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Config Seeder Skill

config-seeder

Seed JSON configuration files into database. Use ONCE at BAZINGA session initialization, BEFORE spawning PM.

SKILL.md

Full skill instructions

Config Seeder Skill

You are the config-seeder skill. Your role is to seed JSON configuration files into database tables at session start.

Overview

This skill seeds workflow configuration from JSON files into database tables:

  • workflow/​transitions.json → workflow_transitions table
  • workflow/​agent-markers.json → agent_markers table
  • _special_rules from transitions.json → workflow_special_rules table

Note: In dev mode, bazinga/​config is a symlink to ../​workflow for path compatibility.

Prerequisites

  • Database must be initialized (bazinga/​bazinga.db exists)
  • Config files must exist:
    • workflow/​transitions.json (source) or bazinga/​config/​transitions.json (symlink)
    • workflow/​agent-markers.json (source) or bazinga/​config/​agent-markers.json (symlink)

When to Invoke This Skill

  • ONCE at session start, BEFORE spawning PM
  • Part of session initialization (after create-session, before PM spawn)
  • Should NOT be invoked during normal orchestration flow

Your Task

When invoked, you must:

Step 1: Call the Session Init Script (RECOMMENDED)

Use the unified initialization script that handles DB + config in one step:

python3 .claude/​skills/​bazinga-db/​scripts/​init_session.py --session-id "{session_id}"

This script:

  1. Ensures database exists with correct schema
  2. Seeds workflow configs (transitions, markers, rules)
  3. Creates artifacts directory
  4. Verifies everything is ready

Alternative: Call seed script directly (requires DB to exist first):

python3 .claude/​skills/​config-seeder/​scripts/​seed_configs.py --all

With auto-init: Initialize DB if missing:

python3 .claude/​skills/​config-seeder/​scripts/​seed_configs.py --all --auto-init-db

Step 2: Verify Success

Expected output on success:

Seeded 45 transitions
Seeded 7 agent marker sets
Seeded 5 special rules
✅ Config seeding complete

Step 3: Report Result

If successful:

  • Report: "Configuration seeded successfully"
  • Orchestration can proceed

If failed:

  • Report the error message
  • Orchestration CANNOT proceed without routing config

What Gets Seeded

Transitions (45+ entries)

State machine rules for routing:

  • developer + READY_FOR_QA → qa_expert
  • developer + READY_FOR_REVIEW → tech_lead
  • qa_expert + PASS → tech_lead
  • tech_lead + APPROVED → merge → check phase
  • etc.

Agent Markers (7 entries)

Required markers per agent type:

  • developer: "NO DELEGATION", "READY_FOR_QA", "BLOCKED", etc.
  • qa_expert: "PASS", "FAIL", "Challenge Level", etc.
  • tech_lead: "APPROVED", "CHANGES_REQUESTED", etc.
  • etc.

Special Rules (5 entries)

Workflow modification rules:

  • testing_mode_disabled: Skip QA entirely
  • testing_mode_minimal: Skip QA Expert
  • escalation_after_failures: Escalate to SSE after 2 failures
  • security_sensitive: Force SSE + mandatory TL review
  • research_tasks: Route to RE with limited parallelism

Output Format

Return success/​failure message. No structured output needed.

Error Handling

ErrorMeaning
Config file not foundJSON files missing - check workflow/ (or bazinga/​config/ symlink)
Database not foundRun init_db.py first
Insert failedDatabase schema mismatch - run migration

If seeding fails, orchestration CANNOT proceed. The prompt-builder and workflow-router skills depend on these database tables.

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