generated from coulomb/repo-seed
248 lines
5.2 KiB
Markdown
248 lines
5.2 KiB
Markdown
# Kontextual Engine Functional Requirements Specification V0.1
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## kontextual-engine
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---
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## 1. System Overview
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kontextual-engine is a **headless knowledge system** that enables persistent storage, transformation, retrieval, and AI-driven operation of structured and semi-structured knowledge across heterogeneous data sources.
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This FRS defines the **externally observable functional behavior** of the system.
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---
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## 2. Actors and Interfaces
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### 2.1 Primary Actors
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* **User (Human Operator)** via API or service interface
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* **Automation System (`atm`)** executing workflows
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* **LLM Agent (`agt`)** interacting with knowledge and workflows
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* **External Systems** integrating via APIs
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---
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### 2.2 System Interfaces
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* Service API (HTTP, RPC, or equivalent)
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* Programmatic API (SDK/library interface)
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* Storage interface (abstracted from implementation)
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---
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## 3. Functional Requirements
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---
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## 3.1 Knowledge Persistence
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### FR-001: Store Knowledge Artifacts
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**Description:**
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The system must allow storage of knowledge artifacts.
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**Input:**
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* Structured or semi-structured data
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**Output:**
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* Persisted knowledge artifact with identifier
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---
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### FR-002: Retrieve Knowledge Artifacts
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The system must allow retrieval of stored knowledge artifacts by identifier or query.
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---
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### FR-003: Update Knowledge Artifacts
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The system must allow modification of existing knowledge artifacts.
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---
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### FR-004: Delete Knowledge Artifacts
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The system must allow removal of stored knowledge artifacts.
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---
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## 3.2 Knowledge Organization
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### FR-010: Group Knowledge into Collections
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The system must allow grouping knowledge artifacts into collections or domains.
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---
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### FR-011: Maintain Relationships
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The system must allow defining and retrieving relationships between knowledge artifacts.
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---
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## 3.3 Ingestion and Normalization
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### FR-020: Ingest Multi-Format Data
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The system must accept input from multiple data formats (e.g. markdown, documents, files).
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---
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### FR-021: Normalize Data
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The system must convert ingested data into a structured representation usable by the system.
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---
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## 3.4 Query and Retrieval
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### FR-030: Query Knowledge
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The system must allow querying knowledge artifacts based on:
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* Content
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* Metadata
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* Relationships
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---
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### FR-031: Return Query Results
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The system must return matching knowledge artifacts and associated data.
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---
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## 3.5 Transformation and Composition
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### FR-040: Transform Knowledge Artifacts
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The system must allow applying transformations to knowledge artifacts.
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---
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### FR-041: Compose Knowledge
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The system must allow combining multiple knowledge artifacts into derived outputs.
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---
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## 3.6 Workflow Orchestration
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### FR-050: Execute Workflows
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The system must allow execution of multi-step workflows on knowledge artifacts.
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---
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### FR-051: Manage Workflow Dependencies
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The system must handle dependencies between workflow steps.
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---
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### FR-052: Provide Workflow Results
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The system must return results of workflow execution.
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---
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## 3.7 AI Interaction
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### FR-060: Support AI-Driven Operations
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The system must allow AI agents to:
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* Access knowledge
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* Trigger transformations
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* Participate in workflows
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---
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### FR-061: Maintain Context for AI Interaction
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The system must provide contextual information to support AI-driven operations.
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---
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## 3.8 Integration with External Tools
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### FR-070: Integrate with Tooling
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The system must allow integration with external tooling (e.g. markitect-tool).
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---
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### FR-071: Accept External Processing Results
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The system must accept outputs from external tools and incorporate them into knowledge.
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---
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## 3.9 API Interaction
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### FR-080: Provide API Access
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The system must expose its capabilities through a programmatic interface.
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---
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### FR-081: Support External Invocation
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The system must allow external systems to invoke operations on knowledge.
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---
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## 3.10 Error Handling
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### FR-090: Provide Structured Errors
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The system must return structured error information for invalid operations.
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---
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### FR-091: Avoid Silent Failures
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The system must not silently ignore errors affecting correctness.
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---
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## 4. Functional Constraints
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* Functions must be accessible through service interfaces
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* System must support heterogeneous data formats
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* AI-related functions must operate independently of specific providers
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* System must not require CLI-based interaction
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---
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## 5. Traceability
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| PRD Concept | FRS Coverage |
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| ---------------------------- | ------------- |
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| Knowledge persistence | FR-001–FR-004 |
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| Organization & relationships | FR-010–FR-011 |
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| Ingestion & normalization | FR-020–FR-021 |
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| Query & retrieval | FR-030–FR-031 |
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| Transformation & composition | FR-040–FR-041 |
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| Workflow orchestration | FR-050–FR-052 |
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| AI interaction | FR-060–FR-061 |
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| Integration | FR-070–FR-071 |
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| API access | FR-080–FR-081 |
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---
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## 6. Acceptance Perspective
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The system satisfies this FRS when:
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* Knowledge can be stored, retrieved, and manipulated via API
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* Queries return expected results
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* Workflows execute and produce observable outputs
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* AI agents can interact with knowledge meaningfully
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* Errors are explicit and traceable
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