ads-audit
Full multi-platform paid advertising audit with parallel subagent delegation. Analyzes Google Ads, Meta Ads, LinkedIn Ads, TikTok Ads, and Microsoft Ads accounts. Generates health score per platform and aggregate score. Use when user says "audit", "full ad check", "analyze my ads", "account health check", or "PPC audit".
90
Quality
86%
Does it follow best practices?
Impact
96%
2.82xAverage score across 3 eval scenarios
Discovery
100%Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.
This is an excellent skill description that hits all the marks. It clearly specifies what the skill does (multi-platform ad auditing with health scores), names the specific platforms supported, uses third person voice throughout, and provides explicit trigger terms that users would naturally say. The description is comprehensive yet concise.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: 'multi-platform paid advertising audit', 'parallel subagent delegation', 'Analyzes Google Ads, Meta Ads, LinkedIn Ads, TikTok Ads, and Microsoft Ads accounts', and 'Generates health score per platform and aggregate score'. | 3 / 3 |
Completeness | Clearly answers both what (multi-platform ad audit with health scores) AND when with explicit 'Use when user says...' clause containing specific trigger phrases. | 3 / 3 |
Trigger Term Quality | Excellent coverage of natural terms users would say: 'audit', 'full ad check', 'analyze my ads', 'account health check', 'PPC audit', plus platform names like 'Google Ads', 'Meta Ads', etc. | 3 / 3 |
Distinctiveness Conflict Risk | Very clear niche focused on paid advertising audits across specific platforms with distinct triggers like 'PPC audit' and 'account health check' - unlikely to conflict with other skills. | 3 / 3 |
Total | 12 / 12 Passed |
Implementation
72%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This skill provides a well-structured overview of a complex multi-platform audit process with excellent organization and token efficiency. However, it lacks concrete executable examples and explicit validation checkpoints for what is inherently a multi-step, error-prone workflow. The heavy reliance on external references is appropriate but the main skill could benefit from at least one concrete example of expected input/output.
Suggestions
Add explicit validation checkpoints between major steps (e.g., 'Confirm data received before proceeding to analysis', 'Verify subagent outputs before aggregating scores')
Include a concrete example of expected input data format and corresponding output snippet for at least one platform
Add error handling guidance for common failure modes (missing data, subagent unavailable, incomplete exports)
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is lean and efficient, using tables and structured lists without explaining concepts Claude already knows. Every section serves a purpose with no padding or unnecessary context about what ads platforms are. | 3 / 3 |
Actionability | Provides clear process steps and references to subagents and external files, but lacks executable code examples. The scoring formula and quick wins criteria use pseudocode rather than actual implementation, and relies heavily on external references without showing concrete examples. | 2 / 3 |
Workflow Clarity | The 6-step process is clearly sequenced, but lacks explicit validation checkpoints. There's no feedback loop for error recovery (e.g., what if data collection fails, what if subagent delegation fails). For a complex multi-platform audit, validation steps between stages would be expected. | 2 / 3 |
Progressive Disclosure | Excellent structure with clear overview, well-organized sections, and appropriate references to external files (scoring-system.md, subagent skills). Content is appropriately split between this overview and detailed materials, with clear navigation signals. | 3 / 3 |
Total | 10 / 12 Passed |
Validation
100%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 11 / 11 Passed
Validation for skill structure
No warnings or errors.
- Reviewed
Table of Contents
Is this your skill?
If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.