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markitect-tool

markitect-tool is a markdown-native toolkit and CLI for turning semi-structured Markdown into structured, queryable, reusable knowledge artifacts.

This repository is the syntax-layer successor to the in-scope core of markitect-main. Its product boundary is defined in INTENT.md and the requirements documents in wiki/.

Start Here

  • INTENT.md - project purpose, boundaries, and design principles
  • wiki/ProductRequirementsDocument.md - product scope and success criteria
  • wiki/FunctionalRequirementsSpecification.md - observable functional behavior
  • docs/markitect-main-scope-assessment.md - migration assessment from markitect-main
  • docs/practical-usecase-relevance.md - practical adoption usecases and relevance expectations
  • docs/getting-started.md - first-use guide from checkout to practical commands
  • docs/command-cheatsheet.md - command-oriented workflow cheat sheet
  • docs/examples-index.md - map from examples to usecases and commands
  • docs/source-adapter-contract.md - v1 source adapter contract for external format adapters
  • docs/source-adapter-migration.md - sibling-repo handoff for source adapter adoption
  • docs/performance-notes.md - local performance posture and smoke coverage
  • docs/cli-reference.md - generated mkt command reference
  • docs/api-reference.md - generated public API reference
  • workplans/ - source-of-truth implementation and migration plans

State Hub

The repo is registered with the Custodian State Hub as markitect-tool under the markitect domain. See docs/state-hub-integration.md.

Development

Run the tests:

python3 -m pytest

Install locally from a checkout:

python3 -m pip install -e .
mkt --help

Try the parser CLI from a checkout:

PYTHONPATH=src python3 -m markitect_tool parse README.md --format tree

Generate shell completion and reference docs:

mkt completion bash > ~/.mkt-complete.bash
mkt docs cli --output docs/cli-reference.md
mkt docs api --output docs/api-reference.md
Description
Markdown-native knowledge toolkit providing a contract layer between semi-structured markdown and structured knowledge systems.
Readme MIT-0 1.5 MiB
Languages
Python 100%