Operon — Mine Sessions

operon-setup is the one-time onboarding skill. operon-mine is the recurring loop: every few weeks (or when the user mentions a new recurring task), run a mining pass to surface fresh patterns.

When to use this skill

• The user says "mine my sessions" or "find new patterns" or "what

has recurred since I last mined."

• It's been more than a couple weeks since their last operon mine.
• The user mentions a new repeated workflow they want to capture.

Do not use this for first-run onboarding — use operon-setup instead.

How to use it

1. Confirm the user is set up

operon doctor --json

If auth.tokenPresent is false, point them at operon-setup. Do not try to mine without auth — mine won't upload drafts to the platform without a valid token.

2. Pick a window

Default mining window is 30 days. If the user mined recently and just wants the new stuff, that's right. If they want a broader sweep (after a sabbatical, after onboarding a new tool, etc.), widen it:

operon mine --since 90d
operon mine --since 180d
operon mine --since 365d

Wider windows take longer but surface stable patterns that didn't quite clear the threshold in a 30-day window.

3. Run the mine

For interactive review:

operon mine --since 30d

For agent-driven flow (recommended when an assistant is driving):

operon mine --since 30d --yes --json

--yes accepts every default; --json outputs the candidate list as a single JSON object on stdout.

4. Parse the output

The JSON shape is:

{
  "input": 412,
  "kept": 287,
  "clusters": 14,
  "dryRun": false,
  "candidates": [
    {
      "slug": "review-pr",
      "uses": 12,
      "spanDays": 14,
      "score": 0.91,
      "suggestedTools": ["Read", "Bash", "WebFetch"],
      "existing": "new"
    }
  ]
}

existing tells you how each candidate compares to what's already published in the workspace:

• new — never published
• same — already published, no diff
• changed — already published, but the draft differs
• unchecked — couldn't compare (offline / no workspace)

5. Direct the user to review

After mining, drafts auto-upload to https://app.withoperon.com/<workspace>/candidates. From there the user can edit, polish, and publish each draft.

Or pipe straight into operon-publish — call that skill next if the user wants to ship one of the new drafts immediately.

Privacy notes

• Mining reads session files in ~/.claude/, ~/.codex/, ~/.cursor/.

Nothing leaves the laptop without explicit consent.

• After redaction, the candidate metadata (slug, score, uses, prompt

fingerprint, draft prompt) uploads to the platform's private Drafts slot — visible only to the user who mined them.

• Exemplar session bodies stay on the laptop. The platform only

sees opaque session IDs.

• Opt-out: operon config set candidates.cloudReview false keeps the

full mining flow local; no drafts upload.

Error handling

• `NO_SOURCES` → user doesn't have Claude Code / Codex / Cursor

installed. Tell them to install at least one and retry.

• `NO_CANDIDATES` → no patterns crossed the clustering threshold.

Suggest a wider --since window.

• `RATE_LIMITED` → wait and retry. The mining itself is local —

rate limiting hits the draft-upload step. The local on-disk drafts under ~/.operon/candidates/ are still authoritative.