Covered ADMT without developer documentation to deployers

Ship a deployer-facing model card or deployer guide with each ADMT release covering intended uses, training-data categories, limitations, and human-review instructions.

A deployer-facing documentation artifact versioned with the decision system, such as MODEL_CARD.md or docs/deployer-guide.md (or a Hugging Face model card README with Uses, Bias, Risks, and Limitations, and Training Data sections). It states what the system is for, the categories of data it was trained on, its known limitations and risks, and how a deployer should monitor it and carry out meaningful human review of its outputs. A CI or release step checks that the file exists, carries each of those sections, and names the version being shipped, so a release cannot go out with missing or stale documentation.

Where it goes: 12 repository artifacts, 14 user-facing text, 11 CI/CD pipeline.

What reviewers look for: a model card or deployer guide in the repository (or shipped with the package) with sections for intended uses, training-data categories, known limitations and risks, and monitoring and human-review instructions, matching the current release version; a CI or release check that fails when the document or a section is missing.

# Tenant Screening Scorer
Install with `pip install screener` and call `score(applicant)`.

# Tenant Screening Scorer
Version: 2.3.0  Developer: Example Analytics
## Intended uses
Ranks rental applications for a leasing agent to review. Not for automatic denial.
## Training data
Categories: rental payment history, income verification, eviction filings (personal data).
## Known limitations
Less accurate for applicants with thin credit files; not validated outside the US.
## Human review
Agents see the top factors per score and must review every score below 40 before acting.

Engineering guidance, not legal advice. Each provision below may add its own details (a cadence, a deadline, a required notice element): open it for those.