model-bank-metadata
Backfill and maintain model-bank metadata (knowledgeCutoff, family, generation). Use when adding models, fixing cutoff/family data, running a metadata sweep across aiModels providers, or researching official knowledge cutoffs.
Profile →npx skills add lobehub/lobehub --skill model-bank-metadata --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.
# Model-Bank Metadata (knowledgeCutoff / family / generation) How to populate and maintain the three structured metadata fields on `packages/model-bank/src/aiModels/*.ts` model cards, at single-model scale (new model PR) or repo-wide scale (sweep across \~80 provider files / \~1900 entries). ## Field semantics | Field | Format | Meaning | | ----------------- | ----------------------------------------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | `knowledgeCutoff` | `'YYYY-MM'` (or `'YYYY'` if only the year is published) | World-knowledge cutoff. When a vendor distinguishes a **"reliable knowledge cutoff"** from the broader training-data cutoff (Anthropic does), always use the **reliable** one. | | `family` | lowercase slug (`claude`, `gpt`, `o-series`, `qwen`, `deepseek`, `llama`, `glm`, …) | Model lineage, finer than `organization`. Lets the UI group models and match the same model across aggregator providers. | | `generation` | family slug + version (`claude-4.6`, `gpt-5.2`, `qwen3.5`, `llama-3.1
- Field semantics
- Sourcing rules for knowledgeCutoff
- family/generation derivation
- Repo-wide sweep workflow
- Maintenance rules
What does the model-bank-metadata skill do?
Backfill and maintain model-bank metadata (knowledgeCutoff, family, generation). Use when adding models, fixing cutoff/family data, running a metadata sweep across aiModels providers, or researching official knowledge cutoffs.
How do I install it?
Run `npx skills add lobehub/lobehub --skill model-bank-metadata --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 lobehub/lobehub, a repository with 81,252 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.