generated from coulomb/repo-seed
227 lines
6.0 KiB
Markdown
227 lines
6.0 KiB
Markdown
# Infospace Bench Product Requirements Document V0.1
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## infospace-bench
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---
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## 1. Product Overview
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### 1.1 Product Name
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**infospace-bench**
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---
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### 1.2 Product Definition
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infospace-bench is a **workspace and service for creating, developing, evaluating, and inspecting structured knowledge spaces (“infospaces”)**.
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It provides an environment for applying structured knowledge methods to real-world domains such as books, research corpora, projects, and organizational knowledge systems.
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---
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## 2. Product Intent
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### 2.1 Problem Statement
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While tools and systems for structured knowledge exist:
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* There is no consistent way to **develop and evaluate knowledge spaces in practice**
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* Knowledge engineering approaches remain abstract and hard to validate
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* Real-world knowledge artifacts lack **structured inspection and quality evaluation**
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* Iterative refinement of knowledge systems is often ad-hoc and untraceable
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This results in a gap between **knowledge theory and applied knowledge systems**.
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---
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### 2.2 Intended Outcomes
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infospace-bench enables:
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* Creation of **explicit, structured knowledge spaces** as first-class artifacts
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* Iterative **development, evaluation, and refinement** of knowledge collections
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* Inspection of **structure, quality, and relationships** within knowledge
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* Application of AI-assisted workflows to real-world knowledge problems
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* Generation of reusable patterns and insights for knowledge engineering
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---
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### 2.3 Success Criteria
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The product is successful when:
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* Infospaces can be **created, evolved, and inspected systematically**
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* Knowledge quality can be **evaluated and improved over time**
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* Real-world use cases (books, domains, projects) can be modeled effectively
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* AI agents can contribute meaningfully to **knowledge development workflows**
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* Insights from infospaces inform improvements in lower-layer systems
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---
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## 3. Scope Definition
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### 3.1 In Scope
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* Definition and management of infospaces as structured knowledge collections
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* Lifecycle management: creation, population, evaluation, refinement, export
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* Inspection tools for structure, relationships, and quality
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* Application of workflows (generation, transformation, analysis) to infospaces
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* AI-assisted development and evaluation of knowledge artifacts
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* Use-case-specific configurations and project setups
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---
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### 3.2 Out of Scope
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* Low-level markdown processing or transformation primitives
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* Persistent system infrastructure or orchestration engines
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* Generic multi-format content management systems
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* Reusable tooling libraries or platform-level abstractions
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* Final production publishing platforms (outside knowledge development context)
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---
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### 3.3 Boundary Clarification
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infospace-bench provides **application-level usage**, not infrastructure:
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* Tooling primitives → `markitect-tool`
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* System/runtime orchestration → `kontextual-engine`
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---
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## 4. Functional Expectations
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### 4.1 Core Capabilities
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The product must support:
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* **Infospace Definition**
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Create structured knowledge collections with clear boundaries
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* **Population & Development**
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Add, modify, and organize knowledge artifacts
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* **Evaluation & Quality Assessment**
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Measure structure, consistency, and completeness
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* **Inspection & Visualization**
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Explore relationships, dependencies, and structure
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* **Transformation & Generation**
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Apply workflows to evolve knowledge artifacts
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* **Export & Representation**
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Produce outputs (documents, reports, derived artifacts)
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---
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### 4.2 Interaction Modes
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* Project/workspace-based interaction
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* CLI and/or service interfaces
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* Agent-assisted workflows
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---
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## 5. Non-Functional Expectations
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### 5.1 Performance
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* Efficient handling of medium-to-large knowledge collections
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* Reasonable responsiveness for interactive inspection and iteration
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---
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### 5.2 Reliability
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* Consistent behavior in evaluation and transformation workflows
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* Traceable changes and reproducible results
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---
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### 5.3 Extensibility
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* Ability to incorporate new workflows and evaluation methods
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* Flexible configuration for different domains and use cases
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---
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### 5.4 Usability
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* Clear structure for organizing knowledge projects
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* Intuitive workflows for iteration and refinement
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* Transparency of system behavior and results
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---
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## 6. Assumptions and Dependencies
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### 6.1 Assumptions
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* Knowledge engineering benefits from iterative, project-based development
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* AI agents can assist in generating and refining knowledge
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* Structured knowledge systems require evaluation and inspection
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---
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### 6.2 Dependencies
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* kontextual-engine for persistence and orchestration
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* markitect-tool for markdown-based structuring and transformation
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* llm-connect (or equivalent) for AI-assisted workflows
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---
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## 7. Constraints
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* Must remain focused on **concrete infospaces**, not abstract infrastructure
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* Must avoid duplication of tooling or system-level responsibilities
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* Must support both human and AI-driven workflows
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* Must maintain clear traceability of knowledge evolution
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---
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## 8. Risks
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* Drifting into general-purpose platform or CMS functionality
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* Over-complex evaluation frameworks reducing usability
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* Tight coupling to specific tools or formats
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* Loss of clarity between experimentation and production usage
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---
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## 9. Related Systems
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* **markitect-tool** – syntax layer (markdown primitives)
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* **kontextual-engine** – system layer (persistence and orchestration)
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* **llm-connect** – LLM abstraction layer
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---
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## 10. Ecosystem Context
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This product is part of a layered knowledge system:
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```text id="k2pz7m"
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markitect-tool → makes markdown structured and manipulable
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kontextual-engine → makes knowledge persistent and operable
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infospace-bench → makes knowledge concrete and meaningful
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```
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Layers:
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* **Syntax layer** → markitect-tool
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* **System layer** → kontextual-engine
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* **Application layer** → infospace-bench
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---
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## 11. PRD Type
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**Hybrid / Boundary PRD**
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This PRD defines application-level intent and usage boundaries while allowing flexibility for experimentation and iterative development.
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