README.md

metadata

pretty_name: Brief 003 - Marketing brief review
language:
  - en
tags:
  - marketing
  - synthetic
  - human-review
size_categories:
  - n<1K
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/briefs.csv
    usecols:
      - id
      - user_text
      - deliverable
      - product_description
      - offer
      - audience_description
      - awareness
      - evidence
      - prohibited
      - status
      - industry
      - price_point
      - completeness
      - approval
dataset_info:
  features:
    - name: id
      dtype: string
    - name: user_text
      dtype: string
    - name: deliverable
      dtype: string
    - name: product_description
      dtype: string
    - name: offer
      dtype: string
    - name: audience_description
      dtype: string
    - name: awareness
      dtype: string
    - name: evidence
      dtype: string
    - name: prohibited
      dtype: string
    - name: status
      dtype: string
    - name: industry
      dtype: string
    - name: price_point
      dtype: string
    - name: completeness
      dtype: string
    - name: approval
      dtype: bool

Brief 003 · Marketing brief review

Review the generated marketing requests and record approval directly in the dataset. This batch contains 339 briefs. All products, offers, and supporting claims are fictional.

Start reviewing

Open the brief viewer and editor →

1. Click a row to inspect the brief. Start with user_text, the request a user would send to the model.
2. Compare it with the structured brief: deliverable, product_description, offer, audience_description, awareness, evidence, and prohibited.
3. Click Toggle Edit Mode in Data Studio. Set approval to true to approve or false to reject. Leave it null until reviewed. Editing requires a Hugging Face account with write access to this repository.
4. Click Commit to save your edits. Until committed, changes are only staged in your browser.

Approval	When to use it
null (blank in CSV)	Not reviewed yet, or still needs a decision.
true	Coherent, faithful to the structured brief, and useful as a training example.
false	Contains contradictions, invented details, missing constraints, or another quality problem.

approval is the review decision. The older status column is retained for compatibility and does not need to be updated.

What to check

• Does user_text sound like a believable request and ask for the correct deliverable?
• Are product facts, pricing, audience, evidence, and prohibitions preserved without invented details?
• Does the awareness stage match the information provided? A blank awareness field is expected when the request does not name a stage.
• If completeness is needs_clarification, does the request preserve the unresolved choices instead of inventing answers? Missing information is intentional in some examples.

Tips

Use search to find a brand, deliverable, or phrase. Click a row and copy its URL to share that specific brief. The split is named train; this is a review queue and approval is still required before training.

Keep id and the column names unchanged. Only rows with approval set to true should be considered approved for training. Edits committed here update data/briefs.csv on Hugging Face; they do not automatically update the local CSV or JSONL. Republishing with --force replaces the remote CSV, including review edits.

Hugging Face editing instructions