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From motion-creative
Deep-dive analysis of a specific creative asset. Use when the user asks about a specific ad by name, ID, or URL — "analyze this ad", "why is this working?", "why is this not working?", "break down this creative", "[pastes ad name]", "look at this ad", "what's the angle in this ad?", "compare to account averages", or references a specific creative by name or identifier. Handles creative lookup, disambiguation when multiple matches exist, entity hierarchy mapping (creative → ads → adsets → campaigns), and metric-appropriate analysis. This is the most common interaction pattern — users often analyze multiple ads in sequence. Always use this skill, not creative-strategist, when the user references a specific creative.
npx claudepluginhub motion-creative/motion-creative-plugin --plugin motion-creativeHow this skill is triggered — by the user, by Claude, or both
Slash command
/motion-creative:analyze-adopusThis skill is limited to the following tools:
The summary Claude sees in its skill listing — used to decide when to auto-load this skill
Deep-dive analysis of a specific creative — the most common customer interaction pattern. Users paste ad names one after another, going 20+ messages deep. Optimize for this multi-turn flow.
Core creative strategy reasoning methodology for the motion-creative plugin. This is a reference skill — it defines how to think about performance, competitive intelligence, and concept generation. Other skills read this for methodology. Only invoke directly when the user asks about the creative strategy framework itself or when no action skill matches. For specific tasks, route to: analyze-ad, performance-analysis, create-concepts, build-brief, write-hooks, find-iterations, industry-trends, qa-feedback, weekly-performance, etc.
Assesses ad creative fatigue risk across channels like Meta, Google, TikTok Ads. Scores fatigue, predicts decline, recommends refreshes, generates A/B test plans for underperformers.
Audits and optimizes multi-platform paid advertising across Google, Meta, YouTube, LinkedIn, TikTok, Microsoft, Apple, and Amazon with 250+ checks, scoring, and AI creative generation.
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Deep-dive analysis of a specific creative — the most common customer interaction pattern. Users paste ad names one after another, going 20+ messages deep. Optimize for this multi-turn flow.
Read ${CLAUDE_SKILL_DIR}/../creative-strategist/references/evaluation-framework.md for the 4-Question Evaluation Framework, metric pattern correlations, Ready/Iterate/Rethink call, and performance context awareness.
The user may reference a creative by:
adName in creative insights resultsadIds arraycreativeAssetIds filter parameterSteps:
get_creative_insights with SPEND insightType, limit 15. Include includeCreativeUrls: true so the user can see the creatives. Start with a smaller set — if the creative is active, it's likely in the top 15 by spend.
On the first pull, extract goalMetric and spendThreshold. If goalMetric.isCustomConversion is true, find the matching conversion in the customConversions array and include ["{id}_cost", "{id}_count"] in tableKPIs on this and all subsequent calls.adName).Multi-turn optimization: After the first pull, cache the creative list mentally. When the user asks about another ad in the same session, search the existing results first — don't re-pull unless the creative can't be found or the user changes the date range.
For the matched creative, present the full entity map:
creativeAssetId) — the visual/video itselfadIds, adName) — the ad-level entities using this creativeadsetIds, adsetName) — targeting and budget containerscampaignIds, campaignName) — objective and strategy levelIf a creative runs in multiple ads/adsets/campaigns:
Apply metric intelligence from ${CLAUDE_SKILL_DIR}/../creative-strategist/references/performance-metrics.md — select metrics by creative format (video vs. static) and campaign objective (awareness, traffic, conversions). When the campaign's optimization event differs from the workspace goalMetric, use the campaign-specific objective as the primary lens and note the difference.
Compare to account benchmarks: Pull withAggregatedInsights: true to get account-level averages. Present the creative's metrics as above/below/at benchmark.
Spend trajectory: Note if spend is increasing (scaling), declining (potentially fatiguing), or stable.
Apply performance context checks from evaluation-framework.md — funnel stage, budget starvation, account stage, and test fairness. Surface these factors when they change the interpretation of metrics.
Go beyond what the numbers say — explain WHY this creative performs the way it does.
For video creatives:
get_creative_transcript — this is the most valuable data for explaining performance.For static creatives:
get_creative_summary for AI-detected format and messaging.Glossary enrichment: Pull glossary tags via includeGlossary: true on the creative insights call (or get_glossary_values if needed). Surface taxonomy tags — Decision Stage, Human Desire, Messaging Theme, Headline Tactic, Intended Audience — to enrich the "why" analysis. These tags make the analysis reusable for concept generation and briefs.
Compare to account patterns:
If the creative is underperforming, diagnose using the 4-Question metric correlations from evaluation-framework.md:
Conclude every analysis with a clear Ready / Iterate / Rethink call from evaluation-framework.md:
Don't soften Rethink to avoid disagreement. Running a fundamentally broken creative wastes budget and teaches nothing.
Offer specific options based on what you found:
If the user has analyzed multiple ads in the session, offer: "You've analyzed [N] ads — want me to compare them or find patterns across what we've looked at?"
Creative not found: This happens frequently. Be helpful:
Multiple versions: When a creative runs in different campaigns with different names, show ALL versions with their respective performance. Don't collapse them — the user needs to see each context.
Zero spend creative: If found but has $0 spend, note it: "This creative exists but has no spend in this period — it may be paused, newly launched, or in a campaign that hasn't started spending."
Follow the creative-strategist Data Accuracy rules: