pick-a-pii-model
Select an on-device OpenMed PII model from the committed registry by language, runtime format, and size budget, then require recall validation before deployment. Use when an agent must choose a local PII detector for CPU, Apple Silicon, or a mobile export without relying on live model discovery.
Profile →npx skills add maziyarpanahi/openmed --skill pick-a-pii-model --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Pick an on-device PII model Use the committed registry to build an offline shortlist. Treat the language default as the safety baseline, but never treat model size or format as proof of recall. ## Procedure 1. Identify the input language and script before choosing a model. 2. Choose the runtime: `pytorch` for local CPU/GPU and mobile export sources, `mlx-fp` or `mlx-8bit` for Apple Silicon. 3. Read `get_default_pii_model(language)` as the baseline. 4. Filter `get_pii_models_by_language(language)` by runtime and device budget. 5. Prefer the baseline when it fits; otherwise select a compatible candidate. 6. Benchmark the candidate on direct identifiers, critical leakage, scripts, and the target quantization before shipping. ## Runnable offline shortlist This snippet reads only the bundled manifest; it does not download weights. ```python from openmed import get_default_pii_model, get_pii_models_by_language LANGUAGE = "en" TARGET_FORMAT = "mlx-fp" # Use "pytorch" for CPU or as an export source. MAX_PARAMETERS_M = 150 baseline_id = get_default_pii_model(LANGUAGE) models = get_pii_models_by_language(LANGUAGE) shortlist = [ (key, info) for key, info in models.items() if TARGET_FORMAT i
- Procedure
- Runnable offline shortlist
- Selection rules
- Repository example
What does the pick-a-pii-model skill do?
Select an on-device OpenMed PII model from the committed registry by language, runtime format, and size budget, then require recall validation before deployment. Use when an agent must choose a local PII detector for CPU, Apple Silicon, or a mobile export without relying on live model discovery.
How do I install it?
Run `npx skills add maziyarpanahi/openmed --skill pick-a-pii-model --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From maziyarpanahi/openmed, a repository with 4,851 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.