---
name: automate-me
description: "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 using session history exposed by the active Copilot client and the Agent Skills format."
---

# 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`).

Use the active Copilot client's documented skill-creation feature when available. VS Code provides `/create-skill`; other clients may require authoring the file directly using the Agent Skills format. Apply the **unslop** skill for prose.

## Flow

### 0. Check for an existing skill

Look recursively for `.github/skills/**/*-mode/SKILL.md` and `~/.copilot/skills/**/*-mode/SKILL.md` matching the user's handle. Mode skills can live in a project category directory (`.github/skills/<handle>/`), not only at the top level. If one exists, confirm intent with `ask the user` (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

Survey session history exposed by the active Copilot client. Copilot CLI supports `/chronicle search`; use another client's documented history UI where available. Do not assume raw transcript files exist. If the client cannot expose prior conversations, use the current conversation only and do not claim a pattern across sessions. Never guess a transcript path or search another workspace.

Survey recent agent conversations within that scope for recurring patterns. If the client exposes enough history to review, split the results across parallel subagents. Give each reviewer only the session excerpts it needs. Each returns a short structured list of patterns 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 `ask the user` 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 the active client's documented skill-creation feature when available. Otherwise author the skill directly using the Agent Skills format. Placement:

- Path: preserve an existing mode skill's category. For a new mode, use `.github/skills/<handle>/<handle>-mode/SKILL.md` when the repo has an established project category for that handle. Otherwise default to `.github/skills/<handle>-mode/SKILL.md` in the project (or `~/.copilot/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 the Agent Skills format. Keep `description` as one YAML scalar. Quote it or use `description: >-` with indented continuation lines when punctuation or wrapping requires it. VS Code supports additional skill frontmatter fields, but those extensions are not portable to every Copilot client; use them only when their client-specific behavior is needed and document the fallback.
- In VS Code, `disable-model-invocation: true` can require manual invocation. It is a VS Code extension, not portable Agent Skills metadata; do not imply the same control exists in Copilot CLI.

### 5. Iterate on prose

Apply the **unslop** skill and the Agent Skills format 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 formal 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): use the active client's documented skill-creation feature if available, or author directly to the Agent Skills format; no history mining is required.
- User wants to capture one narrow workflow (e.g. "how I write commit messages"). That's a regular skill, not a mode skill.