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Automate Me

OrganizationPopular
cursor
automate-me

Use for "automate me", "create/update/refresh my -mode skill", "turn/capture my preferences or working style into a skill", or wanting agents to follow how the user works. Drafts or revises a personal -mode skill via create-skill + unslop, optionally pulling fresh evidence from recent transcripts.

Overview

Publishercursor
Repositoryplugins
Skill nameautomate-me
Stars
8K
Forks
728
Bundled files
Instructions only
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 cursor on GitHub. Read the source before you install it.

Installation

Install the Automate Me 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/cursor/plugins.git /tmp/plugins
mkdir -p .claude/skills
cp -r /tmp/plugins/pstack/skills/automate-me .claude/skills/automate-me
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Automate Me 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 Automate Me 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 Automate Me 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.

Automate me

A guided flow for turning the user's working conventions into a skill agents will follow. The output is one -mode skill tailored to them (e.g. jay-mode, priya-mode).

This skill orchestrates three others: an inline mining pass (see step 1), Cursor's built-in create-skill (authoring), and the unslop skill (prose discipline). It sequences them. It doesn't replace them.

Flow

0. Check for an existing skill

Look recursively for .cursor/skills/**/*-mode/SKILL.md and ~/.cursor/skills/*-mode/SKILL.md matching the user's handle. Mode skills can live in a personal category directory (.cursor/skills/<handle>/), not only at the top level. If one exists, confirm intent with AskQuestion (unless they already said "update my skill" or similar):

  • Update the existing skill (default for repeat runs)
  • Start fresh (rare, ask why before doing it)

Update mode changes the rest of the flow:

  • Step 1 mines only history since the skill was last edited (git log -1 --format=%cI <path>).
  • Step 2 asks what's changed or missing, not what to capture from zero.
  • Step 4 edits the existing file in place. Preserve sections the user hasn't contradicted. Revise ones with new evidence. Add new sections only for genuinely new rules.

1. Mine their history

Locate the active workspace's transcripts before fanning out. The system prompt names the workspace's agent-transcripts/ directory. Use only that path. Don't glob across ~/.cursor/projects/*/. That crosses workspace boundaries and reads private chats from unrelated projects.

Survey recent agent conversations within that scope for recurring patterns. Run multiple parallel subagents across slices of history (e.g. last 2-4 weeks, split into 3 slices so each has enough material). Each slice mining subagent reads transcripts from the workspace-scoped path the parent provides, looks for the signals below, and returns a short structured list of patterns it saw with evidence pointers. Default signals worth hunting:

  • Response preferences (length, tone, format, "dumb it down" corrections)
  • Delegation habits (subagents, models, specialized workflows, parallelism)
  • Verification posture (what "done" means, unit tests vs live repro, reviewers)
  • Code and prose discipline (style, principles cited, lint/format tools)
  • Process conventions (worktrees, commits, PRs, review/merge tooling)
  • Meta preferences (fixing skills mid-task, proposing new ones)

Cross-check across slices before elevating a signal. Patterns seen in 2+ slices are high-confidence. Lone signals are weak and usually get dropped.

2. Ask the user directly

Mining misses intent that hasn't come up yet. Use the AskQuestion tool (structured multi-choice) rather than asking the user to type from scratch.

Shape: one or two questions with 4-6 options each, allow_multiple: true for category questions. Start broad ("Which areas matter most?"), then follow up on selected areas with specific options. After the structured rounds, one free-form chat question catches anything the options missed.

Don't dump 20 questions.

3. Cluster findings

Group the combined signals into sections. Common ones (use only what applies):

  • Response style: length, tone, format.
  • Autonomy: how much to do without asking, MCP tool use.
  • Understand first: which skills to reach for when scoping or investigating a change.
  • Subagents: default, parallelism, model-to-task, specialized workflows.
  • Prose / code discipline: principles, lint tools, style guides.
  • Review and verify: repro posture, verification skills, live-testing tools.
  • Process: git worktrees, commits, PRs, review/merge tooling.
  • Skills: skill-authoring habits, fix-the-skill-first, proposing new skills.

The poteto-mode skill shows the shape. Read it for granularity. Don't copy its content. The user's rules are not the same as poteto-mode's.

4. Draft the skill

Use Cursor's built-in create-skill skill to author the skill. Placement:

  • Path: preserve an existing mode skill's category. For a new mode, use .cursor/skills/<handle>/<handle>-mode/SKILL.md when the repo has an established personal category for that handle. Otherwise default to .cursor/skills/<handle>-mode/SKILL.md in the project (or ~/.cursor/skills/<handle>-mode/ if the user prefers a personal skill).
  • Handle: the user's first name or chosen identifier.
  • Frontmatter description: trigger on their name + /<handle>-mode + "work in their style", not on generic keywords like "write code" or "review PR".
  • Frontmatter formatting: follow create-skill's YAML rules. Keep description as one YAML scalar. Quote it or use description: >- with indented continuation lines when punctuation or wrapping requires it.
  • Frontmatter disable-model-invocation: true by default. Opt out only if the user explicitly wants their mode to apply on every turn.

5. Iterate on prose

Apply the unslop skill and create-skill's writing guidelines to every line.

Show the draft to the user and take feedback. Expect multiple iterations. Cut ruthlessly. A mode skill is not a manual.

6. Land it

Work in a worktree off main. Commit and open a PR. Don't push to main directly.

Guardrails

  • Don't overfit to one conversation. A preference stated once and contradicted another time is noise. Require multiple instances before codifying it.
  • Don't be clever. Restating other skills' contents, inventing metaphors, or writing "poetic" prose for an agent reader is cost without benefit. Keep it operational.
  • Reference, don't inline. Other skills the user relies on should appear as path references, not pasted excerpts. Same for any principle docs they maintain elsewhere.
  • Keep sections minimal. Only add a section if the user has a specific, non-default rule there. "Communicate clearly" is not a section. "Short paragraphs. Tables when comparing options. Bullets only when items are genuinely parallel." is.
  • Name conventions generic. Use "the user" or "the human" in imperatives, not the author's first name.
  • Don't force symmetry. If a user has no process rules worth writing down, skip the Process section entirely.

Evaluation

A -mode skill is subjective output. A create-skill-style test/iterate benchmark loop isn't useful here. Vibe-check with the user: does it read like them? Did it miss anything? Then ship.

Run a description-optimization loop only if the skill's trigger accuracy turns out to be a problem in practice.

When not to use

  • User wants a task-specific skill (not working conventions): create-skill alone, no mining required.
  • User wants to capture one narrow workflow (e.g. "how I write commit messages"). That's a regular skill, not a mode skill.

Frequently asked questions

What does the Automate Me AI skill do?

Use for "automate me", "create/update/refresh my -mode skill", "turn/capture my preferences or working style into a skill", or wanting agents to follow how the user works. Drafts or revises a personal -mode skill via create-skill + unslop, optionally pulling fresh evidence from recent transcripts.

Why use Automate Me on TypingMind?

Because you install it once and use it with any model. Automate Me 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 Automate Me in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/cursor/plugins/tree/main/pstack/skills/automate-me. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Automate Me?

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 Automate Me?

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

Is the Automate Me AI skill free?

It is published on GitHub by cursor. Check the repository for licensing terms. 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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