# 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 skill-creator and unslop, optionally using recent transcripts. - Skill: `scriptedalchemy/automate-me` (Agent Skill, multi-file: 2 files) - Install (CLI): `npx skillmds@latest add scriptedalchemy/automate-me` - Raw SKILL.md: https://api.skillmd.com/api/skills/scriptedalchemy/automate-me/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Coding & Dev Tools - Author: ScriptedAlchemy (https://skillmd.com/u/scriptedalchemy) - Updated: 2026-09-22 - Page: https://skillmd.com/skills/scriptedalchemy/automate-me --- Before following this workflow, read [the Codex runtime contract](../../CODEX.md). It defines plugin paths, model configuration, delegation, and persistence. # 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), Codex's `skill-creator` 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 `.agents/skills/**/*-mode/SKILL.md` and `~/.agents/skills/*-mode/SKILL.md` matching the user's handle. Mode skills can live in a personal category directory (`.agents/skills//`), not only at the top level. If one exists, confirm intent with the available user-input tool or one concise chat question (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 `). - 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 candidate transcripts under `~/.codex/sessions/YYYY/MM/DD/*.jsonl`. Read each candidate's first `session_meta` record and keep only files whose `payload.cwd` equals the active workspace. Do not read unrelated workspaces. 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 the available user-input tool or one concise chat question 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 Codex's `skill-creator` skill to author the skill. Placement: - Path: preserve an existing mode skill's category. For a new mode, use `.agents/skills//-mode/SKILL.md` when the repo has an established personal category for that handle. Otherwise default to `.agents/skills/-mode/SKILL.md` in the project (or `~/.agents/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 `skill-creator`'s YAML rules. Keep `description` as one YAML scalar. Quote it or use `description: >-` with indented continuation lines when punctuation or wrapping requires it. - Preserve an existing skill's invocation policy. For a new skill, use automatic discovery by default; set `policy.allow_implicit_invocation: false` in `agents/openai.yaml` only if the user requests explicit-only invocation. A task-long standing instruction still applies only to the task in which the user gave it. ### 5. Iterate on prose Apply the **unslop** skill and `skill-creator`'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 `skill-creator`-style test/iterate benchmark loop is not 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): `skill-creator` 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.