pattern-analysis

Invoke the analyst agent to run an outcome pattern analysis on the user's application history.

Workflow

1. Confirm data exists

Read {user_dir}/CareerNavigator/tracker.json. If the applications array is empty or has fewer than 3 entries with a resolved outcome (phone_screen, interview, offer, rejected, or inactive):

"You don't have enough outcome data yet for pattern analysis — I need at least a few applications with known results. Keep logging updates via /career-navigator:track-application and run this again once you have more history."

Otherwise, proceed.

2. Invoke analyst — Operation 1

Hand off to the analyst agent with:

• The full CareerNavigator/tracker.json
• The full artifacts-index.json
• The full CareerNavigator/ExperienceLibrary.json

The agent will:

• Cross-reference artifact performance with application outcomes
• Identify patterns in variant performance, experience unit performance, role/market fit, and timelines
• Update performance_weights in CareerNavigator/ExperienceLibrary.json
• Write a weight_update_log entry for each change
• Write a search_performance summary to tracker.json

3. Confirm updates

After the agent completes, report what changed:

Pattern analysis complete.

ExperienceLibrary weights updated
  {n} unit(s) increased  — {role titles, brief rationale}
  {n} unit(s) decreased  — {role titles, brief rationale}
  {n} unit(s) unchanged  (insufficient data)

Search performance summary written to tracker.json
  Top converting role types: {list}
  Top converting industries:  {list}
  Signals to avoid:           {list}

Data confidence: {Preliminary / Directional / Moderate / High} ({n} applications with outcomes)

If weights could not be updated for any unit due to insufficient data, note it. Do not suppress this — the user should know when the dataset is too small to support a change.

4. Suggest next step

"Run /career-navigator:report for the full analyst report, or /career-navigator:tailor-resume to use the updated weights in your next resume."