What it is

Better Writing is an agent skill for rewriting, drafting, and reviewing prose. Most de-slop skills delete AI tells and converge everything toward one generic "casual human" register. This one adds what those skip:

1. The writer's voice. A user-provided writing sample is the style source of truth, and per-genre dials (directness, warmth, density, polish) replace blanket rules. A board memo and a personal essay get different treatment.
2. Specificity without invention. "Make it concrete" prompts tempt models into fabricating numbers, anecdotes, and named experts. The guardrails and pre-flight preservation check forbid that: missing facts become placeholders or questions, never inventions.
3. Context beats blanket rules. The same dash, hedge, or formal phrase can be a tell in one genre and correct in another. The audit looks for clusters of tells, with an explicit false-positive list so polished human writing survives the pass.

On top of that, it does the expected job well:

• AI-sounding patterns such as significance inflation, vague attribution, promotional padding, and formulaic conclusions
• slop structures such as throat-clearing, binary contrast, false agency, over-signposting, and manufactured drama
• confidence tiers and a near-conclusive-artefact check, so a single quirk never triggers an edit but leaked tool markup or an unfilled [Your Name] placeholder does
• a final pre-flight check before delivery

It also ships with an evaluation harness: fixtures seeded with known tells and known facts, a checker, and a runner that sends each fixture through a real model with the skill loaded.

Before and after

Real input, real output, no cherry-picked single sentences. These pairs double as test fixtures in evals/fixtures/.

A launch email, de-slopped

Before:

I hope this email finds you well! We're thrilled to announce the launch of our groundbreaking new analytics dashboard, which goes live on Monday 15 June. This isn't just an update — it's a game-changer designed to transform your workflow. The dashboard replaces the weekly CSV export, and data now refreshes every hour instead of every seven days, empowering you to unlock deeper insights across teams, projects, and date ranges. To get started on this exciting journey, simply navigate to the Reports tab after logging in. Exciting times lie ahead!

After:

The new analytics dashboard goes live on Monday 15 June. It replaces the weekly CSV export. Data refreshes every hour instead of every seven days, and you can filter by team, project, or date range. Log in and open the Reports tab to try it. Reply here if anything looks wrong and I will take a look.

Every fact survived (the date, the CSV export, the hourly refresh, the Reports tab). Everything else went.

A report paragraph, made specific without inventing anything

Before:

It is important to note that customer churn has become a significant challenge in today's competitive landscape, rising for the second consecutive quarter. Some internal observers suggest the March pricing change and onboarding drop-off may have contributed, underscoring the need for a proactive retention strategy moving forward. The implications are significant.

After:

Churn rose for the second quarter in a row [figure needed from the Q1 report]. Two causes have been flagged internally: the March pricing change and onboarding drop-off. The retention plan should start with those.

Note the placeholder. The skill will not invent a churn figure to make the paragraph sound concrete. If the figure exists in the source material, it goes in; if not, the gap is marked honestly.

A writer's draft, edited without flattening

Writer's draft:

I have rewritten this parser three times now, which is either dedication or a cry for help. Version three finally handles nested quotes, escaped backslashes, and the cursed Windows-1252 em dash that started this whole saga. I am not proud of the regex. It works.

What a generic humaniser pass produces:

After several iterations, the parser now robustly handles nested quotes, escaped backslashes, and Windows-1252 em dashes.

What this skill does: nothing. The draft has a voice, the details are specific, and "a cry for help" is a defendable quirk, not a tell. The skill's job here is to recognise that and leave it alone.

When to use it

Use this skill when an agent needs to improve:

• emails and messages
• essays, posts, and opinion drafts
• reports, proposals, and memos
• documentation and release notes
• marketing copy and product copy
• UI text and microcopy
• any draft that sounds too generic, verbose, evasive, salesy, or AI-written

Installation

The skills.sh CLI is the easiest way to install the skill.

With npx:

npx skills add forjd/better-writing

With bunx:

bunx skills add forjd/better-writing

You can also install from the full GitHub URL:

npx skills add https://github.com/forjd/better-writing
bunx skills add https://github.com/forjd/better-writing

For local development, install from this checkout:

npx skills add /path/to/better-writing
bunx skills add /path/to/better-writing

The CLI collects anonymous install telemetry by default. To opt out:

DISABLE_TELEMETRY=1 npx skills add forjd/better-writing
DISABLE_TELEMETRY=1 bunx skills add forjd/better-writing

You can also copy the folder into your agent skills directory if your agent runtime supports local skill discovery.

Usage

Invoke it explicitly:

Use $better-writing to rewrite this launch email so it sounds direct, warm, and less AI-written.

