Interactive command center for the freshie ecosystem inventory database.
Current DB Status
!sqlite3 freshie/inventory.sqlite "SELECT 'Run #' || id || ' — ' || run_date || ' | Plugins: ' || total_plugins || ' | Skills: ' || total_skills || ' | Packs: ' || COALESCE(total_packs, 0) FROM discovery_runs ORDER BY id DESC LIMIT 3;" 2>/dev/null || echo "DB not found at freshie/inventory.sqlite"
!sqlite3 freshie/inventory.sqlite "SELECT grade || ': ' || COUNT(*) FROM skill_compliance GROUP BY grade ORDER BY grade;" 2>/dev/null
Overview
The freshie database is the single source of truth for ecosystem-wide metrics — plugin counts,
skill compliance grades, pack coverage, anomaly detection, and historical trends across versioned
discovery runs. This skill is an interactive wizard — it always asks what you want to do,
then delegates heavy operations to specialized subagents.
Database location:freshie/inventory.sqlite (51 tables, versioned by run_id)
Key scripts:
freshie/scripts/rebuild-inventory.py — full repo scan, creates new discovery run
scripts/validate-skills-schema.py — enterprise validation with DB population
freshie/scripts/run-delta.py [--run-id N] [--alert-on-regression] — (re)generate a run's
delta report (schema-vs-data changes + grade regressions; exit 4 signal on regressions)
freshie/scripts/dolt-sync.py [--alert-on-regression] — Dolt sync; emits the delta report
post-commit and can exit 4 when grades regressed
Prerequisites
sqlite3 CLI available on PATH
python3 with pyyaml installed
Working directory is the repo root (claude-code-plugins/)
Database exists at freshie/inventory.sqlite
/email skill installed (for PDF report emailing)
Instructions
Step 1: Present Main Menu
When invoked, ALWAYS start by presenting this menu using AskUserQuestion:
FRESHIE INVENTORY COMMAND CENTER
================================================================
What would you like to do?
1. Dashboard — Current status, grades, staleness
2. Discovery Scan — Full repo scan, create new run
3. Compliance Check — Enterprise validation + DB population
4. Remediation — Batch fix compliance issues
5. Query — Ad-hoc SQLite queries
6. Compare Runs — Delta analysis between runs
7. Export Data — CSV exports to freshie/exports/
8. Anomaly Scan — Data quality + outlier detection
9. Pack Coverage — SaaS pack completeness metrics
10. Full Audit — Scan + validate + report (end-to-end)
11. Report Only — Generate summary from existing data
Use AskUserQuestion with these options. If the user's initial prompt already contains
a clear intent (e.g., "freshie status"), skip the menu and route directly.
Step 2: Execute Chosen Workflow
Based on selection, follow the matching workflow below. Every workflow ends with
Step 3 (Email Report).
Workflow A: Dashboard
Run these queries and present as a formatted dashboard:
sqlite3 freshie/inventory.sqlite "SELECT id, run_date, total_plugins, total_skills, COALESCE(total_packs,0) FROM discovery_runs ORDER BY id DESC LIMIT 1;"
sqlite3 freshie/inventory.sqlite "SELECT grade, COUNT(*) FROM skill_compliance WHERE run_id=(SELECT MAX(id) FROM discovery_runs) GROUP BY grade ORDER BY grade;"
sqlite3 freshie/inventory.sqlite "SELECT CAST(julianday('now') - julianday(run_date) AS INTEGER) FROM discovery_runs ORDER BY id DESC LIMIT 1;"
sqlite3 freshie/inventory.sqlite "SELECT 'plugins', COUNT(*) FROM plugins WHERE run_id=(SELECT MAX(id) FROM discovery_runs) UNION ALL SELECT 'skills', COUNT(*) FROM skills WHERE run_id=(SELECT MAX(id) FROM discovery_runs) UNION ALL SELECT 'packs', COUNT(*) FROM packs WHERE run_id=(SELECT MAX(id) FROM discovery_runs) UNION ALL SELECT 'anomalies', COUNT(*) FROM anomalies WHERE run_id=(SELECT MAX(id) FROM discovery_runs);"# Core vs SaaS pack breakdown
sqlite3 freshie/inventory.sqlite "SELECT CASE WHEN path LIKE '%saas-packs%' THEN 'saas-pack-skills' ELSE 'core-skills' END as type, COUNT(*) FROM skills WHERE run_id=(SELECT MAX(id) FROM discovery_runs) GROUP BY type;"
If Critical (>7 days), recommend a discovery scan.
