# Kontextual Engine Functional Requirements Specification V0.1

## kontextual-engine

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## 1. System Overview

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.

This FRS defines the **externally observable functional behavior** of the system.

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## 2. Actors and Interfaces

### 2.1 Primary Actors

* **User (Human Operator)** via API or service interface
* **Automation System (`atm`)** executing workflows
* **LLM Agent (`agt`)** interacting with knowledge and workflows
* **External Systems** integrating via APIs

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### 2.2 System Interfaces

* Service API (HTTP, RPC, or equivalent)
* Programmatic API (SDK/library interface)
* Storage interface (abstracted from implementation)

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## 3. Functional Requirements

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## 3.1 Knowledge Persistence

### FR-001: Store Knowledge Artifacts

**Description:**
The system must allow storage of knowledge artifacts.

**Input:**

* Structured or semi-structured data

**Output:**

* Persisted knowledge artifact with identifier

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### FR-002: Retrieve Knowledge Artifacts

The system must allow retrieval of stored knowledge artifacts by identifier or query.

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### FR-003: Update Knowledge Artifacts

The system must allow modification of existing knowledge artifacts.

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### FR-004: Delete Knowledge Artifacts

The system must allow removal of stored knowledge artifacts.

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## 3.2 Knowledge Organization

### FR-010: Group Knowledge into Collections

The system must allow grouping knowledge artifacts into collections or domains.

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### FR-011: Maintain Relationships

The system must allow defining and retrieving relationships between knowledge artifacts.

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## 3.3 Ingestion and Normalization

### FR-020: Ingest Multi-Format Data

The system must accept input from multiple data formats (e.g. markdown, documents, files).

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### FR-021: Normalize Data

The system must convert ingested data into a structured representation usable by the system.

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## 3.4 Query and Retrieval

### FR-030: Query Knowledge

The system must allow querying knowledge artifacts based on:

* Content
* Metadata
* Relationships

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### FR-031: Return Query Results

The system must return matching knowledge artifacts and associated data.

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## 3.5 Transformation and Composition

### FR-040: Transform Knowledge Artifacts

The system must allow applying transformations to knowledge artifacts.

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### FR-041: Compose Knowledge

The system must allow combining multiple knowledge artifacts into derived outputs.

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## 3.6 Workflow Orchestration

### FR-050: Execute Workflows

The system must allow execution of multi-step workflows on knowledge artifacts.

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### FR-051: Manage Workflow Dependencies

The system must handle dependencies between workflow steps.

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### FR-052: Provide Workflow Results

The system must return results of workflow execution.

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## 3.7 AI Interaction

### FR-060: Support AI-Driven Operations

The system must allow AI agents to:

* Access knowledge
* Trigger transformations
* Participate in workflows

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### FR-061: Maintain Context for AI Interaction

The system must provide contextual information to support AI-driven operations.

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## 3.8 Integration with External Tools

### FR-070: Integrate with Tooling

The system must allow integration with external tooling (e.g. markitect-tool).

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### FR-071: Accept External Processing Results

The system must accept outputs from external tools and incorporate them into knowledge.

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## 3.9 API Interaction

### FR-080: Provide API Access

The system must expose its capabilities through a programmatic interface.

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### FR-081: Support External Invocation

The system must allow external systems to invoke operations on knowledge.

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## 3.10 Error Handling

### FR-090: Provide Structured Errors

The system must return structured error information for invalid operations.

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### FR-091: Avoid Silent Failures

The system must not silently ignore errors affecting correctness.

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## 4. Functional Constraints

* Functions must be accessible through service interfaces
* System must support heterogeneous data formats
* AI-related functions must operate independently of specific providers
* System must not require CLI-based interaction

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## 5. Traceability

| PRD Concept                  | FRS Coverage  |
| ---------------------------- | ------------- |
| Knowledge persistence        | FR-001–FR-004 |
| Organization & relationships | FR-010–FR-011 |
| Ingestion & normalization    | FR-020–FR-021 |
| Query & retrieval            | FR-030–FR-031 |
| Transformation & composition | FR-040–FR-041 |
| Workflow orchestration       | FR-050–FR-052 |
| AI interaction               | FR-060–FR-061 |
| Integration                  | FR-070–FR-071 |
| API access                   | FR-080–FR-081 |

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## 6. Acceptance Perspective

The system satisfies this FRS when:

* Knowledge can be stored, retrieved, and manipulated via API
* Queries return expected results
* Workflows execute and produce observable outputs
* AI agents can interact with knowledge meaningfully
* Errors are explicit and traceable