Content
63%Weight 40%Scale 1-5Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
The content is a rich, highly actionable reference for retargeting design with concrete numbers, platform-specific steps, and good worked examples. Its main weaknesses are duplication (budget guidance repeated three times, a promotional footer) and total absence of progressive disclosure — 300+ lines of tables and examples are inlined with no references/ bundle.
Suggestions
Move the five benchmark tables (audience window CVR, frequency caps, budget allocation, DCO elements, platform capabilities) and the three worked examples into references/ files (e.g., references/benchmarks.md, references/examples.md), keeping SKILL.md as a concise overview with clearly signaled one-level-deep links.
Cut duplication and non-task content: remove the promotional 'About this skill' footer, drop the Capabilities section that restates the frontmatter description, and state the budget allocation once instead of in Workflow 2, the reference table, and every example.
Add explicit validation checkpoints to the workflows, e.g., a step verifying each audience exceeds the platform minimum sizes (100/300/1,000) before budget allocation, and a post-launch monitoring step like the frequency thresholds already shown in Example 3.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Most content is dense domain data Claude would not know (bid modifiers, frequency caps, CVR benchmarks), but there is real fat: the Capabilities section and intro repeat the frontmatter description, budget-allocation guidance appears three times (Workflow 2, its own table, and again inside every example), and the ~10-line promotional "About this skill" footer earns nothing for the task. This is 'mostly efficient but could be tightened', not the severely padded anchor 2. | 3 / 5 |
Actionability | For an instruction-only skill the guidance is highly concrete: exact day windows, budget percentages, frequency caps per platform, platform-specific exclusion steps ("Google: Audience Manager → create suppression list", "Meta: Custom Audience → exclude from ad set"), and three complete worked funnels covering e-commerce, B2B SaaS, and frequency management. It falls short of anchor 5 only through minor gaps like "Allocate by platform based on where audience spends time" and "Use email-based matching" with no how; it is clearly above anchor 3, which would require pseudocode-level vagueness. | 4 / 5 |
Workflow Clarity | The five workflows are clearly sequenced with numbered steps and concrete values, and Example 3 includes a genuine feedback loop ("If >8: reduce budgets or tighten audience windows; If <3: may be under-serving"), while the platform table surfaces minimum-audience-size checkpoints. It misses anchor 5 because most design workflows lack explicit validation checkpoints (e.g., no step to verify audience sizes against platform minimums before launch); this is a design skill, not a destructive/batch operation, so the cap-at-3 rule does not apply. | 4 / 5 |
Progressive Disclosure | The body is well-sectioned with clear headers (above anchor 2's 'minimal structure'), but it is a single ~310-line monolith with no bundle files at all — the five large benchmark tables and three full worked examples clearly belong in references/ files, matching anchor 3's 'content that should be separate is inline'. It cannot score higher because nothing is split out and there are no references to signal. | 3 / 5 |
Total | 14 / 20 Passed |