AI Spark Coder Skill | Agent Skills

AI Spark Coder

Automates implementation of kipinä (sparks) from two sources:

Primary: ai_prompt.pm_sparks where ai_creatable = true
Secondary: public.feature_suggestions where status = 'in_progress' AND ai_implementation_plan IS NOT NULL

Workflow

1. Query ready-to-code sparks

Use mcp__plugin_supabase_supabase__execute_sql with project ID iryqgmjauybluwnqhxbg.

Primary source (pm_sparks):

SELECT s.*, c.name AS core_name, c.name_fi AS core_name_fi
FROM ai_prompt.pm_sparks s
LEFT JOIN ai_prompt.pm_cores c ON s.core_id = c.id
WHERE s.ai_creatable = true
ORDER BY s.updated_at DESC
LIMIT 1;

If none found, try secondary source (feature_suggestions):

SELECT * FROM public.feature_suggestions
WHERE status = 'in_progress' AND ai_implementation_plan IS NOT NULL
ORDER BY priority ASC NULLS LAST, created_at ASC
LIMIT 1;

2. If none found in either source

Report "Ei toteutettavia kipinöitä. Merkitse kipinä 'AI voi koodata' IdeaMachinassa tai aja /ehdota suunnitelma." and stop.

3. Count remaining

SELECT
  (SELECT count(*) FROM ai_prompt.pm_sparks WHERE ai_creatable = true) AS sparks,
  (SELECT count(*) FROM public.feature_suggestions WHERE status = 'in_progress' AND ai_implementation_plan IS NOT NULL) AS suggestions;

4. Build context block

For pm_sparks source:

id, title (or title_fi), content (or content_fi)
problem (or problem_fi), benefit_fi
type, status, maturity_status, usage_state
ai_prompt (AI instructions if set)
ai_complexity (estimated complexity)
clarification_notes (jsonb array of {question, answer} pairs — key context)
core_id, core_name (linked YDIN)
angle, priority, rating
created_at, updated_at

The linked core tells which product/app the spark concerns. Look up app_systems.meta.linked_core_id to find the system_id.

For feature_suggestions source:

id, system_id, title_fi (or title), description_fi (or description)
category, priority, benefit_fi (or benefit)
suggestion (original user text), source
admin_notes, ai_implementation_plan, ai_plan_generated_at
ai_context (jsonb — may contain feedback source info)
created_at

5. Announce and present plan

Tell the user:

Kipinä: [title_fi or title, truncated to ~80 chars] Ydin: [core_name or "–"] | Prioriteetti: [priority] | Jäljellä: N kpl

Tarkennukset: [List each clarification_notes Q&A pair]

AI-ohje: [ai_prompt if set, or "–"]

Suunnitelma (tutkimuksen perusteella):

[Konkreettinen askel 1]

[Konkreettinen askel 2]

...

Tiedostot joihin koskee: file1.tsx, file2.ts

Jatketaanko toteutukseen? (Voit muuttaa suunnitelmaa ennen toteutusta.)

MANDATORY — always present this plan and wait for user confirmation before proceeding. The user may:

Approve as-is → proceed to step 6
Modify the plan → adjust and re-present
Skip this spark → leave as-is and stop

To build a good plan, use the Explore agent or Grep/Glob to find relevant files. Pay attention to clarification_notes — they contain user's answers to clarifying questions.

6. Route to the right implementation skill

After user approves the plan, invoke the appropriate skill(s) directly based on what the spark requires. Do NOT delegate to using-superpowers — route directly.

Routing table

| Spark concerns | Invoke skill | Context to pass | |----------------|-------------|-----------------| | New UI component / page | frontend-design | Component spec, design requirements | | Admin panel feature | admin-panel-builder | Page, section, functionality | | Database table / RPC / migration | supabase-migration-writer | Schema, table design, RLS | | Edge Function | edge-function-generator | Function spec, auth, endpoints | | AI feature / prompt | ai-prompt-manager | Feature registration, prompt template | | Idea Machina internal | idea-machina | Evolution stage, component, data flow | | Practice / gamification | practice-gamification | Practice type, scheduling, rewards | | Bible feature | bible-lookup-helper or cinema-voice-architect | Feature type | | i18n / translation | language-specialist | Keys, languages | | Refactoring | code-refactoring | Files, what to restructure | | Subscription / quota | subscription-system | Plan, limits, feature gating |

Multiple skills may apply. For a feature that needs DB + UI + Edge Function, run: supabase-migration-writer → edge-function-generator → frontend-design in sequence.

If the spark doesn't clearly match any skill, use code-guru for general implementation guidance.

7. Update spark status

MANDATORY — always run after implementation:

For pm_sparks source:

UPDATE ai_prompt.pm_sparks
SET ai_creatable = false, usage_state = 'implemented', updated_at = NOW()
WHERE id = '<id>';

7b. Write implementation comment (pm_sparks only)

INSERT INTO ai_prompt.pm_spark_comments (spark_id, user_id, content)
VALUES (
  '<id>',
  (SELECT id FROM auth.users ORDER BY created_at ASC LIMIT 1),
  'AI-toteutettu: <1-3 lauseen yhteenveto tehdyistä muutoksista>'
);

For feature_suggestions source:

UPDATE public.feature_suggestions
SET status = 'implemented', updated_at = NOW()
WHERE id = '<id>';

8. Report

Report the final count of remaining ai_creatable sparks and in_progress suggestions.

Data Models

pm_sparks (ai_prompt schema) — PRIMARY

| Field | Type | Notes | |-------|------|-------| | id | uuid | PK | | evolution_id | uuid | FK to pm_evolutions | | user_id | uuid | FK to auth.users | | title | text | Spark title | | title_fi | text | Finnish title | | content | text | Main description | | content_fi | text | Finnish content | | problem | text | Problem statement | | problem_fi | text | Finnish problem | | type | text | idea, question, insight, etc. | | status | text | raw, analyzed, promoted, etc. | | maturity_status | text | raw, refined, etc. | | usage_state | text | inbox, linked_to_core, etc. | | priority | int | 0-based | | core_id | uuid | FK to pm_cores (linked YDIN) | | ai_creatable | boolean | TRUE = ready for AI coding | | ai_complexity | text | Estimated complexity | | ai_prompt | text | AI instructions | | clarification_notes | jsonb | Array of {question, answer} | | benefit_fi | text | Finnish benefit | | angle | text | Approach angle | | created_at | timestamptz | | | updated_at | timestamptz | |

feature_suggestions (public schema) — SECONDARY

| Field | Type | Notes | |-------|------|-------| | id | uuid | PK | | system_id | text | 'raamattu-nyt' or 'idea-machina' | | title_fi | text | Finnish title | | description_fi | text | Finnish description | | category | text | ai, search, audio, etc. | | priority | int | Lower = higher | | status | text | pending, in_progress, implemented, rejected | | ai_implementation_plan | text | Generated plan (markdown) | | ai_context | jsonb | Extra context | | created_at | timestamptz | |

Configuration

Supabase project ID: iryqgmjauybluwnqhxbg
Tool: mcp__plugin_supabase_supabase__execute_sql

Agent Skills: AI Spark Coder

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