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Preservation Verifier

CommunityPopular
conorbronsdon
preservation-verifier

Use when the user provides an original and rewritten version, asks whether a rewrite preserved protected content, or wants a deterministic check for code, frontmatter, quotes, tables, links, paths, numbers, headings, and residual AI-pattern regressions.

Overview

Publisherconorbronsdon
Repositoryavoid-ai-writing
Skill namepreservation-verifier
Stars
4.4K
Forks
393
Bundled files
3
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.

  • 3 bundled files

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

  • Open source

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

Installation

Install the Preservation Verifier 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.
  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/conorbronsdon/avoid-ai-writing.git /tmp/avoid-ai-writing
mkdir -p .claude/skills
cp -r /tmp/avoid-ai-writing/skills/preservation-verifier .claude/skills/preservation-verifier
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Preservation Verifier 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 Preservation Verifier 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 Preservation Verifier 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.

Preservation Verifier

Verify that a rewrite or file edit kept the content the original ../avoid-ai-writing/SKILL.md says to protect.

For cross-Skill work, follow ../avoid-ai-writing-router/references/handoff-contract.md and ../avoid-ai-writing-router/references/skill-graph.json.

Connection contract

Incoming

Accept before/after verification from:

  • avoid-ai-writing-router via ROUTE when the user directly supplies before and after material.
  • voice-preserving-rewriter via VERIFY after returned-text rewriting.
  • file-edit-in-place via VERIFY after an authorized named-file mutation.

Require both original and current versions. If either is unavailable, return control to the router rather than inventing a comparison.

Produce

Update the handoff envelope with:

  • execution_evidence.verifier: executed only if the bundled validator ran, otherwise model_only.
  • verification_summary.status: PASS, REVIEW, or FAIL.
  • blocking errors and warnings.
  • exact repair target when repair is possible.

A FAIL is a blocking workflow result. The rewrite/edit stage is not complete merely because text was produced or a file write succeeded.

Outgoing

  • REPAIR to voice-preserving-rewriter when returned text failed preservation and the shared editing budget has room.
  • REPAIR to file-edit-in-place when a named file failed preservation and the shared editing budget has room.
  • RECHECK to ai-writing-detector only when convergence or a residual audit was part of the user's request.
  • Stop on PASS unless another user-requested stage remains.
  • Stop and report on a second verification failure. Do not start another repair loop.

Architecture and implementation lenses

Apply both encoded lenses from ../avoid-ai-writing-router/references/agency-role-lenses.md:

  • agency-software-architect: verification is a boundary gate with explicit ownership and bounded repair cycles.
  • agency-senior-developer: execution claims require actual command evidence, errors propagate, and before/after state remains attributable to the correct target.

The verifier does not rewrite content itself.

Preferred deterministic path

The bundled scripts/validate.js is an exact copy of the source repository's preservation validator. When Node execution is available, run:

bash
node scripts/validate.js before.md after.md

For programmatic use:

js
const { validate } = require("./scripts/validate.js");

The validator checks protected structures and reports blocking errors separately from warnings. It does not decide whether a semantic change was grounded in an explicit user correction or whether the user specifically authorized editing a normally protected span. Never claim it ran unless the current host executed it.

If execution is unavailable, compare the original and rewrite manually using the same preservation contract and label the result as model_only.

Additional protected constraints

In addition to the canonical validator's structural checks, apply the canonical editing contract in a separate semantic review. Check remaining meaning, attribution, quantities and units, negation, conditions, causality, uncertainty, and speaker experience. Treat an explicit user correction as the intended change rather than an invention. If the user specifically placed a normally protected span in scope, verify that requested change and continue protecting its data and attribution; do not infer permission from a general cleanup, style, or voice request. Report this review as model-only rather than claiming the deterministic validator performed it.

When human_representation_sensitive: true, review identity and representation details protected by the agency-inclusive-visuals-specialist lens. A structurally valid rewrite may still require REVIEW or FAIL if it erased or genericized material cultural, geographic, disability, attire, skin-tone/lighting, physical-reality, or anti-stereotype constraints.

Do not claim the deterministic validator checked semantic representation details that it does not implement. Report that portion separately as model-only semantic review.

Result handling

PASS

No blocking preservation error was found. Continue only if another requested stage remains.

REVIEW

Warnings or semantic changes need judgment but are not automatically blocking. This includes a literal validator difference that corresponds to a specifically requested edit of normally protected content: review it against that scope and its remaining data and attribution constraints instead of automatically repairing it back to the original. Explain the exact uncertainty.

FAIL

Protected content changed or disappeared. Identify the correct repair owner from source kind:

  • returned text -> voice-preserving-rewriter
  • named file -> file-edit-in-place

Pass only the blocking repair scope and existing envelope. Do not ask the repair owner to redo clean parts. If pass.index has reached pass.max, report the unresolved failure instead of requesting another mutation.

Repair-loop limit

At most one repair re-entry is allowed, and only while the requested editing budget has room. The repair consumes the next editing pass. Verification itself does not consume a pass. After repair, verify once more. If that check still fails, stop and report the unresolved errors. Never cycle indefinitely.

Output

Return PASS, FAIL, or REVIEW, verifier execution status, blocking preservation errors, warnings, any separate semantic-guard review, the suggested repair owner, and whether the bounded repair opportunity has already been used.

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 Preservation Verifier AI skill do?

Use when the user provides an original and rewritten version, asks whether a rewrite preserved protected content, or wants a deterministic check for code, frontmatter, quotes, tables, links, paths, numbers, headings, and residual AI-pattern regressions.

Why use Preservation Verifier on TypingMind?

Because you install it once and use it with any model. Preservation Verifier 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 Preservation Verifier in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/conorbronsdon/avoid-ai-writing/tree/main/skills/preservation-verifier. 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 Preservation Verifier?

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 Preservation Verifier?

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

Is the Preservation Verifier AI skill free?

Yes. It is published on GitHub by conorbronsdon 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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