# 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. - Skill: `shishiv/automate-me` (Agent Skill) - Install (CLI): `npx skillmds@latest add shishiv/automate-me` - Raw SKILL.md: https://api.skillmd.com/api/skills/shishiv/automate-me/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Coding & Dev Tools - Author: shishiv (https://skillmd.com/u/shishiv) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/shishiv/automate-me --- # 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 parts: an inline mining pass (see step 1), the host's skill-authoring workflow, and the **unslop** skill. It sequences them; it doesn't replace them. ## Flow ### 0. Check for an existing skill Look recursively for `.pi/skills/**/*-mode/SKILL.md` and `~/.pi/agent/skills/*-mode/SKILL.md` matching the user's handle. Mode skills can live in a personal category directory (`.pi/skills//`), not only at the top level. If one exists, confirm intent in the Pi conversation unless the user 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 `). - 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 `$PI_SESSION_FILE`. Use only that path. Don't glob across `$PI_SESSION_FILE`. That crosses workspace boundaries and reads private chats from unrelated projects. Survey recent agent conversations within that scope for recurring patterns. Follow [`../../docs/delegation.md`](../../docs/delegation.md) and launch parallel delegates across slices of history when the corpus is large enough. Each delegate reads only the workspace-scoped paths the parent provides and 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 has not come up yet. Ask in the normal Pi conversation. Offer concise choices when they reduce typing, then leave room for a free-form answer. 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. Two structured rounds plus one open question is usually enough. ### 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; use of external-source tools. - **Understand first**: which skills to reach for when scoping or investigating a change. - **Delegation**: 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 host's skill-authoring workflow to author the skill. Placement: - Path: preserve an existing mode skill's category. For a new mode, use `.pi/skills//-mode/SKILL.md` when the repo has an established personal category for that handle; otherwise default to `.pi/skills/-mode/SKILL.md` in the project (or `~/.pi/agent/skills/-mode/` if the user prefers a personal skill). - Handle: the user's first name or chosen identifier. - Frontmatter `description`: trigger on their name + `/-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. Mode skills are heavy and opinionated; they should only apply when the user explicitly invokes them (by name or slash command), not auto-trigger on description matching. 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. Both apply to any agent-read prose, not just skills. 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 so the user can review it. 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. Others may read or adopt the skill. - **Don't force symmetry.** If a user has no process rules worth writing down, skip the Process section entirely. Sparse is fine; bloated is not. ## 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. ## Reference files - The **poteto-mode** skill: example of the output shape. - The **unslop** skill: prose discipline for every line. - The host's skill-authoring workflow: skill authoring process and writing guidelines.