automate-me
Skill3 starsChanged 7 days agoMITView on GitHub
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 + unslop, optionally pulling fresh evidence from recent transcripts.
47 other projects use a version of this, 40 of them edited.
Adopted by
Most recently taken up by
- tristanphvn/keeledited, first seen Nov 8, 2026
- ryanportfolio/winuse-mcpedited, first seen Nov 8, 2026
- orbyn-dev/orbyn-fullstack-skillstheir own version, first seen Nov 8, 2026
- requie/endostacktheir own version, first seen Nov 8, 2026
- creedants/pstack-t3edited, first seen Nov 3, 2026
- christofferbergj/agent-skillsedited, first seen Nov 1, 2026
Used with
Projects with it also use make-bot-ui, setup-pstack and 2 more.
Other files people use alongside this one.
Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
eryzerzSkillmake-bot-ui
Use when building a custom UI (page, dashboard, buttons) that should wake a Grok Bot over a webhook, when the user must provide a webhook sender key, or when exposing that UI on Tailscale.
Also in 20 projects that use this
bnemaSkillsetup-pstack
Configure which Pi models pstack uses per role. Detects available provider/model specs and writes pstack's user configuration. Use for /setup-pstack, "configure pstack models", or changing pstack model choices.
Also in 25 projects that use this
ianclearySkillprinciple-explain-the-number
Apply before you trust, report, or act on a number you measured: a speedup, a regression, a throughput, a latency, or an eval result. Find what limits it, and rule out that it measured something other than the work you think.
Also in 26 projects that use this
JoshueOsunaSkillPoteto Mode
poteto's agent style for concise, detailed responses, deliberate subagents, unslopped prose, simple code, and verified work. Use for poteto, /poteto-mode, or requests to work in this style.
Also in 3 projects that use this
Other versions47 projects use a version of this.
Word for word · 0
None found.
Edited · 40
- backnotprop/pstack★ 3.8k65% same
- jtaroreh/agystack★ 12869% same
- uzairansaruzi/p3-stack★ 12670% same
- dsebban/skills★ 7171% same
- creedants/pstack-t3★ 1853% same
- Scino/fstack★ 1867% same
- mariusflorescu/pstack-t3★ 1362% same
- adjohn/pstack★ 974% same
- kkgogogo17/pi-pstack★ 967% same
- alexnthnz/keel★ 574% same
30 more not listed
Wrote their own version · 7
- TheOnlyFusionCube/potetos-for-everyone★ 21same name
- 0xrsydn/pstack-pi★ 6same name
- kinqsradio/orbyn-fullstack-skills★ 4same name
- orbyn-dev/orbyn-fullstack-skills★ 4same name
- requie/endostack★ 4same name
- fullerzz/agent-skills★ 2same name
- DarthJonathan/guac-skills★ 0same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository33 other files it gives its agents.
- CLAUDE.mdCLAUDE.md
- sync-upstreamSkill
- architectSkill
- arenaSkill
- benchmark-checklistSkill
- blast-radiusSkill
- broSkill
- correctSkill
- create-formal-verification-skillSkill
- create-verification-skillSkill
- figure-it-outSkill
- howSkill
- interrogateSkill
- in-your-own-wordsSkill
- ketchupSkill
- ketchup-videoSkill
- maintain-formal-verification-skillSkill
- maintain-verification-skillSkill
- no-commentsSkill
- poteto-helpSkill
- poteto-modeSkill
- recallSkill
- reflectSkill
- sharpenSkill
- show-me-your-workSkill
- statechartSkill
- swarmSkill
- tddSkill
- teachSkill
- technical-writingSkill
- typescript-best-practicesSkill
- unslopSkill
- whySkill
The file
We split this skill into the rules it gives an agent
12 rules. 9 are common, 1 is distinctive, and 2 are very specific to this project.
9
Common
Most of the 46 edited versions we read keep these.
1
Distinctive
This author's own choices. Worth a look.
2
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- could be automatic: a setting could enforce it
- Very specific: line 17
Look for ~/.claude/skills/*-mode/SKILL.md and .claude/skills/*-mode/SKILL.md matching the user's handle.
- Common: line 19
Update the existing skill (default for repeat runs)
- Common: line 20
Start fresh (rare, ask why before doing it)
- Common: line 22
Update mode changes the rest of the flow:
- Common: line 48
Don't dump 20 questions.
- Common: line 57
Subagents: default, parallelism, model-to-task, specialized workflows.
- Very specific: line 67
Use the skill-creator skill to author the skill.
- Distinctive: line 83
Write it to its path. When that directory is under version control, commit on a branch in a worktree off main and open a PR.
- Common: line 90
Keep sections minimal: Only add a section if the user has a specific, non-default rule there.
- Common: line 91
Name conventions generic: Use "the user" or "the human" in imperatives, not the author's first name.
- Common: line 92
Don't force symmetry: If a user has no process rules worth writing down, skip the Process section entirely.
- Common: line 98
Run a description-optimization loop only if the skill's trigger accuracy turns out to be a problem in practice.
“Common” is measured: kept by at least 6 in 10 of the 46 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
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), the skill-creator skill (authoring), and the unslop skill (${CLAUDE_SKILL_DIR}/../unslop/SKILL.md, prose discipline). It sequences them. It doesn't replace them.
Flow
0. Check for an existing skill
Look for ~/.claude/skills/*-mode/SKILL.md and .claude/skills/*-mode/SKILL.md matching the user's handle. If one exists, confirm intent with AskUserQuestion (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>, or the file's mtime outside git). - 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. They are ~/.claude/projects/<slug>/*.jsonl, where <slug> is the working directory with every non-alphanumeric character replaced by -, plus the worktree slugs that extend it. Skip this session's own ${CLAUDE_SESSION_ID}.jsonl and the subagents/ directories. Never read another project's transcripts without being asked, since they hold private chats from unrelated work.
Survey recent agent conversations within that scope for recurring patterns. Run multiple parallel pstack:read-only 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 AskUserQuestion tool (structured multi-choice) rather than asking the user to type from scratch.
Shape: one or two questions with up to 4 options each (the tool's limit), multiSelect: 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 (${CLAUDE_SKILL_DIR}/../poteto-mode/SKILL.md) 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:
~/.claude/skills/<handle>-mode/SKILL.md, or the existing mode skill's path in update mode. - 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. Keepdescriptionas one YAML scalar. Quote it or usedescription: >-with indented continuation lines when punctuation or wrapping requires it. - Frontmatter
disable-model-invocation: trueby 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 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
Write it to its path. When that directory is under version control, commit on a branch in a worktree off main 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. Name pstack skills and agents with their plugin prefix (
/pstack:how,pstack:poteto-agent). Most pstack skills are user-invoked only, so route agent-side work through thepstack:poteto-modeskill, which knows their paths. - 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 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):
skill-creatoralone, 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.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

