# python-typelets - Doramagic AI Context Pack

> Purpose: pre-work context for the user's host AI. This pack does not prove that the project has been installed, run, or validated.

## Project

- canonical_name: `beanbaginc/python-typelets`
- capability: Type hints and utility objects for Python and Django projects.
- expected_user_outcome: Type hints and utility objects for Python and Django projects.

## Operating Boundaries

- Do not claim that the project has been installed, run, called through an API, or used on local files unless separate evidence proves it.
- Project facts must come from repo evidence, Claim Graph, or explicit source references.
- When a capability is not verified, mark it as unverified instead of completing it as fact.
- publish_status: `publishable`
- blocking_gaps: none

---

## Doramagic Context Augmentation

The following sections strengthen the repository context for a host AI. Human Manual data is a reading route, and pitfall notes become operating constraints.

## Human Manual Outline

Usage rule: this is only a reading route and salience signal, not factual authority. Concrete claims must still return to repo evidence or Claim Graph.

Host AI hard rules:
- Do not treat page titles, section order, summaries, or importance values as factual project evidence.
- When explaining the Human Manual outline, state that it is only a reading route or salience signal.
- Capability, installation, compatibility, runtime state, and risk claims must cite repo evidence, source paths, or Claim Graph.

- **Overview and Module Architecture**: importance `high`
  - source_paths: README.md, typelets/__init__.py, typelets/py.typed
- **General Python Typing Utilities**: importance `high`
  - source_paths: typelets/funcs.py, typelets/json.py, typelets/symbols.py, typelets/runtime.py
- **Django Typing Extensions**: importance `high`
  - source_paths: typelets/django/__init__.py, typelets/django/auth.py, typelets/django/forms.py, typelets/django/json.py, typelets/django/models.py
- **Versioning, Releases, and Contributing**: importance `medium`
  - source_paths: typelets/_version.py, README.md

## Repo Inspection Evidence

- repo_clone_verified: true
- repo_inspection_verified: true
- repo_commit: `7c2c0523a776311d2ddd4793b1704a8177effaba`
- inspected_files: `README.md`, `pyproject.toml`, `docs/conf.py`, `docs/settings.py`

Host AI hard rules:
- Without repo_clone_verified=true, do not claim that the source code has been read.
- Without repo_inspection_verified=true, do not write README, docs, or package-file conclusions as facts.
- Without quick_start_verified=true, do not claim that the Quick Start path has run successfully.

## Doramagic Pitfall Constraints

These rules come from Doramagic discovery, validation, or compilation findings. The host AI must treat them as operating constraints, not background notes.

### Constraint 1: Identity risk requires verification

- Trigger: Project evidence flags a identity risk. Review the linked source before relying on this workflow.
- Host AI rule: Reproduce the official install and quickstart path in an isolated environment.
- Why it matters: May increase setup, validation, or first-run risk for the user.
- Evidence: identity.distribution | https://github.com/beanbaginc/python-typelets
- Hard boundary: Do not present this pitfall as solved, verified, or ignorable unless later evidence explicitly closes it.

### Constraint 2: Capability evidence risk requires verification

- Trigger: README/documentation is current enough for a first validation pass.
- Host AI rule: Reproduce the official install and quickstart path in an isolated environment.
- Why it matters: May increase setup, validation, or first-run risk for the user.
- Evidence: capability.assumptions | https://github.com/beanbaginc/python-typelets
- Hard boundary: Do not present this pitfall as solved, verified, or ignorable unless later evidence explicitly closes it.

### Constraint 3: Maintenance risk requires verification

- Trigger: Project evidence flags a maintenance risk. Review the linked source before relying on this workflow.
- Host AI rule: Reproduce the official install and quickstart path in an isolated environment.
- Why it matters: May increase setup, validation, or first-run risk for the user.
- Evidence: evidence.maintainer_signals | https://github.com/beanbaginc/python-typelets
- Hard boundary: Do not present this pitfall as solved, verified, or ignorable unless later evidence explicitly closes it.

### Constraint 4: Security or permission risk requires verification

- Trigger: no_demo
- Host AI rule: Reproduce the official install and quickstart path in an isolated environment.
- Why it matters: May increase setup, validation, or first-run risk for the user.
- Evidence: downstream_validation.risk_items | https://github.com/beanbaginc/python-typelets
- Hard boundary: Do not present this pitfall as solved, verified, or ignorable unless later evidence explicitly closes it.

### Constraint 5: Security or permission risk requires verification

- Trigger: no_demo
- Host AI rule: Reproduce the official install and quickstart path in an isolated environment.
- Why it matters: May increase setup, validation, or first-run risk for the user.
- Evidence: risks.scoring_risks | https://github.com/beanbaginc/python-typelets
- Hard boundary: Do not present this pitfall as solved, verified, or ignorable unless later evidence explicitly closes it.

### Constraint 6: Maintenance risk requires verification

- Trigger: issue_or_pr_quality=unknown。
- Host AI rule: Reproduce the official install and quickstart path in an isolated environment.
- Why it matters: May increase setup, validation, or first-run risk for the user.
- Evidence: evidence.maintainer_signals | https://github.com/beanbaginc/python-typelets
- Hard boundary: Do not present this pitfall as solved, verified, or ignorable unless later evidence explicitly closes it.

### Constraint 7: Maintenance risk requires verification

- Trigger: release_recency=unknown。
- Host AI rule: Reproduce the official install and quickstart path in an isolated environment.
- Why it matters: May increase setup, validation, or first-run risk for the user.
- Evidence: evidence.maintainer_signals | https://github.com/beanbaginc/python-typelets
- Hard boundary: Do not present this pitfall as solved, verified, or ignorable unless later evidence explicitly closes it.
