Update docs/MVP-PRD.md
adding requirements
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@@ -48,6 +48,9 @@ We will use the following prioritization model:
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- **P3**: Use cases that bring additional value but can be cut if time or resource constrained.
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## Chapter 2: User Stories (Bob)
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These user stories are based on the personas and archetypes document contained in this repo.
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Chapter 2.1 - Bob's user stories
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**As Bob, I want to…**
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@@ -65,10 +68,62 @@ We will use the following prioritization model:
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**Bob-30.** Understand why a particular signal is considered strong or weak (e.g., cross-source convergence or falsification results).
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Chapter 2.2 - Alice's user stories
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As Alice, I want to…
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Alice-1. Integrate deep, vetted research directly into my existing content production pipeline so I can reduce manual research time.
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Alice-5. Query the research system with follow-up questions to explore specific angles or topics on demand.
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Alice-10. Have my tools automatically receive curated, high-signal research so I can focus on content creation instead of information filtering.
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Alice-15. Get research outputs in a structured format that my existing AI tools and workflows can consume without manual reformatting.
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Alice-20. Quickly surface non-obvious insights and patterns from research data to develop more compelling content angles.
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Alice-25. Control which research sources and signals are prioritized so the output stays aligned with my content focus and audience.
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Alice-30. Understand the reasoning and supporting evidence behind key research findings so I can speak to them confidently in my content.
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## Chapter 3: Requirements
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Requirements defined as what the product / system must do, differentiated from what the persona can accomplish. Requirements are defined to meet the needs of use cases as well as the architectural system design.
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This chapter captures non-functional and system-level requirements that support the product vision but are not expressed as user stories.
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High level design (refer to ***TBD_Design.MD for full design details)
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Linux
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>> Docker
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> > SQLLite
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> > CRON
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> > Runtime
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> > HTTP client (internet accessible)
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> > Supports OpenAI inference endpoint
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> > Supports HTTP queries for data feeds (RSS, Curl, Playwright?)
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> > HTTP server endpoint (internet acceesible)
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> > MCP
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> > HTTP client (intranet)
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> > Supports OpenAI inference endpoint to Hermes
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> > File system
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> > Output dir for daily digest artifact (saved outside of the docker container)
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> > Diagnostics / instrumentation (should land in the Docker infa for this container)
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> > Configuration
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> > Research topic mainfest (feeds, URLS, declarations)
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> > System settings (YAML)
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> > System secrets (.env))
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> > Business logic
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> > Starting trigger
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> > preflight check
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> > Query feeds / TMP store results
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> > Vet temp results / store final results to DB
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> > Produce digest (if configured)
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> > Cleanup / sleep
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3.1 Setup and configuration (REQ-SNC-XX)
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Requirements for initial setup, deployment configs, updating, and uninstall
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REQ-SNC-05 -, with outbound access to the internet and in/outbound access to the underlying OS network
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REQ-SNC-10 - The installation process shall be a single command which can be run interactively or silently
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REQ-SNC-15 - The insallation shall utilize best-practice settings and secrets storage
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REQ-SNC-20 -
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3.2 Platform requirements (REQ-PLT-XX)
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REQ-PLT-05 - All processes will run as standard user (no admin / sudo elevation necessary)
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REQ-PLT-10 - All internet-facting HTTP endpoints shall be TLS protected with well known can
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REQ-PLT-15 - The system shall be Docker based limited to 150MB of memory
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Requirements addressing what OS and hardware support is in scope
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3.3 Performance and scalability (REQ-PERF-XX)
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3.4 Instrumenation and diagnostics (REQ-DIAG-XX)
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3.5
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### 3.1 Reliability
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**REQ-REL-05:** Once setup and configured, the system will reliably operate without interaction from the user.
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