diff --git a/templates/campaign_review.yml b/templates/campaign_review.yml index c8daba1..97158a5 100644 --- a/templates/campaign_review.yml +++ b/templates/campaign_review.yml @@ -1,112 +1,114 @@ -name: campaign_review -description: "CLM performance review -- Leo checks real-world campaign response and dispatches learnings to CL if the book is flopping." -debug: true -model: power -system: agent_prompt - -agent_prompt: - - "= identity.md" - -sections: - - agent - - project - - deliverables - - rag - - message - - instructions - -steps: - - type: tool - capability: Tool_WebSearcher - query: "'{project.name}' romance novel reviews sales Amazon Goodreads TikTok BookTok" - - - type: tool - capability: Tool_WebSearcher - query: "'{project.name}' romance book social media engagement Instagram Facebook author" - - - type: think - max_tokens: 4000 - output_key: performance_analysis - hint: | - You are Leo, Marketing Director at Crimson Leaf Marketing. - - Review the web search results above for the "{project.name}" campaign. - Also review the campaign deliverables in the DELIVERABLES section. - - Analyze campaign performance: - 1. REACH: Are people finding the book? Any search results, reviews, mentions? - 2. ENGAGEMENT: Any social media traction (TikTok, Instagram, Facebook)? - 3. REVIEWS: Any reader reviews on Amazon, Goodreads, or BookTok? - 4. SALES SIGNALS: Any sales rank data, bestseller mentions, or download counts? - 5. SENTIMENT: Is the reception positive, mixed, or negative? - - If the book is too new (less than 2 weeks since campaign launch), note that and - recommend checking again in 1 week. - - Rate overall performance: - - GREEN: Exceeding expectations -- organic traction, positive reviews, good engagement - - YELLOW: Mixed results -- some traction but underperforming potential - - RED: Minimal traction -- the book is not getting discovered - - End with exactly: - PERFORMANCE_RATING: GREEN|YELLOW|RED - WEEKS_SINCE_LAUNCH: - - - type: think - max_tokens: 100 - output_key: performance_rating - hint: | - Read the PERFORMANCE_RATING line from the analysis above. - Output ONLY the value: GREEN, YELLOW, or RED. Nothing else. - - - type: think - max_tokens: 600 - output_key: learnings_message - hint: | - Read the performance analysis above. - - If performance_rating is GREEN: output exactly: none - - If performance_rating is YELLOW or RED, write a MARKET LEARNINGS report for - Crimson Leaf Holdings strategic team. This report will inform the next book. - - Include: - - What did NOT work in this campaign (specific observations) - - What the market data suggests about genre/audience fit - - What competitors or similar books are doing that we are not - - Concrete recommendations for the next book (genre, themes, marketing channels, - pricing strategy, platform focus) - - Should we continue this book's campaign or pivot resources to the next book? - - Format as a professional post-mortem. Be specific and data-driven. - Output ONLY the report text. No preamble. - - - type: tool - action: enqueue_strategy - optional: true - params: - company_slug: "crimson_leaf" - project_slug: "incubation" - task_type: "market_intelligence" - content: "{learnings_message}" - - - type: document - filename: "campaign_performance_review" - - - type: close - rag_update: true - -adjudication: - enabled: true - pass_threshold: 60 - deliverable_type: analysis - criteria: - completeness: - weight: 40 - description: "All performance dimensions assessed (reach, engagement, reviews, sentiment)" - actionability: - weight: 35 - description: "Learnings are specific and actionable for future books" - accuracy: - weight: 25 - description: "Assessment is grounded in the search evidence, not speculation" +name: campaign_review +description: "CLM performance review -- Leo checks real-world campaign response and dispatches learnings to CL if the book is flopping." +debug: true +model: power +system: agent_prompt +agent_prompt: + - "= identity.md" +sections: + - agent + - project + - deliverables + - rag + - message + - instructions +steps: + - type: tool + capability: Tool_WebSearcher + optional: true + query: "'{project.name}' romance novel reviews sales Amazon Goodreads TikTok BookTok" + + - type: tool + capability: Tool_WebSearcher + optional: true + query: "'{project.name}' romance book social media engagement Instagram Facebook author" + + - type: think + max_tokens: 4000 + output_key: performance_analysis + hint: | + You are Leo, Marketing Director at Crimson Leaf Marketing. + + Review the web search results above for the "{project.name}" campaign. + Also review the campaign deliverables in the DELIVERABLES section. + + If no web search results are available (tool offline or no data found), note that + and rate the campaign YELLOW with a recommendation to check again in 1 week. + + Analyze campaign performance: + 1. REACH: Are people finding the book? Any search results, reviews, mentions? + 2. ENGAGEMENT: Any social media traction (TikTok, Instagram, Facebook)? + 3. REVIEWS: Any reader reviews on Amazon, Goodreads, or BookTok? + 4. SALES SIGNALS: Any sales rank data, bestseller mentions, or download counts? + 5. SENTIMENT: Is the reception positive, mixed, or negative? + + If the book is too new (less than 2 weeks since campaign launch), note that and + recommend checking again in 1 week. + + Rate overall performance: + - GREEN: Exceeding expectations -- organic traction, positive reviews, good engagement + - YELLOW: Mixed results -- some traction but underperforming potential, or too early to assess + - RED: Minimal traction -- the book is not getting discovered + + End with exactly: + PERFORMANCE_RATING: GREEN|YELLOW|RED + WEEKS_SINCE_LAUNCH: + + - type: think + max_tokens: 100 + output_key: performance_rating + hint: | + Read the PERFORMANCE_RATING line from the analysis above. + Output ONLY the value: GREEN, YELLOW, or RED. Nothing else. + + - type: think + max_tokens: 600 + output_key: learnings_message + hint: | + Read the performance analysis above. + + If performance_rating is GREEN or YELLOW: output exactly: none + + If performance_rating is RED, write a MARKET LEARNINGS report for + Crimson Leaf Holdings strategic team. This report will inform the next book. + + Include: + - What did NOT work in this campaign (specific observations) + - What the market data suggests about genre/audience fit + - What competitors or similar books are doing that we are not + - Concrete recommendations for the next book (genre, themes, marketing channels, + pricing strategy, platform focus) + - Should we continue this book's campaign or pivot resources to the next book? + + Format as a professional post-mortem. Be specific and data-driven. + Output ONLY the report text. No preamble. + + - type: tool + action: enqueue_strategy + optional: true + params: + company_slug: "crimson_leaf" + project_slug: "incubation" + task_type: "market_intelligence" + content: "{learnings_message}" + + - type: document + filename: "campaign_performance_review" + + - type: close + rag_update: true + +adjudication: + enabled: true + pass_threshold: 60 + deliverable_type: analysis + criteria: + completeness: + weight: 40 + description: "All performance dimensions assessed (reach, engagement, reviews, sentiment)" + actionability: + weight: 35 + description: "Learnings are specific and actionable for future books" + accuracy: + weight: 25 + description: "Assessment is grounded in the search evidence, not speculation" \ No newline at end of file