Workflow B: Discovery Scan
Delegate to the discovery-scanner subagent via the Agent tool:
Launch Agent: discovery-scanner
Prompt: "Run a full freshie discovery scan. Show current state first, execute
rebuild-inventory.py, then report the delta (plugin/skill count changes)
compared to the previous run."
The subagent handles the long-running scan in isolation and returns the delta report.
Workflow C: Compliance Check
Delegate to the compliance-validator subagent via the Agent tool:
Launch Agent: compliance-validator
Prompt: "Run enterprise compliance validation against the freshie DB.
Execute: python3 scripts/validate-skills-schema.py --enterprise --populate-db freshie/inventory.sqlite --verbose
Then summarize: grade distribution with percentages, and list all D/F grade skills."
The subagent runs the full validation pipeline and returns a structured summary.
Workflow D: Remediation
CRITICAL: Always dry-run first, then confirm before executing.
Skills that changed grade (upgrades/downgrades with score delta)
New skills added since previous run
Skills removed since previous run
Workflow G: Export Data
mkdir -p freshie/exports
Use AskUserQuestion to let user pick what to export:
EXPORT OPTIONS
================================================================
What should I export?
- Skill Grades — All skill compliance scores + grades
- Plugin Inventory — All plugins with category and version
- Pack Coverage — Pack names, skill counts, categories
- Full Dump — All three exports
- Custom Query — Export any query result to CSV
Delegate to the anomaly-detector subagent via the Agent tool:
Launch Agent: anomaly-detector
Prompt: "Run anomaly detection on the freshie inventory DB. Check:
1. Stored anomalies from the latest discovery run
2. Skills with word count < 50 (likely stubs)
3. Plugins with no skills
4. Skills with high template-text density (>10%)
5. Duplicate files
Report all findings grouped by severity."
Workflow I: Pack Coverage
sqlite3 freshie/inventory.sqlite "SELECT name, skill_count, category FROM packs WHERE run_id=(SELECT MAX(id) FROM discovery_runs) ORDER BY skill_count DESC;"
Also flag packs below minimum viable (< 3 skills) and show grade distribution within packs.
Use pack coverage queries from common-queries.md.
Workflow J: Full Audit
This is the power workflow — runs everything end-to-end:
Discovery Scan (Workflow B) — via subagent
Compliance Check (Workflow C) — via subagent
Anomaly Scan (Workflow H) — via subagent
Report Generation (Workflow K) — compile all results
Launch steps 1-3 as parallel subagents, then compile the report when all complete.
Workflow K: Report Only
Generate a summary report from existing data (no new scans). Gather dashboard data
(Workflow A queries) and compile:
After ANY workflow completes, use AskUserQuestion to offer the report:
WORKFLOW COMPLETE
================================================================
{Brief summary of what was done}
Would you like a PDF report emailed?
- Yes, email me — Generate PDF + send to jeremy@intentsolutions.io
- Yes, email someone — Specify recipient
- Save PDF only — Generate PDF, no email
- No thanks — Done
If the user wants a report:
Generate markdown report — write the workflow results to /tmp/freshie-report-{date}.md
Convert to PDF using the email skill's converter:
python3 ~/.claude/skills/email/scripts/md-to-pdf.py /tmp/freshie-report-{date}.md /tmp/freshie-report-{date}.pdf --style professional
Send via /email skill — invoke the Skill tool with skill: "email" and args describing:
All operations produce structured text output. Dashboards use fixed-width formatting.
Query results use table format. Deltas show +/- indicators. CSV exports write to
freshie/exports/. PDF reports write to /tmp/ and optionally email.
Error Handling
Error
Cause
Solution
"DB not found"
Missing freshie/inventory.sqlite
Run python3 freshie/scripts/rebuild-inventory.py to create
"no such table"
DB schema outdated or empty
Run a fresh discovery scan (Workflow B)
Empty grades
Compliance not yet populated
Run compliance validation (Workflow C)
rebuild-inventory.py fails
Missing pyyaml
pip install pyyaml
Stale data (>7 days)
No recent scans
Run discovery scan, then compliance
PDF generation fails
Missing weasyprint
pip install weasyprint
Email send fails
Missing env vars
Check ~/.env for GMAIL_APP_PASSWORD
Examples
See examples.md for detailed input/output examples covering all workflows:
Quick status check (direct intent, skips menu)
Full audit with email PDF report (parallel subagents)
Ad-hoc query with CSV export follow-up
Remediation cycle (dry-run, confirm, re-validate)
Compare discovery runs (delta analysis)
Pack coverage analysis
Resources
Common Queries — pre-built SQLite query library: grades, stubs, plugins, packs, content quality, trends, anomalies, field analysis, cross-references
freshie/scripts/rebuild-inventory.py — full repo scanner, versioned discovery runs
