80 lines
2.1 KiB
YAML
80 lines
2.1 KiB
YAML
name: ai_article_research
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description: "Research the article series topic — live search + synthesis + spawn article plan task."
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debug: true
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rag_exclude: [business_plan, charter]
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system: agent_prompt
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agent_prompt:
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- "= identity.md"
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- "agent.rag.json"
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sections:
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- agent
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- project
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- history
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- rag
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- prior_results
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- message
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- instructions
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builders:
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prior_results: |
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*** WEB SEARCH RESULTS ***
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{steps[1].text}
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(If the above is empty, use your expert training knowledge.)
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steps:
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- type: think
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hint: |
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Read the project description and the message above carefully.
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Identify the best search query to find current, real-world information on this topic.
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State your reasoning, then on the last line write:
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SEARCH QUERY: [your query here]
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Query rules: 3-8 words. Specific. Current year preferred.
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- type: tool
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capability: Tool_WebSearcher
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input_from: last_text
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- type: think
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hint: |
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Using the search results above (or your training knowledge if unavailable), write a
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RESEARCH BRIEF on the topic from the project description.
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Cover as many relevant angles and subtopics as you can find real evidence for.
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For each angle: what is happening, what problem it solves, one concrete result.
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End with a SERIES RECOMMENDATION section proposing exactly 10 article topics.
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For each topic: working title, target reader, the one thing they will learn.
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- type: document
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filename: "{{task_name_slug}}"
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- type: spawn
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task_type: ai_article_plan
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task_name: "Plan Article Series: {project.name}"
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message: "{task.message}"
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- type: close
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rag_update: true
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adjudication:
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enabled: true
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pass_threshold: 65
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deliverable_type: coordination
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criteria:
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accuracy:
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weight: 35
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description: "Facts are correct and verifiable"
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thoroughness:
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weight: 30
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description: "Topic covered in sufficient depth"
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source_quality:
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weight: 20
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description: "Sources are credible and relevant"
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organization:
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weight: 15
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description: "Findings are well-structured"
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