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Debug Broken Ui

OrganizationPopular
reticlehq
debug-broken-ui

Find out why something in a running web app does not work, when the console is empty and the code looks correct. Reads the click, the request, the store and the console together and returns the file:line to open. Use when a button does nothing, a form will not submit, data will not load, a page renders blank or stale, a modal will not close, or the user says "it's broken" and the code review says it is fine.

Overview

Publisherreticlehq
Repositoryreticle
Skill namedebug-broken-ui
Stars
1.2K
Forks
176
Bundled files
Instructions only
LicenseApache-2.0
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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

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

Installation

Install the Debug Broken Ui 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/reticlehq/reticle/tree/main/skills/debug-broken-ui
  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/reticlehq/reticle.git /tmp/reticle
mkdir -p .claude/skills
cp -r /tmp/reticle/skills/debug-broken-ui .claude/skills/debug-broken-ui
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Debug Broken Ui 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 Debug Broken Ui 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 Debug Broken Ui 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.

The app is broken and the code looks fine

Reading the source again will not tell you why. The evidence is in the running app, and most of it never reaches the screen: the request that failed, the store that never moved, the handler that was never bound, the element covered by something invisible.

Reticle reads all of it from inside the page. Not installed? RETICLE_INSTALL_SOURCE=npx_skill npx @reticlehq/server@latest init, then the install-and-verify skill.

Do not start by guessing. Start by reproducing.

reticle_look({ action: "page", sessionId, mode: "interactive" })   // controls only, with refs
reticle_act_and_wait({ sessionId, ref, action: "click", until: { kind: "element", query: { testid: "..." } } })

The verdict already narrows it: no / contradicted means a channel saw something incompatible with the UI: you have the bug. unknown means Reticle drove it and could not tell, which is a different investigation from "it failed".

Read the act result before you call anything else. Its summary block already carries the whole causal window of that one click: net {total, errors, headline}, consoleErrors, stateDiffs [{path, from, to}], storageDiffs [{key, from, to}], route, signals, layoutShift, longTasks: real before→after diffs, not counts. The console, network, storage and state calls below are for going DEEPER into something the summary already pointed at. Calling all three straight after an act pays three model round trips (and, in an approval-gated client, three human clicks) for evidence you were already holding.

summary.stateUnwatched: true means the state channel is dark: no subscribable store is registered, so an empty stateDiffs means unwatched, not unchanged, and no state-based conclusion is available until someone registers the store. It is the one field here that is about your instrumentation rather than about the app.

When the summary does point somewhere, read that channel scoped to what you just did: pass since from the act result, or you are reading a buffer that predates the click:

reticle_observe({ action: "console", sessionId, since })
reticle_observe({ action: "network", sessionId, since })
reticle_look({ action: "state", sessionId, store })

The diagnosis table

What you seeWhat it isNext
No request fired at allthe handler is not bound, or a client cache served a stale valuereticle_look { action: "element" } the element for its file:line; check the cache if it is TanStack Query
Request fired, 4xx/5xxa real backend failure the UI swallowedthe response body is in the network entry
2xx but nothing changedthe app never read the response: verdict says outcome_unreadusually a real bug in the success path
Request fine, DOM fine, store staleUI-vs-state desync, invisible to any screenshotreticle_look { action: "state" } is the only witness; this is the highest-value read here
Click did nothing, no errorthe control is dead, occluded, or disabledreticle_look { action: "element" } returns occluded, box (0×0), styles.cursor, opacity
Element "not found" that you can seevirtualised list has not mounted itreticle_scroll_to. A query that misses is not evidence of absence
Looks logged in, behaves logged outthe token never persistedreticle_storage
Console error that predates your clicka pre-existing fault, not your bugcall it out before continuing

Get the file, not a theory

reticle_look({ action: "element", sessionId, ref })

Returns the component and source: { file, line } for the element you are looking at, plus whether it is occluded, sized, disabled or off-theme. That is the pointer to open. End the investigation with a location, not a hypothesis.

When the flow is long

Do not ping-pong act → snapshot → act → snapshot to find the failing step. Drive the journey with reticle_act { steps: [...] } and assert once; the first step whose consequence fails is the one to look at, and you paid a fraction of the calls to find it.

Before you say it is fixed

Re-run the reproduction as a verdict (reticle_act_and_wait with the consequence named up front) rather than eyeballing the page. A fix confirmed by looking at it is the failure mode that created this ticket.

And never weaken the check to make it pass.


Troubleshooting Reticle itself (as opposed to the app): curl https://docs.reticle.sh/troubleshooting.md. Everything else: curl https://docs.reticle.sh/llms.txt. If Reticle could not see something you needed, reticle_session { action: "feedback" } with kind: "gap".

Frequently asked questions

What does the Debug Broken Ui AI skill do?

Find out why something in a running web app does not work, when the console is empty and the code looks correct. Reads the click, the request, the store and the console together and returns the file:line to open. Use when a button does nothing, a form will not submit, data will not load, a page renders blank or stale, a modal will not close, or the user says "it's broken" and the code review says it is fine.

Why use Debug Broken Ui on TypingMind?

Because you install it once and use it with any model. Debug Broken Ui 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 Debug Broken Ui in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/reticlehq/reticle/tree/main/skills/debug-broken-ui. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Debug Broken Ui?

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 Debug Broken Ui?

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

Is the Debug Broken Ui AI skill free?

Yes. It is published on GitHub by reticlehq under the Apache-2.0 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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