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Get Started Free →cursor/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.
Passed 15 of 19 test cases with the skill, and 3 of 19 without it.
and 18 more in the full report
15 fixed2 passed either way3 still failing2 broke
Tokens, turns and time describe resource use, not a dollar price.
This benchmark measured an earlier version of the skill.
One of 15 test cases the skill fixed. Same model, same prompt, with and without the skill.
I am authoring a new mode skill for user handle 'alex' in a repository where an established category directory '.cursor/skills/alex/' already exists. What exact file path should be chosen for the skill file?
| Checked | Without skill | With skill |
|---|---|---|
| Paths the file to .cursor/skills/alex/alex-mode/SKILL.md. | Missed | Passed |
The instructions your model reads when the skill loads.
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), Cursor's built-in create-skill (authoring), and the unslop skill (prose discipline). It sequences them. It doesn't replace them.
Look recursively for .cursor/skills/**/*-mode/SKILL.md and ~/.cursor/skills/*-mode/SKILL.md matching the user's handle. Mode skills can live in a personal category directory (.cursor/skills/<handle>/), not only at the top level. If one exists, confirm intent with AskQuestion (unless they already said "update my skill" or similar):
Update mode changes the rest of the flow:
git log -1 --format=%cI <path>).Locate the active workspace's transcripts before fanning out. The system prompt names the workspace's agent-transcripts/ directory. Use only that path. Don't glob across ~/.cursor/projects/*/. That crosses workspace boundaries and reads private chats from unrelated projects.
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). Pick each subagent's reasoning level and fast or standard speed for the job, per the Subagents section of the poteto-mode skill. 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:
Cross-check across slices before elevating a signal. Patterns seen in 2+ slices are high-confidence. Lone signals are weak and usually get dropped.
Mining misses intent that hasn't come up yet. Use the AskQuestion 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.
test cases passed, vs 3 / 19 without
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