# =============================================================================
# SHOWCASE 15 — Full Orchestration (Diamond DAG)
# =============================================================================
# requires_llm: true
# category: advanced
#
# All 5 verbs, MCP, media pipeline, vision, structured output,
# for_each, guardrails, limits, diamond DAG with 12 tasks.

schema: "nika/workflow@0.12"
workflow: full-orchestration
provider: "{{PROVIDER}}"
model: "{{MODEL}}"

artifacts:
  dir: .

mcp:
  filesystem:
    command: "npx"
    args:
      - "-y"
      - "@anthropic/mcp-filesystem"

inputs:
  project_name:
    type: string
    default: "SuperNovae Tech Audit"
  target_url:
    type: string
    default: "https://github.com"

tasks:
  - id: setup
    exec:
      command: "echo '{\"started\": \"now\", \"project\": \"{{inputs.project_name}}\"}'"
      shell: true

  - id: scrape_content
    depends_on: [setup]
    fetch:
      url: "{{inputs.target_url}}"
      extract: markdown
      timeout: 20

  - id: scrape_metadata
    depends_on: [setup]
    fetch:
      url: "{{inputs.target_url}}"
      extract: metadata
      timeout: 20

  - id: scrape_links
    depends_on: [setup]
    fetch:
      url: "{{inputs.target_url}}"
      extract: links
      timeout: 20

  - id: download_image
    depends_on: [setup]
    fetch:
      url: "https://httpbin.org/image/png"
      response: binary
      timeout: 15

  - id: process_image
    depends_on: [download_image]
    with:
      img: $download_image
    invoke:
      tool: "nika:pipeline"
      params:
        hash: "{{with.img.media[0].hash}}"
        steps:
          - op: thumbnail
            width: 600
          - op: strip
          - op: convert
            format: webp
    artifact:
      path: output/orchestration/processed.webp
      format: binary

  - id: generate_chart
    depends_on: [setup]
    invoke:
      tool: "nika:chart"
      params:
        type: "bar"
        title: "{{inputs.project_name}} Metrics"
        width: 900
        height: 600
        series:
          - name: "Score"
            data: [85, 72, 91, 68, 77]
          - name: "Target"
            data: [80, 80, 80, 80, 80]
        labels: ["SEO", "A11y", "Perf", "Security", "UX"]

  - id: vision_analysis
    depends_on: [scrape_content, scrape_metadata, scrape_links, process_image, generate_chart]
    with:
      content: $scrape_content
      metadata: $scrape_metadata
      links: $scrape_links
      chart: $generate_chart
    infer:
      content:
        - type: image
          source: "{{with.chart.media[0].hash}}"
          detail: high
        - type: text
          text: |
            Tech audit for "{{inputs.project_name}}":
            Content: {{with.content | first(1500)}}
            Metadata: {{with.metadata}}
            Links: {{with.links}}
            Produce structured scores per category.
      response_format: json
      temperature: 0.3
      max_tokens: 1500
    structured:
      schema:
        type: object
        properties:
          overall_score:
            type: integer
          critical_issues:
            type: array
            items:
              type: string
          quick_wins:
            type: array
            items:
              type: string
        required: [overall_score, critical_issues, quick_wins]
    artifact:
      path: output/orchestration/analysis.json
      format: json

  - id: category_deep_dives
    depends_on: [vision_analysis]
    with:
      analysis: $vision_analysis
    for_each:
      - { area: "SEO", focus: "meta tags, structured data" }
      - { area: "Accessibility", focus: "ARIA, contrast" }
      - { area: "Performance", focus: "load times, caching" }
    as: category
    concurrency: 3
    infer:
      prompt: |
        Deep dive into {{with.category.area}} ({{with.category.focus}}):
        Context: {{with.analysis | first(1000)}}
        Provide assessment, top 3 issues, and fix list.
      temperature: 0.4
      max_tokens: 800

  - id: synthesis_agent
    depends_on: [vision_analysis, category_deep_dives, process_image]
    with:
      analysis: $vision_analysis
      deep_dives: $category_deep_dives
      image: $process_image
    agent:
      system: "You are the lead auditor. Use MCP and builtin tools."
      prompt: |
        Final report for "{{inputs.project_name}}":
        Analysis: {{with.analysis}}
        Deep dives: {{with.deep_dives}}
        Image: {{with.image}}
        Include score, issues, quick wins, 30-day roadmap.
        Call nika_complete when done.
      mcp: [filesystem]
      tools: [builtin]
      max_turns: 8
      max_tokens: 2500
      token_budget: 25000
      completion:
        mode: explicit
      guardrails:
        - type: length
          min_words: 400
          on_failure: retry
        - type: regex
          pattern: "(?i)roadmap"
          message: "Must include a roadmap"
          on_failure: retry
      limits:
        max_turns: 8
        max_tokens: 50000
        max_cost_usd: 2.00
        max_duration_secs: 300
    artifact:
      path: output/orchestration/final-report.md

  - id: completion_log
    depends_on: [synthesis_agent]
    with:
      report: $synthesis_agent
    exec: "echo '=== {{inputs.project_name}} COMPLETE === All 5 verbs. Diamond DAG. ==='"
