Website · Install the skill · Try the example · Read the whitepaper · Installation guide
Discover what you could automate.
Requests you copy into a tracker. Questions you answer every week. Reports you assemble by hand. Automation Mining helps your agent find this work in activity it can read and show you what an automation could do.
Give it one work source. It finds repeated manual tasks and returns up to five proposals. Each proposal includes source records, a count of work instances, and a clear description of the change. You check the evidence and choose what to build.
An n8n labs experiment for Claude Code, Codex, Cursor, Pi, and other agents that support Agent Skills. Open source under the Apache License 2.0.
Install with Skills CLI:
npx skills@latest add n8n-io/automation-mining-skill --skill automation-miningChoose your agent and installation scope. The installer needs Node.js and Git. Start a new agent session, then ask:
Use automation-mining to find repeated manual work in my agent sessions from the last two weeks.
This needs no external connection if your agent can read those session files. With a Slack connection, try:
Use automation-mining on #ops-requests for the last 30 days. I handle operations for the team.
No activity to connect yet? Use the small synthetic example. It includes the input records and a report for comparison.
Claude Code, Codex, and Pi packages
Choose one installation route per agent.
Claude Code — run these commands inside Claude Code:
/plugin marketplace add n8n-io/automation-mining-skill
/plugin install automation-mining@n8n-automation-mining
Start a new session, then use /automation-mining:automation-mining.
Codex — run these commands in your terminal:
codex plugin marketplace add n8n-io/automation-mining-skill
codex plugin add automation-mining@n8n-automation-miningStart a new session, then select Automation mining in the skill picker. Use Skills CLI if your client does not support plugins.
Pi — run this command in your terminal:
pi install git:github.com/n8n-io/automation-mining-skillStart a new session, then use /skill:automation-mining.
For ZIP downloads, updates, and removal, see the installation guide.
| The work you keep doing | The change to investigate |
|---|---|
| Copy a request from chat into a tracker | Create the record and route it for approval |
| Answer the same question with the same links | Put the answer and its source with the request |
| Check a lead in several tools, then update the CRM | Collect the fields and update the record |
| Assemble a weekly report from several sources | Prepare a report for a person to review |
| Notice a failed job and tell its owner | Detect the failure and notify the owner |
| Ask your agent for the same meeting brief | Prepare it from the calendar and source records |
These are examples, not promises. The skill checks your records before it proposes a change. It also identifies work already automated and gaps that need a decision, an owner, or a document first.
- Choose a starting point. The agent states what it can read and asks about your work. Start with one source and a clear time window.
- Steer the findings. Review short cards. Keep, drop, or deepen a candidate. Approve a new source when the evidence points there.
- Check the proposal. See the work, its count, the proposed change, and what still needs a person. Source links let you check the claims.
- Give your verdict. Build it. Real, but not worth it. You misread this.
Run time and model cost depend on the agent, tools, and number of records. A report can be empty when the records do not support a useful proposal.
The released skill includes the procedure tested in Improving Automation Discovery with a Workflow Taxonomy, by Albert Alises, n8n. The repository includes the reviewed whitepaper and its LaTeX source.
The study used a taxonomy of 907,353 workflow rows to define tasks and make synthetic activity. Feedback changed the skill instructions; it did not change model weights. A separate test used 57 synthetic companies and two AI models to read their activity.
| Measure | Starting procedure | Included procedure | Change, with 95% interval |
|---|---|---|---|
| Useful proposal quality | 44.7% | 53.0% | +8.3 points [0.3, 16.8] |
| Verified task recall | 28.2% | 51.7% | +23.5 points [13.0, 34.4] |
These results compare the released procedure with its starting version on synthetic records. They do not measure the full interactive flow or time saved by real teams. A later procedure did not pass the release rule, so the package keeps the confirmed version. A separate comparison with a short prompt did not show a clear gain in proposal quality.
Whitepaper PDF · Method and limits · Study records · Citation
The skill tells the agent to read source activity without posting, editing, or reacting. Reports use pointers and counts, not copied message bodies, personal data, or credentials. Use your own work or a channel you belong to, and tell the channel.
The package contains instructions. It does not add data connections or a background service. Your agent, tools, and model provider process data under your account settings. Tool permissions must enforce access limits.
Building an automation is a separate task after review. Changes to a source require your approval for that source.
An accepted proposal states the trigger, operation, output, and checks that remain. Use it as the starting specification for an n8n workflow.
Help improve the skill: report a problem or share feedback. Use synthetic examples and remove private data before sharing.
Install and update · Contribute · Release notes · Security · Apache License 2.0