Flywheel Scan

Invocation

Skill(skill: "flywheel-scan")                          # Full scan (default)
Skill(skill: "flywheel-scan", args: "--mode quick")    # Active-invest repos only
Skill(skill: "flywheel-scan", args: "--domain biz")    # Single domain
Skill(skill: "flywheel-scan", args: "--mode diff")     # Only repos with git activity since last scan
Skill(skill: "flywheel-scan", args: "--dry-run")       # Scouts only, no doppelganger scoring

Steps

1. Parse Arguments

Extract from args:

• --mode: full (default) | quick | diff | dry-run
• --domain: biz | training | tooling | personal (default: all)
• --date: override scan date (default: today)

2. Load Config & References

Read config/scan-config.yaml           → repo assignments, scoring config, external paths
Read references/event-schema.md        → event type definitions
Read references/scoring-rubric.md      → 4 scoring dimensions
Read references/drift-mappings.json    → canonical field rename table (SINGLE SOURCE OF TRUTH)
Read references/scout-protocol.md      → 7-step repo scan checklist
Read references/doppelganger-protocol.md → strategic review protocol

3. Resolve Mode Filters

For --domain, filter to only that scout's repo list.

4. Create Output Directory

mkdir -p {output_base}/flywheel-scan-{date}

Where {output_base} comes from config/scan-config.yaml.

5. Load Goals Graph

python {goals_query_path} status
python {goals_query_path} threads
python {goals_query_path} tensions

Save combined output as goals-context.md in the output directory. This feeds the doppelganger.

6. Create Team

TeamCreate(team_name: "flywheel-scan-{date}")

7. Create Tasks

One task per active scout domain + doppelganger review + report generation. Set dependencies:

• Doppelganger task is blockedBy all scout tasks
• Report generation is blockedBy doppelganger task (or all scouts if --dry-run)

8. Spawn Scout Agents

For each active domain, spawn a scout agent using Task tool:

Task(
  subagent_type: "general-purpose",
  team_name: "flywheel-scan-{date}",
  name: "scout-{domain}",
  prompt: <scout.md template filled with domain + repo list + event schema + scout protocol>
)

Spawn all scouts in parallel (one Task call per scout, all in same message).

Each scout writes: scout-{domain}-results.json in the output directory.

9. Collect Scout Results

After all scouts complete, read their result files. Verify each produced valid JSON with the expected event types.

10. Spawn Doppelganger (skip if --dry-run)

Task(
  subagent_type: "general-purpose",
  team_name: "flywheel-scan-{date}",
  name: "lee-doppelganger",
  prompt: <doppelganger.md template filled with all scout results + goals context + scoring rubric + persona schema>
)

Doppelganger writes: doppelganger-results.json in the output directory.

11. Assemble simulation-events.json

Merge all agent result files into canonical format:

{
  "session": { "id": "flywheel-scan", "title": "Cross-Project Roadmap Discovery", "date": "{date}" },
  "agents": [ ... ],
  "events": [ ... all events merged in time_offset order ... ]
}

Write to simulation-events.json in the output directory.

12. Run Validator

Spawn the scan-validator agent to fix schema drift:

Task(
  subagent_type: "general-purpose",
  name: "scan-validator",
  prompt: <scan-validator.md + path to simulation-events.json + drift-mappings.json>
)

Review fix count. >20 fixes = scout prompts need hardening.

13. Generate Reports (skip if --dry-run)

Using the report templates, generate:

• flywheel-scan-report.md — executive summary
• master-work-queue.md — ranked work items by tier
• thread-proposals.md — open decision threads with options

14. Generate Replay

python {skill_dir}/replay/generate_replay.py {output_dir}

Produces flywheel-replay.html — self-contained, opens in browser.

15. Diff Against Previous Scan

If a previous scan exists (auto-detected or from config):

python {skill_dir}/scripts/diff_scans.py {previous_dir} {current_dir}

Produces scan-diff-report.md in the output directory.

16. Shutdown Team

Send shutdown messages to all agents. Then TeamDelete().

17. Report to User

Present:

• Verdict: repos scanned, events generated, items scored
• Top 5 work items with scores
• Thread decisions needed (count + titles)
• Classification changes from previous scan (if diff ran)
• File locations: output directory, replay HTML, reports

Cost Notes

Full scan with 5+ agents is expensive. Preferred approach:

1. First run: --dry-run --domain biz to verify scout communication
2. Weekly cadence: --mode diff to catch only changed repos
3. Monthly cadence: --mode full for complete baseline

FMEA