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Suggest Improvements

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ethanplusai
suggest-improvements

List what is worth fixing on a site the conversion reproduced as-is — SEO, content, links, accessibility, performance, security, analytics and design — each item with its path, evidence, effort, risk and whether it can be applied mechanically, plus the agent's own design and content observations. Use after the parity gates and the visual review are green and before the pull request, or when someone asks what could be better on the converted site. It changes nothing.

Overview

Publisherethanplusai
Repositoryastro-conversion-kit
Skill namesuggest-improvements
Stars
110
Forks
20
Bundled files
31
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.

  • 31 bundled files

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

  • Open source

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

Installation

Install the Suggest Improvements 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/ethanplusai/astro-conversion-kit/tree/main/skills/suggest-improvements
  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/ethanplusai/astro-conversion-kit.git /tmp/astro-conversion-kit
mkdir -p .claude/skills
cp -r /tmp/astro-conversion-kit/skills/suggest-improvements .claude/skills/suggest-improvements
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Suggest Improvements 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 Suggest Improvements 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 Suggest Improvements 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.

suggest-improvements

The converted site reproduces the live site on purpose, flaws included. This skill writes down the flaws, with evidence, so the site owner can decide which to fix. It never fixes them.

The golden rule

Nothing from here is applied directly. An improvement becomes a proposal: an entry in proposals.json that ships only in a PROPOSALS=on build until a person approves it, or a later convert-site --apply <id> run that does the same on its own commit. Editing the default build because this report said so breaks parity, and the gates will say so.

When to run

After every parity gate passes and the visual review is green for every page, with review/ still on disk (it feeds the design checks), and before the pull request is opened. The report goes in the PR.

The command

From the site root:

node <skill-dir>/scripts/suggest.mjs --capture capture --baseline baseline --review review --out docs/suggestions.md --json suggestions.json

Add --gates gates.json when the gate runner wrote that file (the header then summarises the gates), and --lighthouse capture/lighthouse-live when that folder exists (it is also the default). Run node <skill-dir>/scripts/suggest.mjs --help for every option.

Exit 0 means the report was written, whatever it found; 2 is a usage error or a missing input. It reads capture/, baseline/ and review/ only and never requests the live site.

Reading the report

docs/suggestions.md opens with the site, the counts and the gates line, then the Not covered list, then one section per category: SEO, Content, Links, Accessibility, Performance, Security, Analytics, Design. Inside each, one heading per check with its reason, then one line per item:

- `/about/` `h1` (`missing-h1`, effort S, risk low)
  - Evidence: no <h1> on the page
  • Path is the page (for a site-wide problem, the first page it appears on).
  • Effort is S, M or L; risk is none, low, medium or high; applyable means convert-site --apply <id> can make the change mechanically.
  • Evidence is what the check saw in the capture: a value, a count, the pages.
  • Grouped items. One problem repeated across the site (a script in the header, an image, a link, a title) is one item, not one per page. The evidence names the page count and the first three pages; pages in suggestions.json lists every page it applies to. Use the JSON when you need the full list.
  • The report ends with How to apply, listing the checks that can be applied mechanically.

Not covered is never a pass. A check with no input (no --review, no Lighthouse reports, no media.json) is listed there, and so is part of one. A check that threw is listed as check failed: <message>; a check whose coverage note threw keeps its items and is listed as (partly): coverage note failed: <message>. The other checks still ran. Quote the whole Not covered list verbatim in the PR, unedited. If --review was missing because review/ was deleted, rerun the visual review's shoot and styles steps and run this again rather than shipping the gap.

What you add by hand

The scripts cannot see everything. At the end of docs/suggestions.md, add a section:

## From the review

- `/services/` hero: the heading overlaps the image at 390 px on live and new alike
  - Evidence: review/index.html, pair /services/ at 390, top of page

What goes there:

  1. Design observations from the contact sheet: anything that looks wrong on live and was reproduced faithfully (cramped spacing, an image cropped badly on mobile, low contrast, a misaligned grid). Name the route and width.
  2. Content issues noticed while building: typos, outdated copy, dead offers, a phone number that differs between pages, a page that duplicates another. Quote the text and name the captured file it came from.

Each line carries the same discipline as the script's items: a path, evidence a person can check (a route and width on the contact sheet, a file under capture/, a quoted snippet), and nothing you did not see. No guesses, no "probably". If the list is empty, write "Nothing further noticed." so the reader knows you looked.

Do not rerun the script after adding the section: it rewrites docs/suggestions.md. Rerun it first if the inputs changed, then add the section again.

Acting on an item

Never in this run. When the person picks an item:

  • Applyable checks: convert-site --apply <id> records the proposal in proposals.json, makes the change on its own commit, reruns the gates and the contact sheet, and ships it only with PROPOSALS=on.
  • Everything else (alt text, copy, which duplicate page to keep, a design fix): a person decides or writes it, and it goes in as a proposal the same way, never into the default build.

The checks

references/catalogue.md lists every check: its id, category, what it looks for, the evidence it cites, its default effort and risk, whether it is applyable, which checks group across pages, and which inputs each check needs. Read it when an item's reason is unclear or a check is missing from the report.

Present the result

  1. The counts per category, then the items with risk medium or high and the applyable ones.
  2. From the review, every line.
  3. Not covered, verbatim: every line of the report's list, unedited. None of it was checked.
  4. What happens next: nothing is applied until the person picks items; each becomes a proposal or a --apply run.

References

FileCovers
references/catalogue.mdEvery check, its evidence, effort, risk, applyability and inputs

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 Suggest Improvements AI skill do?

List what is worth fixing on a site the conversion reproduced as-is — SEO, content, links, accessibility, performance, security, analytics and design — each item with its path, evidence, effort, risk and whether it can be applied mechanically, plus the agent's own design and content observations. Use after the parity gates and the visual review are green and before the pull request, or when someone asks what could be better on the converted site. It changes nothing.

Why use Suggest Improvements on TypingMind?

Because you install it once and use it with any model. Suggest Improvements 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 Suggest Improvements in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/ethanplusai/astro-conversion-kit/tree/main/skills/suggest-improvements. 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 Suggest Improvements?

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 Suggest Improvements?

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

Is the Suggest Improvements AI skill free?

Yes. It is published on GitHub by ethanplusai 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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