Update README.md

README.md

@@ -13,4 +13,354 @@ tags:
 - songwriting
 - tiktok
 - creativity
----
+---
+
+<p align="center">
+  <img src="./assets/viralmuse.png" alt="Agentarium — Agent #002 • Viral Muse" width="720" />
+</p>
+
+Viral Muse – Music Pattern Agent
+
+A dataset-driven creative agent for music concept development: hooks, song structures, TikTok-native concepts, genre transformations, and viral-signal auditing.
+
+This is not a finetuned model with weights. It’s an Agentarium-style agent package (system prompt + reasoning + personality + guardrails) bundled with RAG datasets + a lightweight knowledge graph (atoms/edges/knowledge map) so builders can plug it into their own runtime (n8n, LangChain, Flowise, Dify, custom app).
+
+
+---
+
+What it does
+
+Hook generation (concept-first): multiple hook angles with replay triggers
+
+Song structure blueprinting: verse/pre/chorus/bridge plans + escalation rules
+
+TikTok concept patterns: openers, filming format, loop mechanics, cut points
+
+Genre transformations: keep the “core payload” while changing genre skin
+
+Viral signal audit: clarity, novelty, tension, comment-bait, replay value
+
+Creative partner advice: testable edits + A/B variants + what to watch in metrics
+
+
+
+---
+
+What’s inside
+
+Core agent components
+
+core/system_prompt.md
+
+core/reasoning_template.md
+
+core/personality_fingerprint.md
+
+guardrails/guardrails.md
+
+
+Datasets (RAG)
+
+datasets/lyric_structure_map.csv
+
+datasets/viral_pattern_signals.csv
+
+datasets/genre_transformation_rules.csv
+
+datasets/tiktok_concept_patterns.csv
+
+datasets/viral_potential_rated.csv
+
+datasets/creative_partner_advice_map.csv
+
+
+Knowledge graph (optional but included)
+
+datasets/knowledge_map.csv
+
+datasets/atoms_master.csv
+
+datasets/edges_master.csv
+
+
+Docs + memory
+
+docs/product_readme.md
+
+docs/use_cases.md
+
+docs/workflow_notes.md
+
+memory_schemas/user_profile_memory.csv
+
+memory_schemas/project_workspace_memory.csv
+
+memory_schemas/memory_rules.md
+
+
+Manifest
+
+meta/agent_manifest.json
+
+
+
+---
+
+Quick start (RAG runtime)
+
+1) Load the agent prompt stack (in this order)
+
+1. core/system_prompt.md (system message)
+
+
+2. guardrails/guardrails.md
+
+
+3. core/reasoning_template.md (developer/hidden rules)
+
+
+4. core/personality_fingerprint.md (style constraints)
+
+
+
+2) Upsert datasets to your Vector DB
+
+Convert each CSV row into a clean “retrieval document” and embed it.
+Recommended metadata per vector:
+
+dataset (which CSV it came from)
+
+row_id (or primary key)
+
+optional tags (genre, pattern_type, etc.)
+
+
+3) At runtime
+
+Classify intent (hook / structure / TikTok / genre flip / audit)
+
+Retrieve top-K rows from the relevant dataset(s)
+
+Synthesize an output that is structured, testable, and compact
+
+If something isn’t in retrieved context, say unknown (don’t invent dataset facts)
+
+
+See docs/workflow_notes.md for a step-by-step n8n-style implementation.
+
+
+---
+
+Example prompts
+
+“Give me 10 hook angles for bittersweet confidence — modern pop. Add replay triggers.”
+
+“Design a 30s TikTok loop concept: 1 angle, 1 prop, bedroom performance.”
+
+“Transform this concept into cumbia, then alt-rock. Keep the emotional payload.”
+
+“Audit this chorus for viral signals. Give minimal fixes, not a full rewrite.”
+
+
+
+---
+
+Guardrails (important)
+
+No imitation or reproduction of copyrighted lyrics/melodies.
+
+No “copy this artist/song” outputs.
+
+No hallucinated dataset claims: stay grounded in retrieved rows.
+
+Outputs should be structured (variants, constraints, test plan).
+
+
+
+---
+
+License
+
+Set your preferred license in LICENSE and in meta/agent_manifest.json.
+
+
+---
+
+Credits
+
+Created by Agentarium (Frank / FlowMancer).
