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Jev Prose

CommunityPopular
pchalasani
jev-prose

Check prose with Jev for narrow AI-writing patterns and revise from its feedback. Use when asked for Jev prose checks, AI-pattern cleanup, or an ongoing check-and-rewrite loop while writing sentences or paragraphs.

Overview

Publisherpchalasani
Repositoryclaude-code-tools
Skill namejev-prose
Stars
2K
Forks
134
Bundled files
6
LicenseMIT
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.

  • 6 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by pchalasani on GitHub. Read the source before you install it.

Installation

Install the Jev Prose 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/pchalasani/claude-code-tools/tree/main/packages/jev-prose/src/jev_prose
  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/pchalasani/claude-code-tools.git /tmp/claude-code-tools
mkdir -p .claude/skills
cp -r /tmp/claude-code-tools/packages/jev-prose/src/jev_prose .claude/skills/jev-prose
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Jev Prose 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 Jev Prose 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 Jev Prose 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.

Jev prose check and revision

Use the jev-prose CLI to get independent, probabilistic editorial feedback. It checks patterns, not authorship. The writer makes the editorial decisions.

Setup

Run jev-prose --help to check availability. From a claude-code-tools checkout, install with uv tool install ./packages/jev-prose. The package carries the persistent question bank; no global skill source paths are needed at runtime. If no checkout or installed CLI is available, report that prerequisite rather than substituting self-review for a Jev result.

Default authentication is CLOUDFLARE_ACCOUNT_ID and CLOUDFLARE_API_TOKEN, or an existing sysone account configuration and Wrangler login. The backend is hosted Jev; the text and optional context are sent there. A configured alternative can be selected with --backend typesafe or --url and --model. Do not print secrets. An authentication or billing failure stops the loop.

Bounded loop

For each requested sentence, paragraph, or short section:

  1. Save the exact draft in a temporary UTF-8 file. Keep the original and track the revision count (initial draft is attempt 0). Preserve the user's intended facts, names, numbers, citations, caveats, voice, and literal quotations.
  2. Run jev-prose check draft.txt --profile general > report.json. For papers, specifications, and formal technical prose use --profile formal. Use strict only when requested; it adds personal editorial preferences. Optional --audience, --voice, and --context context.txt help avoid false positives. Keep these settings and the threshold fixed throughout the loop.
  3. Read the report even when the command exits 1: that means findings, not a failed call. Require ran: true, ok: true, and answered == expected. Exit 2, missing output, malformed JSON, or an incomplete check stops the loop as an error; never label the draft clean in those cases.
  4. If status is clean, stop. Otherwise inspect the flagged questions and guidance against the actual draft. A high probability is not a command to edit: dismiss an inapplicable flag with a brief reason. Jev provides no evidence spans; locate the passage yourself without pretending it supplied an exact quote. Combine overlapping findings into one targeted revision.
  5. If no useful revision follows, stop and disclose the unresolved or dismissed flags. Otherwise revise only the affected prose, increment the attempt count, and return to step 2. Allow at most three revisions and four checks total. Stop earlier if text repeats or feedback cycles without useful improvement. Always check the last revision; never end on an unchecked rewrite.

Preserve substantive claims as well as individual facts. If addressing a finding would weaken, strengthen, remove, or otherwise change a conclusion, leave the claim intact and report the finding unresolved unless the user has authorized factual or argument changes. An unsupported claim is not permission to silently replace the author's intended claim with a different one.

Do not change thresholds to obtain a clean result. Do not add invented examples, anecdotes, feelings, measurements, sources, or stronger claims. Do not remove necessary qualifications or factual content to lower the number of flags. Check meaning against the original after each revision; undo any harmful edit.

A sentence check cannot establish document-level structure. If asked to use this while writing a document, check each completed paragraph and then the finished short section for repetition. Respect the 24,000-character input limit; do not silently truncate. This workflow runs when invoked; it installs no automatic hook.

Return the revised prose in the requested form. Briefly report the number of revisions, check outcome, and any unresolved/dismissed findings. If every finding was dismissed, say that explicitly instead of reporting a model-clean result. Keep detector reports out of published prose unless requested.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Jev Prose AI skill do?

Check prose with Jev for narrow AI-writing patterns and revise from its feedback. Use when asked for Jev prose checks, AI-pattern cleanup, or an ongoing check-and-rewrite loop while writing sentences or paragraphs.

Why use Jev Prose on TypingMind?

Because you install it once and use it with any model. Jev Prose 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 Jev Prose in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/pchalasani/claude-code-tools/tree/main/packages/jev-prose/src/jev_prose. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Jev Prose?

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 Jev Prose?

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

Is the Jev Prose AI skill free?

Yes. It is published on GitHub by pchalasani under the MIT 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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