Fix What I Pointed At logo

Fix What I Pointed At

OrganizationPopular
reticlehq
fix-what-i-pointed-at

Pick up the bugs a human flagged by pointing at them in the running app, each arriving with the element, the note they typed, and the source file and line. Use when the user says they marked or flagged something, when starting a session on an app someone has been clicking through, when a designer or PM has left feedback in the UI, or when the user describes a problem as "that button there" without saying which file.

Overview

Publisherreticlehq
Repositoryreticle
Skill namefix-what-i-pointed-at
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 Fix What I Pointed At 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/fix-what-i-pointed-at
  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/fix-what-i-pointed-at .claude/skills/fix-what-i-pointed-at
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Fix What I Pointed At 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 Fix What I Pointed At 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 Fix What I Pointed At 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 human pointed at the bug. Go fix it.

"The spacing on that card is wrong" is unactionable in chat and precise in the app. Reticle's running app has a Flag a bug control: the human clicks it, points at an element, and types what is wrong. Each flag becomes a mark carrying the element, the note, and the file:line, so the round trip that usually costs a screenshot, a description, and two clarifying questions costs one call.

Not installed? RETICLE_INSTALL_SOURCE=npx_skill npx @reticlehq/server@latest init, then the install-and-verify skill.

Drain the marks

reticle_session({ action: "review", sessionId })
json
{
  "marks": [
    {
      "id": "m1",
      "note": "this button is misaligned",
      "label": "button \"Pay\"",
      "source": { "file": "src/Checkout.tsx", "line": 42 },
      "fix": "Open src/Checkout.tsx:42 and fix: this button is misaligned."
    }
  ],
  "pendingCount": 1
}

Check this at the start of a session, and again whenever the human has been in the app. Reading never consumes a mark, so list → fix → verify → resolve is safe to run in any order.

The loop

  1. Read the marks. Group them if several point at the same file: one edit often answers three.
  2. Open source.file at source.line. This is the whole point: no hunting for which component rendered that button.
  3. Fix what the note asks for. If the note is ambiguous, the element label and its source usually disambiguate it. Ask the human only when they genuinely do not.
  4. Verify in the app, do not eyeball it. Re-drive the affected control with reticle_act_and_wait and name the consequence, or reticle_look { action: "element" } on the element for a layout or theme complaint. A visual fix confirmed by looking at it is how the mark gets reopened.
  5. Resolve it:
reticle_session({ action: "review", sessionId, resolve: "m1" })

Resolve only after the fix is verified. A resolved mark is a promise to the human that the thing they pointed at is done.

When you cannot fix one

Say so against that mark and leave it unresolved. A mark silently dropped is worse than an open one: the human believes it was handled and finds out later. If the note describes intended behaviour rather than a bug, say that too, and let them decide.

Report back in their vocabulary

They pointed at "that button". Report on "the Pay button on checkout", with what you changed and the evidence it now works. Marks come from people who are looking at the screen, not at the repo, so a report full of file paths and no user-facing language answers the wrong question.


Everything else: curl https://docs.reticle.sh/llms.txt. If a mark arrived without a usable source pointer, that is worth a reticle_session { action: "feedback" } with kind: "gap".

Frequently asked questions

What does the Fix What I Pointed At AI skill do?

Pick up the bugs a human flagged by pointing at them in the running app, each arriving with the element, the note they typed, and the source file and line. Use when the user says they marked or flagged something, when starting a session on an app someone has been clicking through, when a designer or PM has left feedback in the UI, or when the user describes a problem as "that button there" without saying which file.

Why use Fix What I Pointed At on TypingMind?

Because you install it once and use it with any model. Fix What I Pointed At 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 Fix What I Pointed At in TypingMind?

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

Which AI models can use Fix What I Pointed At?

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 Fix What I Pointed At?

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

Is the Fix What I Pointed At 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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