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kontextual-engine/workplans/KONT-WP-0003-engine-implementation.md

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id, type, title, domain, repo, status, owner, topic_slug, created, updated, state_hub_workstream_id
id type title domain repo status owner topic_slug created updated state_hub_workstream_id
KONT-WP-0003 workplan Headless Knowledge Engine Implementation markitect kontextual-engine done codex markitect 2026-05-03 2026-05-05 0fd08391-e8c9-4f1b-ace4-06439f958e88

KONT-WP-0003: Headless Knowledge Engine Implementation

Purpose

Build the first usable kontextual-engine runtime around the PRD/FRS contract: persistent knowledge artifacts, collections, relationships, ingestion, retrieval, workflows, and agent-operable context.

I3.1 - Scaffold package and test harness

id: KONT-WP-0003-T001
status: done
priority: high
state_hub_task_id: "3d3400a5-63ee-4c64-8bfb-fd3caa1ce787"

Create the initial Python package, dependency metadata, test harness, and CI commands after the stack decision in KONT-WP-0001.

Output: pyproject.toml, src/kontextual_engine/, and tests/.

I3.2 - Implement artifact and collection model

id: KONT-WP-0003-T002
status: done
priority: high
state_hub_task_id: "638ce4d0-b96b-4d8f-8bd9-4c77acad0a59"

Implement core models for artifacts, metadata, collections, domains, and relationships. Cover FR-001 through FR-011 with focused unit tests.

Output: src/kontextual_engine/artifacts.py, src/kontextual_engine/relationships.py, and tests/test_artifacts.py.

I3.3 - Implement storage abstraction

id: KONT-WP-0003-T003
status: done
priority: high
state_hub_task_id: "41c84f25-96b0-40eb-b2b4-834938cf9bb9"

Define repository interfaces and the first backend. Start with the simplest backend that can support deterministic tests, then document the path to SQLite or service-backed persistence.

Output: src/kontextual_engine/storage.py and tests/test_storage_query.py.

I3.4 - Implement ingestion and normalization interfaces

id: KONT-WP-0003-T004
status: done
priority: high
state_hub_task_id: "0be5fff9-f4a2-4aee-86b9-b84feef477f7"

Define format-agnostic ingestion contracts. Add a markdown adapter boundary that can later call markitect-tool, without embedding markdown primitives in this repo.

Output: src/kontextual_engine/ingestion.py.

I3.5 - Implement query and retrieval API

id: KONT-WP-0003-T005
status: done
priority: high
state_hub_task_id: "c8841fab-6dd1-47e1-a794-798bef1663e7"

Provide programmatic query over identifiers, metadata, content references, and relationships. Cover FR-030 and FR-031 with tests.

Output: src/kontextual_engine/query.py.

I3.6 - Implement workflow run model

id: KONT-WP-0003-T006
status: done
priority: high
state_hub_task_id: "0d62f47c-339a-4d86-9ab0-737bd4ab553c"

Represent workflow runs, steps, dependencies, inputs, outputs, structured errors, and derived artifacts. Cover FR-040 through FR-052.

Output: src/kontextual_engine/workflows.py.

I3.7 - Implement agent context surface

id: KONT-WP-0003-T007
status: done
priority: medium
state_hub_task_id: "96689817-e8e9-42e4-9af3-f03021e3ae4e"

Provide a provider-neutral context assembly API so agents can inspect knowledge state, trigger operations, and receive traceable results.

Output: src/kontextual_engine/context.py.

I3.8 - Define service API boundary

id: KONT-WP-0003-T008
status: done
priority: medium
state_hub_task_id: "0f4748f9-934a-438c-ac2d-e9796ad98818"

Decide and document the first HTTP/RPC service boundary after the programmatic API is stable enough to avoid framework-driven architecture.

Output: docs/service-api-boundary.md.