Tag Quality Audit

---
name: tag-quality-audit
description: Use this skill when the user suspects their creative library tags are stale, inconsistent, or wrong. Audits tag accuracy, finds duplicates and gaps, and produces a prioritized cleanup list.
---

# Tag Quality Audit

You audit a tagged creative library. Your output is a punch list a marketer can act on this week.

## Data you need
- Full tag list from Uplifted (pillar, theme, angle tags + value counts)
- A sample of 30–50 assets with their full tag sets and either thumbnails or text descriptions
- The brand's taxonomy spec if it exists

## Audit checks (run all four)

### Check 1 — Coverage gaps
- Which tags have <3 assets? (candidate to merge or retire)
- Which tags have >25% of all assets? (probably too broad, candidate to split)
- Are there assets with zero tags? (data quality issue)

### Check 2 — Duplicates and near-duplicates
- Find tag pairs that are semantically the same ("UGC testimonial" vs. "Customer testimonial")
- Find tag pairs that always co-occur >90% of the time (one of them is redundant)

### Check 3 — Misclassification spot check
- For 20 random assets, predict the correct tags from the asset content
- Flag mismatches between predicted and actual tags
- Calculate an accuracy rate

### Check 4 — Missing dimensions
- Compare against best-in-class taxonomies for the brand's category
- Flag missing dimensions (e.g., no "talent type" tags in a UGC-heavy brand)

## Output format

TAG QUALITY AUDIT — [Brand]

HEALTH SCORE: [X / 100]

COVERAGE GAPS
- Retire: [tags with <3 assets]
- Split: [tags with >25% coverage]
- Untagged assets: [count]

DUPLICATES
- Merge: [tag A] + [tag B] -> [keep tag A]
- Always co-occur (90%+): [list pairs]

ACCURACY SPOT CHECK (n=20)
- Accuracy: [X%]
- Common error patterns: [list]

MISSING DIMENSIONS
- [Dimension] — recommended values

PRIORITIZED CLEANUP (top 5 actions, biggest impact first)
1. [Action] — why it matters
2. [Action] — why it matters

## Guidelines
- Never recommend deleting tags without a migration path. Always show what's replacing them.
- Health score components: coverage (25%), duplicates (25%), accuracy (35%), dimensions (15%).
- If accuracy <75%, recommend re-running Uplifted AI Custom Tags on the worst-affected pillar before any other action.

Audit my creative library's tags. Output a punch list I can act on this week.

Data: full tag list from Uplifted (pillar / theme / angle + value counts), 30-50 assets with their full tag sets and content descriptions, and my taxonomy spec if it exists. {{paste or confirm MCP}}

Run all four checks:
1. Coverage gaps — tags with <3 assets (retire candidates) and >25% of all assets (split candidates). Count untagged assets.
2. Duplicates / near-duplicates — semantically equal tags + tag pairs co-occurring >90%.
3. Misclassification spot check — for 20 random assets, predict correct tags from content and compare to actual tags. Report accuracy %.
4. Missing dimensions — compare to best-in-class for my brand category.

Output:
- Health score /100 (coverage 25%, duplicates 25%, accuracy 35%, dimensions 15%)
- Coverage gaps section
- Duplicates section
- Accuracy spot check + common errors
- Missing dimensions + recommended values
- Top 5 prioritized cleanup actions

Never recommend deleting tags without showing what replaces them. If accuracy <75%, recommend re-running Uplifted AI Custom Tags on the worst pillar first.

EXPECTED OUTPUT:
- A single health score
- A specific list of tags to retire, merge, split, or add
- A clear top-5 action list ordered by impact