Intent and specification files

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