analyzing-marketing-campaign

Analyze weekly marketing campaign performance data across channels. Use when analyzing multi-channel digital marketing data to calculate funnel metrics (CTR, CVR) and compare to benchmarks, compute cost and revenue efficiency metrics (ROAS, CPA, Net Profit), or get budget reallocation recommendations based on performance rules.

Quality

100%

Does it follow best practices?

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Securityby

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Quality

Content

100%Weight 40%Scale 1-3

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The body is concise, concrete, and well-structured, with exact formulas, explicit defaults, clear sequencing, and a single well-signaled reference file. It assumes Claude's competence while providing everything needed to execute the analysis correctly.

Dimension	Reasoning	Score
Conciseness	The body is lean and reference-style — column lists, terse formulas, benchmark tables, and status rules — with no padding explaining concepts Claude already knows, matching the score-3 anchor where every token earns its place.	3 / 3
Actionability	Provides fully actionable guidance: exact formulas (CTR = clicks / impressions × 100), concrete defaults (Shipping Cost $8/order, Product Cost 35%, Target ROAS 4.0x, Max CPA $50), and explicit status-indicator rules, matching the score-3 anchor for copy-paste-ready instruction.	3 / 3
Workflow Clarity	A clear sequence (Data Quality Check → Funnel Analysis → Efficiency Analysis → Output Format → Budget Reallocation) with explicit validation checks ('Flag anomalies', 'Verify no negative values'); this single-purpose analysis skill is unambiguous, matching the score-3 anchor.	3 / 3
Progressive Disclosure	Core analysis stays inline while the heavy ruleset is split into a single, clearly signaled one-level-deep reference ('read references/budget_reallocation_rules.md'), which is a real verified file, matching the score-3 anchor.	3 / 3
	Total	12 / 12 Passed

Description

100%Weight 40%Scale 1-3

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

The description is specific, well-triggered, and complete, clearly communicating both what the skill does and when to use it. It lists concrete actions with named metrics and natural trigger terms, with minimal risk of conflict with other skills.

Dimension	Reasoning	Score
Specificity	Lists multiple concrete actions — 'calculate funnel metrics (CTR, CVR)', 'compute cost and revenue efficiency metrics (ROAS, CPA, Net Profit)', 'get budget reallocation recommendations' — matching the score-3 anchor for listing several specific actions.	3 / 3
Completeness	Explicitly answers both 'what' (Analyze weekly marketing campaign performance data, calculate funnel/efficiency metrics) and 'when' (explicit 'Use when' trigger listing multiple trigger scenarios), satisfying the score-3 anchor for both what AND when.	3 / 3
Trigger Term Quality	Includes a natural 'Use when analyzing multi-channel digital marketing data to calculate funnel metrics' clause with good coverage of terms users would say (marketing campaign performance, funnel metrics, benchmarks, budget reallocation), matching the score-3 anchor.	3 / 3
Distinctiveness Conflict Risk	Targets a clear niche (multi-channel marketing funnel and efficiency analysis) with distinct, metric-specific triggers unlikely to fire for unrelated skills, matching the score-3 anchor.	3 / 3
	Total	12 / 12 Passed

Validation

100%

Warnings & errors only

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository: https-deeplearning-ai/sc-agent-skills-files
Path: L1-partI/skill/analyzing-marketing-campaign/SKILL.md
Commit: 438a5a5

Reviewed: 12 days ago

Table of Contents

Discovery Implementation Validation

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