AI AGENTS
Candidate model shortlist to Notion scorecard
On demand, an agent searches HuggingFace for models matching a task brief, reads each candidate's card.
How it runs
The automated pipeline, trigger to output.
- TriggerManual run with task brief
- ActionSearch HuggingFace for candidatesHugging Face
- ActionFetch each candidate's model cardHugging Face
- ActionScore and rank candidatesOpenAI
- OutputWrite ranked scorecard to NotionNotion
What it does
Turns a one-line task brief into a ranked, side-by-side model comparison. The agent finds candidate HuggingFace models, reads their cards, scores each on the dimensions you care about, and lands a tidy scorecard in Notion.
When to use it
Use at the start of a model-selection effort, when you need an evidence-backed shortlist instead of guessing from popularity counts. Good for kicking off an evaluation spike before anyone writes integration code.
How it works
- 1You run it manually with a task description and constraints (e.g. task type, max size, license).
- 2The agent queries HuggingFace for candidate models that match the task.
- 3For each candidate it fetches the model card and key metadata.
- 4An LLM scores every candidate on fit, license, size, and evaluation evidence, then ranks them with a short rationale each.
- 5The ranked scorecard is written as rows in a Notion database, one row per model.
Set it up
What you configure once, before turning it on.
- 1Connect Hugging FaceModels, datasets, spaces — the open-source hub.
- 2Connect OpenAIModels, embeddings, files.
- 3Connect NotionPages, databases, comments.
- 4Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 5Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 6Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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Run it inside a business
This workflow drops into a full company template. Import the org, and this is one of the playbooks its agents run.
Run this workflow in your colony.
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