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…
Skill by nahuelb
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Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
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About
Use cases: productivity, agent-building
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What's inside
- Skill 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 through skill-creator and unslop, optionally using supported recent task history.
- License
- MIT
- Instructions
- 107 lines in SKILL.md · view on GitHub
Files (2)
- SKILL.md
- openai.yaml · agents/
SKILL.md (first lines)
# Automate me
Delegation and optional capabilities follow `../poteto-mode/references/codex-agent-runtime.md`.
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), the `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/<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
List recent tasks through supported Codex task APIs and scope them to the active project. Never infer or search a private history directory. If task APIs are unavailable, ask the user for a history digest or skip mining and state the limitation.
Survey recent conversations within that scope for recurring patterns. For a large set, assign read-only subagents disjoint task IDs after proving their isolation. Each returns a short structured list of patterns with task identifiers as evidence. If agents are unavailable, inspect sequentially in the parent.
- 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. Lower cognitive load, higher hit rate.
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; 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 `skill-creator` skill to author the skill. Placement:
- Path: preserve an existing mode skill's category. For a new mode, use `.agents/skills/<handle>/<handle>-mode/SKILL.md` when the repo has an established personal category for that handle; otherwise default to `.agents/skills/<handle>-mode/SKILL.md` in the project (or `~/.agents/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 `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.
- 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 `skill-creator`'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 `skill-creator` 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.
## Reference files
- The **poteto-mode** skill: example of the output shape.
- The **unslop** skill: prose discipline for every line.
- the `skill-creator` skill: skill authoring process and writing guidelines.From nahuelb/pstack-codex, MIT.
More from nahuelb/pstack-codex
- 0.564score
architect
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Sketch types, signatures, and module structure before code, then stay in the loop while implementation fills in.
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Spawn N parallel candidates at the same task, pick a base, graft the strongest parts of the losers into it.
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conversation-audit
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Deeply audit a supplied Codex conversation for subagent and pstack-role token usage, model routing, timing, decisions, verification, and workflow performance.
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Use for "interrogate", "adversarial review", "multi-model review", "challenge this", "stress test this code", "find blind spots", or "tear this apart".
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Design an auditable playbook when no narrower one fits: a large migration, an ambitious multi-part change, or work a human reviews after stepping away.
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Spawn Comment Sicko, fix accepted findings, and offer encodings for claimed constraints.
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blast-radius
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Find what a change could break somewhere else before it ships, beyond the diff, and prove the one fact it's safe because of by running real code instead of…
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Signals
- Stars
- 1
- Forks
- 0
- Open issues
- 0
- Last commit (this folder)
- Aug 28, 2026 (2 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Repository
- github.com/nahuelb/pstack-codex
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
Same skill elsewhere
Copies of this SKILL.md published by others; search shows only one of them.
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SkillAFreshness: A★ 1Claude Code +9 - 0.559score
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make-bot-ui
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Use when building a local page or dashboard whose fixed buttons start approved Codex CLI tasks, with optional tailnet-only access.
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automate-me skill. Agent Mart. https://agentmart.dev/skills/nahuelb-automate-me (last updated 2026-10-24)