social-media-analyzer
Social media campaign analysis and performance tracking. Calculates engagement rates, ROI, and benchmarks across platforms. Use for analyzing social media performance, calculating engagement rate, measuring campaign ROI, comparing platform metrics, or benchmarking against industry standards.
95
85%
Does it follow best practices?
Impact
98%
1.44xAverage score across 9 eval scenarios
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 a strong skill description that clearly articulates specific capabilities (engagement rates, ROI, benchmarking), uses natural trigger terms users would employ, and includes an explicit 'Use for...' clause covering multiple relevant scenarios. It is well-scoped to social media campaign analysis, making it distinctive and unlikely to conflict with other skills.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: 'Calculates engagement rates, ROI, and benchmarks across platforms' along with 'analyzing social media performance, calculating engagement rate, measuring campaign ROI, comparing platform metrics, benchmarking against industry standards.' | 3 / 3 |
Completeness | Clearly answers both 'what' (social media campaign analysis, calculates engagement rates, ROI, benchmarks) and 'when' with an explicit 'Use for...' clause listing specific trigger scenarios like analyzing performance, calculating engagement rate, measuring ROI, comparing metrics, and benchmarking. | 3 / 3 |
Trigger Term Quality | Includes strong natural keywords users would say: 'social media performance', 'engagement rate', 'campaign ROI', 'platform metrics', 'benchmarking', 'industry standards'. These cover a good range of terms a user would naturally use when requesting this type of analysis. | 3 / 3 |
Distinctiveness Conflict Risk | Clearly scoped to social media campaign analysis with distinct triggers like 'engagement rate', 'campaign ROI', 'platform metrics', and 'benchmarking against industry standards'. This is a well-defined niche unlikely to conflict with general analytics or other marketing skills. | 3 / 3 |
Total | 12 / 12 Passed |
Implementation
70%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This is a well-structured skill with clear workflows, good benchmark reference tables, and appropriate progressive disclosure to external files. Its main weaknesses are moderate verbosity (several sections like Communication, Output Artifacts, and Proactive Triggers add limited value) and the lack of executable code for the core analysis logic—the skill references scripts but doesn't show their implementation, and formulas are plain text rather than runnable code.
Suggestions
Include the core calculation logic as executable Python code (at least the engagement rate and ROI calculations) rather than only referencing external scripts that aren't shown.
Trim or remove the 'Communication', 'Output Artifacts', and 'Proactive Triggers' sections—these describe general assistant behavior rather than providing actionable skill-specific guidance.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill contains useful reference tables but is quite lengthy with some sections that could be trimmed. The 'Engagement Value Estimates' rationale column, the 'Proactive Triggers' section, 'Output Artifacts' table, and 'Communication' section add bulk without proportional value. The interpretation section at the end restates what the numbers already show. | 2 / 3 |
Actionability | The skill provides concrete formulas, benchmark tables, and sample input/output JSON which are useful. However, the actual executable code is limited to CLI invocations of scripts (calculate_metrics.py, analyze_performance.py) whose contents are not shown, making it impossible to verify or execute the core logic. The formulas are presented as plain text rather than executable code. | 2 / 3 |
Workflow Clarity | The analysis workflow is clearly sequenced with 8 numbered steps including an explicit validation checkpoint at step 8. Data validation checks are provided as a checklist before analysis begins. The ROI calculation section also includes a validation step. Error conditions like division by zero are explicitly called out. | 3 / 3 |
Progressive Disclosure | The skill has a clear table of contents, well-organized sections, and appropriately references external files (references/platform-benchmarks.md, assets/sample_input.json, assets/expected_output.json, scripts/) for detailed content. References are one level deep and clearly signaled. Related skills are listed at the bottom for cross-navigation. | 3 / 3 |
Total | 10 / 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
- alirezarezvani/claude-skills
- Commit
a96cc20
- Reviewed
Table of Contents
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