name: ai_article_research
description: "Research the article series topic — live search + synthesis + spawn article plan task."
debug: true
system: agent_prompt

agent_prompt:
  - "= identity.md"
  - "agent.rag.json"

sections:
  - agent
  - project
  - history
  - rag
  - prior_results
  - message
  - instructions

builders:
  prior_results: |
    *** WEB SEARCH RESULTS ***
    {steps[1].text}

    (If the above is empty, use your expert training knowledge.)

steps:
  - type: think
    hint: |
      Read the project description and the message above carefully.
      Identify the best search query to find current, real-world information on this topic.

      State your reasoning, then on the last line write:
      SEARCH QUERY: [your query here]

      Query rules: 3-8 words. Specific. Current year preferred.

  - type: tool
    capability: Tool_WebSearcher
    input_from: last_text

  - type: think
    hint: |
      Using the search results above (or your training knowledge if unavailable), write a
      RESEARCH BRIEF on the topic from the project description.

      Cover as many relevant angles and subtopics as you can find real evidence for.
      For each angle: what is happening, what problem it solves, one concrete result.

      End with a SERIES RECOMMENDATION section proposing exactly 10 article topics.
      For each topic: working title, target reader, the one thing they will learn.

  - type: document
    filename: "{{task_name_slug}}"

  - type: package
    packet_type: IntakeResponse
    hint: |
      Create exactly ONE follow-up task.

      - task_name: "Plan Article Series"
      - task_type: "ai_article_plan"
      - description: "Using the research deliverable, plan exactly 10 standalone articles for
          this series. Each article is a 5-minute read (~800-1000 words) for the target audience
          described in the project. You choose the topics based on the research. Then spawn 10
          ai_article_write tasks."
      - depends_on: ""
    schema:
      actions:
        - type: create_task
          task_name: "string"
          agent_name: "string"
          task_type: "string"
          description: "string"
          depends_on: "string"

  - type: close
    rag_update: true
adjudication:
  enabled: true
  pass_threshold: 65
  deliverable_type: coordination
  criteria:
    accuracy:
      weight: 35
      description: "Facts are correct and verifiable"
    thoroughness:
      weight: 30
      description: "Topic covered in sufficient depth"
    source_quality:
      weight: 20
      description: "Sources are credible and relevant"
    organization:
      weight: 15
      description: "Findings are well-structured"