Parallelize collection.

Do these serially before drafting:

  1. Define the reader and use case.
  2. Define scope and exclusions.
  3. Build the ontology table.
  4. Decide the argument order.
  5. Write chapter or section contracts.
  6. Resolve source contradictions.

Then parallelize:

  • source packets
  • paper cards
  • glossary entries
  • examples
  • diagrams
  • exercises
  • tables
  • reference checks
  • local fact checks
  • counterexamples and failure modes

Return to serial work for:

  • synthesis
  • final claim strength
  • voice and terminology
  • cross-references
  • final layout or render inspection

The workflow

1. Intake

Write a short brief before drafting:

  • audience
  • task the reader should perform after reading
  • source surface
  • deliverable format
  • deadline or depth target
  • claim-risk level

If any of these are unknown, make a conservative assumption and state it briefly.

2. Source audit

Separate sources into evidence classes:

  • primary paper or official documentation
  • benchmark or measurement artifact
  • code or reproducibility artifact
  • technical blog or explainer
  • social post or pointer
  • local note or capture

Do not let a pointer carry a claim that belongs to a paper, code artifact, or measurement.

3. Ontology table

For each major topic, create this table before drafting:

text
Topic:
Object:
Method:
Resource or behavior changed:
Evidence:
Boundary:
Common beginner mistake:
Best example:

This table is the backbone. If it is confused, the prose will be confused.

4. Outline contracts

Each section needs a job:

text
Section:
Reader outcome:
Core sources:
Example:
Warning:
What not to include:

Do not write full prose until the contracts are stable.

5. Draft

Write from the reader's next question.

  • Start with the familiar.
  • Introduce one new idea per paragraph.
  • Name the concept after the intuition lands.
  • Use concrete examples before abstraction when possible.
  • Keep implementation runbook detail out of main prose unless implementation is the contribution.
Show full SKILL.md (254 more words)Show less
6. Rigor pass

Check every claim:

  • what changed
  • what stayed fixed
  • what evidence supports it
  • what the claim does not prove
  • whether examples are examples rather than definitions
  • whether setup details affect validity, comparability, or reproducibility
7. Plain-English pass

Use active voice. Prefer short sentences. Use everyday words where they preserve precision.

Replace:

  • utilise with use
  • leverage with use
  • facilitate with help
  • in order to with to
  • with regard to with about
  • commence with start
  • sufficient with enough

Keep technical terms when they are needed, but earn them before using them heavily.

8. Anti-LLM prose pass

Remove patterns that make prose feel generated unless the user explicitly wants that register:

  • em dashes as default punctuation
  • "not only X but also Y"
  • "in conclusion", "moreover", "furthermore", "it is worth noting"
  • "delve", "landscape", "robust", "seamless", "holistic", "unlock", "empower"
  • vague hype such as groundbreaking, revolutionary, transformative
  • generic title forms such as "The power of X", "Ultimate guide", "X, explained"
9. Citation and source pass

Check that citations support the exact claim nearby. Prefer primary sources. Use descriptive link text when writing web prose. For PDFs or papers, include enough source detail to let another reader recover the artifact.

10. Final readiness

Before delivering:

  • run applicable scripts in scripts/
  • verify links or local file paths when practical
  • for PDF/DOCX/HTML deliverables, render or preview the final artifact
  • state any checks that could not be completed

Scripts

The bundled scripts are optional but preferred for non-trivial prose:

bash
python scripts/prose_audit.py path/to/file.md
python scripts/heading_audit.py path/to/file.md
python scripts/citation_audit.py path/to/file.md
python scripts/anti_llm_pattern_audit.py path/to/file.md

Use script output as a review surface, not as an automatic rewrite command.

© tokenbender, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 5 other files (scripts) in claude-skills/technical-writing-workflow of tokenbender/agent-guides.

  • SKILL.md
  • agents/openai.yaml
  • scripts/anti_llm_pattern_audit.py
  • scripts/citation_audit.py
  • scripts/heading_audit.py
  • scripts/prose_audit.py

Open the folder on GitHubat commit a74dd9d

Compare with similar skills

Technical Writing Workflow next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Technical Writing Workflow compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Technical Writing Workflow this skilltokenbender/agent-guides367—~1.3kAutomated safety check: PassApache-2.0
Technical Writing Standardcursor/plugins10k10 repos~2.4kAutomated safety check: PassNone
JavaScript Concept Page Writerleonardomso/33-js-concepts67k—~14kAutomated safety check: PassMIT
ISO 24495-3 Technical Plain LanguageGaZmagik/iso-24495188—~1.6kAutomated safety check: PassMIT
Technical Writingcitypaul/.dotfiles739—~2.5kAutomated safety check: PassMIT
Tabler Docs Writertabler/tabler42k—~2.5kAutomated safety check: PassMIT

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Questions about Technical Writing Workflow

What does Technical Writing Workflow do?

A skill your agent uses for planning, researching, drafting, revising, or auditing technical write-ups, textbooks, papers, reports, READMEs, research notes, PR narratives, and public technical prose. Technical Writing Workflow is an agent skill from tokenbender/agent-guides. Use for planning, researching, drafting, revising, or auditing technical write-ups, textbooks, papers, reports, READMEs, research notes, PR narratives, and public technical prose.

When should I use Technical Writing Workflow?

Technical Writing Workflow fits situations like: auditing technical write-ups; public technical prose.

How do I install Technical Writing Workflow in Claude Code?

Run `npx skills add tokenbender/agent-guides --skill technical-writing-workflow -a claude-code`. Or copy the skill folder (claude-skills/technical-writing-workflow in tokenbender/agent-guides) into .claude/skills/technical-writing-workflow in your project. Claude Code loads it when a task matches its description.

How do I install Technical Writing Workflow in Codex?

Run `npx skills add tokenbender/agent-guides --skill technical-writing-workflow -a codex`. Or copy the skill folder (claude-skills/technical-writing-workflow in tokenbender/agent-guides) into .agents/skills/technical-writing-workflow in your project. Codex loads it when a task matches its description.

Can I use Technical Writing Workflow in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add tokenbender/agent-guides --skill technical-writing-workflow -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/technical-writing-workflow, .gemini/skills/technical-writing-workflow, .github/skills/technical-writing-workflow and .opencode/skills/technical-writing-workflow in your project.

What does Technical Writing Workflow need to run?

Going by SKILL.md and its folder, Technical Writing Workflow needs Python for the scripts in its folder and the command-line tools its instructions call (python). Our summary lists: Python 3.

Does Technical Writing Workflow access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Technical Writing Workflow safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Technical Writing Workflow use?

Technical Writing Workflow is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Technical Writing Workflow use?

About 1.3k tokens (SKILL.md is roughly 5.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Technical Writing Workflow?

Skills that share tags, products or a category with Technical Writing Workflow: Technical Writing Standard (cursor/plugins, 10k stars), JavaScript Concept Page Writer (leonardomso/33-js-concepts, 67k stars), ISO 24495-3 Technical Plain Language (GaZmagik/iso-24495, 188 stars) and Technical Writing (citypaul/.dotfiles, 739 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Technical Writing Workflow?

tokenbender (a GitHub user) maintains it in tokenbender/agent-guides, which has 367 GitHub stars. The repository holds 11 skills in this directory. The repository was last updated on July 23, 2026.

Source: tokenbender/agent-guides on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.