+Package standard: Agentarium v1.Viral Muse – Music Pattern Agent
+
+A dataset-driven creative agent for music concept development: hooks, song structures, TikTok-native concepts, genre transformations, and viral-signal auditing.
+
+This is not a finetuned model with weights. It’s an Agentarium-style agent package (system prompt + reasoning + personality + guardrails) bundled with RAG datasets + a lightweight knowledge graph (atoms/edges/knowledge map) so builders can plug it into their own runtime (n8n, LangChain, Flowise, Dify, custom app).
+
+
+---
+
+What it does
+
+Hook generation (concept-first): multiple hook angles with replay triggers
+
+Song structure blueprinting: verse/pre/chorus/bridge plans + escalation rules
+
+TikTok concept patterns: openers, filming format, loop mechanics, cut points
+
+Genre transformations: keep the “core payload” while changing genre skin
+
+Viral signal audit: clarity, novelty, tension, comment-bait, replay value
+
+Creative partner advice: testable edits + A/B variants + what to watch in metrics
+
+
+
+---
+
+What’s inside
+
+Core agent components
+
+core/system_prompt.md
+
+core/reasoning_template.md
+
+core/personality_fingerprint.md
+
+guardrails/guardrails.md
+
+
+Datasets (RAG)
+
+datasets/lyric_structure_map.csv
+
+datasets/viral_pattern_signals.csv
+
+datasets/genre_transformation_rules.csv
+
+datasets/tiktok_concept_patterns.csv
+
+datasets/viral_potential_rated.csv
+
+datasets/creative_partner_advice_map.csv
+
+
+Knowledge graph (optional but included)
+
+datasets/knowledge_map.csv
+
+datasets/atoms_master.csv
+
+datasets/edges_master.csv
+
+
+Docs + memory
+
+docs/product_readme.md
+
+docs/use_cases.md
+
+docs/workflow_notes.md
+
+memory_schemas/user_profile_memory.csv
+
+memory_schemas/project_workspace_memory.csv
+
+memory_schemas/memory_rules.md
+
+
+Manifest
+
+meta/agent_manifest.json
+
+
+
+---
+
+Quick start (RAG runtime)
+
+1) Load the agent prompt stack (in this order)
+
+1. core/system_prompt.md (system message)
+
+
+2. guardrails/guardrails.md
+
+
+3. core/reasoning_template.md (developer/hidden rules)
+
+
+4. core/personality_fingerprint.md (style constraints)
+
+
+
+2) Upsert datasets to your Vector DB
+
+Convert each CSV row into a clean “retrieval document” and embed it.
+Recommended metadata per vector:
+
+dataset (which CSV it came from)
+
+row_id (or primary key)
+
+optional tags (genre, pattern_type, etc.)
+
+
+3) At runtime
+
+Classify intent (hook / structure / TikTok / genre flip / audit)
+
+Retrieve top-K rows from the relevant dataset(s)
+
+Synthesize an output that is structured, testable, and compact
+
+If something isn’t in retrieved context, say unknown (don’t invent dataset facts)
+
+
+See docs/workflow_notes.md for a step-by-step n8n-style implementation.
+
+
+---
+
+Example prompts
+
+“Give me 10 hook angles for bittersweet confidence — modern pop. Add replay triggers.”
+
+“Design a 30s TikTok loop concept: 1 angle, 1 prop, bedroom performance.”
+
+“Transform this concept into cumbia, then alt-rock. Keep the emotional payload.”
+
+“Audit this chorus for viral signals. Give minimal fixes, not a full rewrite.”
+
+
+
+---
+
+Guardrails (important)
+
+No imitation or reproduction of copyrighted lyrics/melodies.
+
+No “copy this artist/song” outputs.
+
+No hallucinated dataset claims: stay grounded in retrieved rows.
+
+Outputs should be structured (variants, constraints, test plan).
+
+
+
+---
+
+License
+
+Set your preferred license in LICENSE and in meta/agent_manifest.json.
+
+
+---
+
+Credits
+
+Created by Agentarium (Frank Brsrk ).
+Package standard: Agentarium 
+email: agentariumfrankbrsrk@gmail.com 
+X: @frank_brsrk 
+Reddit: @frank_brsrk 
+Substack : @frankbrsrk