Or ask for the behaviour naturally:

Humanise this draft without making it casual. Keep the legal caveats intact.

Review this landing-page copy for generic AI writing and give me a sharper version.

Use my writing sample below as the voice reference, then rewrite the article intro.

What is inside

SKILL.md stays concise so agents can load it quickly. The detailed audit material lives in references/ and is loaded only when needed. The evals/ directory is repo tooling; agents do not load it.

Design principles

• Specific beats impressive.
• Direct beats announced.
• Context beats blanket rules.
• Voice beats cleanliness.
• Evidence beats authority theatre.
• Trust the reader.

Validation

CI runs two dependency-free checks on every push and pull request:

python3 scripts/validate.py                      # frontmatter, fixture, and symlink checks
python3 evals/run_evals.py --all evals/examples  # checker self-test

Neither exercises a model. The self-test proves the checker agrees with the hand-written known-good outputs, nothing more. To test the skill itself, run the model runner described under Evaluation; it needs credentials, so it is not part of CI.

You can also validate the skill with the checker from Anthropic's skill-creator skill:

git clone https://github.com/anthropics/skills.git
python3 skills/skills/skill-creator/scripts/quick_validate.py /path/to/better-writing

This checks the required skill metadata and naming rules.

How it differs from its influences

Better Writing started as a synthesis of three skills and one reference page. Each contributed something worth keeping, and each had a gap this skill closes.

See references/sources.md for fuller source notes.

Evaluation

Pattern lists are easy to break: one well-meaning edit and the skill starts flagging human writing or missing a new tell. The evals/ directory holds ten fixture texts seeded with known tells and known facts, a dependency-free checker that verifies a rewrite removed the tells and kept the facts, and a runner that produces the rewrites with a real model.

python3 evals/run_skill.py                                          # run every fixture through claude-opus-5, then check
python3 evals/run_evals.py evals/fixtures/launch-email my-rewrite.md  # check a rewrite you produced some other way

The runner needs the Claude Code CLI on PATH with working credentials. Run it before and after any change to SKILL.md or the references and compare the two reports.

The checker is a smoke test, not a judge. It matches substrings, bounds the length, and rejects the damage a search-and-replace leaves behind (doubled spaces, space before punctuation). A rewrite can pass it and still read badly, so read the outputs in evals/outputs/ as well as the pass counts. See evals/README.md for the fixture list and check format.

A living pattern catalogue

AI tells drift. "Delve" and "tapestry" marked 2023-era output; "it's not just X, it's Y" and dash dependence mark 2025-era output. The pattern lists in references/ are treated as a dated catalogue, not a fixed rulebook:

• The vocabulary list is era-stamped and tiered, so the skill leans on cluster density and structure rather than any single word. Distinctive markers, common-but-overused words, and ordinary English that only shows up across a corpus are flagged differently.
• Additions, changes, and retirements are dated in CHANGELOG.md.
• Patterns that fade from current model output get marked as legacy rather than deleted, so the skill still catches older drafts.
• The false-positive guardrails carry the detector-bias evidence (non-native and neurodivergent over-flagging), and the plain-human, voice-preservation, and academic-hedge evals fail if the skill over-edits clean prose. Detector-evasion is explicitly a non-goal.
• Pull requests adding newly observed tells are welcome. Bring at least one real example and a false-positive note.

Compatibility

The skill follows the standard agent-skill layout (SKILL.md plus lazily loaded references/), so it works in any runtime that discovers skills by folder:

• Claude Code: tested; install via skills.sh or copy into your skills directory.
• OpenAI-compatible clients: agents/openai.yaml provides display metadata and allows implicit invocation.
• Other runtimes: anything that reads SKILL.md frontmatter will pick it up; the references are plain Markdown loaded on demand.

The skills/better-writing/ directory is a tap layout for managers that expect skills/<name>/. It is built from relative symlinks back to the root files, which survive git clone but not GitHub's Download ZIP or a Windows checkout without symlink support. In those cases install from the repo root, which is the canonical copy.

Contributing

Keep the skill lean. Put core workflow guidance in SKILL.md, and move detailed pattern lists or examples into references/.

Before opening a pull request:

1. Run python3 scripts/validate.py. CI runs it on every pull request as well.
2. Run python3 evals/run_skill.py before and after the change if you touched the pattern lists or SKILL.md, and say in the pull request what changed in the two reports.
3. Date any pattern addition, change, or retirement in CHANGELOG.md.
4. Check that new prose uses British English and sentence-case headings. The repo's own docs follow the catalogue.
5. Avoid adding bulky documentation that the agent does not need.
6. Keep examples factual, concise, and easy to audit.

Licence

MIT licence. Copyright (c) 2026 Forjd.