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CLAUDE.md
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CLAUDE.md
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# CLAUDE.md
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This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
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## Custodian State Hub Integration
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This project is tracked as the **markitect** domain in the Custodian State Hub.
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Hub topic ID: `5571d954-0d30-4950-980d-7bcaaad8e3e2`
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**Session start:** Call `get_domain_summary("markitect")` via the `state-hub` MCP tool.
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If the hub is not reachable: `cd ~/the-custodian/state-hub && make api`
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**Session end:** Call `add_progress_event()` with `topic_id` above, a `summary`, and `event_type` (`note` / `milestone` / `blocker`).
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**Available state-hub MCP tools:** `get_state_summary`, `get_domain_summary`, `add_progress_event`, `create_workstream`, `create_task`, `update_task_status`, `record_decision`, `resolve_decision`.
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If the hub API is unavailable, use `curl` against `http://127.0.0.1:8000/docs`.
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---
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## Development Commands
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All commands assume the `markitect-venv` virtual environment is active (`source ~/.venvs/markitect-venv/bin/activate` or equivalent). The package is installed in editable mode.
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```bash
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# Run the core test suite
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pytest
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# Run a single test file
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pytest tests/test_issue_17_batch_processing.py
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# Run tests by marker
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pytest -m unit
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pytest -m "not slow"
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# Run with coverage
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pytest --cov=markitect
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# Run only fast unit tests (TDD inner loop)
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pytest tests/unit/
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# CLI entry point
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markitect --help
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# Infospace subcommands (primary active development area)
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markitect infospace --help
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markitect infospace eval-summary --update-metrics
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# LLM helper commands
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markitect llm-helper "<question>"
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markitect llm-catalog
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markitect llm-check
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markitect llm-default
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markitect llm-preference
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# Install / reinstall in dev mode
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pip install -e ".[analysis]"
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```
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## Architecture
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MarkiTect is a CLI-driven markdown engine that treats documents as structured, queryable information spaces. Entry point: `markitect/cli.py` → `main()` (Click group). All subcommand groups are registered at the bottom of `cli.py`.
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### Core Modules (`markitect/`)
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| Module | Purpose |
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|--------|---------|
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| `spaces/` | InformationSpace model — composability, events, history, transclusion, rendering, sync |
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| `prompts/` | Prompt resolver, compiler, execution engine, quality gates, dependency graph, traceability |
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| `llm/` | LLM adapter layer — 4 text providers + embedding adapter; 7-layer config resolution |
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| `infospace/` | Infospace lifecycle — init, entity parsing, evaluation, composition, graph export |
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| `analysis/` | Graph analysis (networkx) and FCA (Formal Concept Analysis, pure Python) |
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| `schema*/` | Schema generation, validation, naming, refinement, metaschema |
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| `core/` | Foundational parser, AST, serializer, workspace |
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### LLM Configuration (`markitect/llm/`)
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Resolution order (highest → lowest priority):
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1. CLI flags (`--provider`, `--model`)
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2. `MARKITECT_HELPER_MODEL` env var (model only)
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3. User preference (`[llm.preference]` in `~/.config/markitect/config.toml`)
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4. Directory preference (`[llm.preference]` in `.markitect.toml`)
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5. Directory default (`[llm.default]` in `.markitect.toml`)
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6. User default (`[llm.default]` in `~/.config/markitect/config.toml`)
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7. Hardcoded fallback: `gemini/gemini-2.5-flash`
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Canonical models: `markitect/llm/models.py` (`RunConfig`, `LLMResponse`) and `markitect/llm/adapter.py` (`LLMAdapter`). These are mirrored in the standalone `/home/worsch/llm-connect/` package (`llm_connect`), which is installed as a local path dependency. `markitect/prompts/execution/{models,llm_adapter}.py` are re-export shims for backward compatibility.
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**Gotcha:** The `OPENROUTER_API_KEY` env var may hold a stale key — `unset OPENROUTER_API_KEY` before running LLM commands if you get auth errors. `claude-code` provider fails inside Claude Code sessions (nested session restriction).
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### Infospace (`markitect/infospace/`)
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An infospace is a directory-based collection of typed entities governed by an `infospace.yaml` config. Key files:
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- `config.py` — config loading, `find_infospace_config()`, `DisciplineBinding`
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- `entity_parser.py` — parse entity markdown files from `output/entities/<slug>.md`
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- `evaluation.py` / `evaluation_io.py` — per-entity LLM evaluation (5 dimensions)
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- `state.py` — `build_state()` aggregates entity + evaluation state
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- `history.py` / `checks/` — viability tracking and collection-level checks
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Slugs use **underscores** (e.g., `accumulation_of_stock`). Active example: `examples/infospace-with-history/` (988 entities).
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### Layered Architecture
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The project has a partially-implemented layered architecture separate from `markitect/`:
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- `domain/` — domain models (issues, projects)
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- `infrastructure/` — config, repositories, logging, connection management
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- `application/` — application layer (mostly empty)
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- `capabilities/` — pluggable capability packages (`issue-facade`, `release-management`, `testdrive-jsui`, `markitect-utils`, `markitect-content`, `kaizen-agentic`)
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### Tests
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Tests live in `tests/`. Many test files are named `test_issue_NNN_*.py` (TDD by issue). Layered tests follow `test_l{N}_*.py` naming. The `tests/unit/` subtree has the cleanest structure and covers `prompts/`, `spaces/`, `llm/`, `infospace/`, `analysis/`.
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Pytest config is in `pytest.ini`. Relevant markers: `unit`, `integration`, `e2e`, `slow`, `performance`.
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### Active Roadmap Files
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- `roadmap/infospace-tooling/PLAN.md` — main infospace roadmap (S1 ✅ S2 ✅ S3 nearly done)
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- `roadmap/infospace-s3-closeout/PLAN.md` — S3 close-out tasks (C.1–C.8)
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- `roadmap/llm-shared-library/PLAN.md` — llm-connect extraction (S1+S2 done, S3 pending)
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# markitect-main — Claude Code Instructions
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@SCOPE.md
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@.claude/rules/repo-identity.md
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@.claude/rules/session-protocol.md
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@.claude/rules/first-session.md
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@.claude/rules/workplan-convention.md
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@.claude/rules/stack-and-commands.md
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@.claude/rules/architecture.md
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@.claude/rules/repo-boundary.md
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@.claude/rules/agents.md
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