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.
84
81%
Does it follow best practices?
Impact
Pending
No eval scenarios have been run
Passed
No known issues
Quality
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 clearly communicates what the skill does (multi-platform ad account auditing with health scoring), which platforms it covers, and when to use it with natural trigger terms. It uses proper third-person voice, is concise without being vague, and has strong distinctiveness through its specific domain focus on paid advertising audits.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: multi-platform paid advertising audit, parallel subagent delegation, analyzes specific platforms (Google Ads, Meta Ads, LinkedIn Ads, TikTok Ads, Microsoft Ads), generates health scores per platform and aggregate score. | 3 / 3 |
Completeness | Clearly answers both 'what' (multi-platform paid advertising audit, analyzes specific ad platforms, generates health scores) and 'when' with an explicit 'Use when...' clause listing specific trigger phrases. | 3 / 3 |
Trigger Term Quality | Includes strong natural trigger terms users would actually say: 'audit', 'full ad check', 'analyze my ads', 'account health check', 'PPC audit'. Also names specific platforms (Google Ads, Meta Ads, etc.) which users would naturally mention. | 3 / 3 |
Distinctiveness Conflict Risk | Highly distinctive with a clear niche: multi-platform paid advertising audit with specific platform names and unique concepts like health scores and parallel subagent delegation. Unlikely to conflict with other skills. | 3 / 3 |
Total | 12 / 12 Passed |
Implementation
62%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 workflow for multi-platform ad auditing with good validation checkpoints and clear scoring methodology. Its main weaknesses are the lack of executable examples (no concrete subagent invocation syntax or API commands) and some verbosity in the report structure section that could be offloaded to a reference file. The scoring tables and priority definitions are appropriately concise and useful.
Suggestions
Add concrete subagent invocation examples showing exact syntax for delegating to audit-google, audit-meta, etc., including expected input/output formats.
Move the detailed Report Structure section to a separate reference file (e.g., `ads/references/report-template.md`) and link to it, keeping only a brief summary inline.
Add explicit links to the subagent skill files (e.g., `See [audit-google](ads/skills/audit-google.md)`) so navigation is clear and one-level deep.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is reasonably efficient but includes some sections that could be tightened—the report structure section is quite detailed and prescriptive about things Claude could infer (e.g., what an executive summary contains). The scoring weights table and process steps are appropriately dense, but the overall length could be reduced. | 2 / 3 |
Actionability | The skill provides a clear process and specific check IDs (G01-G74, M01-M46), scoring weights, and output file names, which is concrete. However, it lacks executable code/commands—there are no actual API calls, script invocations, or copy-paste-ready examples. The subagent delegation is described conceptually rather than with concrete invocation syntax. | 2 / 3 |
Workflow Clarity | The multi-step process is clearly sequenced with explicit validation checkpoints at steps 2 and 6 (validate data availability before proceeding, verify subagent scores before aggregating). The workflow includes a clear delegation pattern with fallback (subagents or inline sequential), and the priority/quick-wins criteria provide a feedback mechanism for output quality. | 3 / 3 |
Progressive Disclosure | There is one reference to an external file (`ads/references/scoring-system.md`) which is good, but the report structure section is quite lengthy and could be split into a separate reference file. The subagent references (audit-google, audit-meta, etc.) imply external skills but don't link to them explicitly. The content is reasonably organized with clear headers but borders on monolithic. | 2 / 3 |
Total | 9 / 12 Passed |
Validation
90%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 10 / 11 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
frontmatter_unknown_keys | Unknown frontmatter key(s) found; consider removing or moving to metadata | Warning |
Total | 10 / 11 Passed | |
- Repository
- AgriciDaniel/claude-ads
- Commit
402ba63
- Reviewed
Table of Contents
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