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 well-crafted skill description that clearly states what the skill does (social media campaign analysis, engagement rate calculation, ROI measurement, benchmarking) and when to use it with an explicit 'Use for...' clause containing natural trigger terms. It uses proper third-person voice throughout and provides enough specificity to distinguish it from general analytics or reporting 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' (calculates engagement rates, ROI, benchmarks across platforms) 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 | The description carves out a clear niche around social media campaign analysis with distinct triggers like 'engagement rate', 'campaign ROI', 'platform metrics', and 'benchmarking against industry standards', making it 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 reference skill with clear workflows, good benchmark data, and appropriate progressive disclosure. Its main weaknesses are moderate verbosity (some sections like engagement value estimates and the generic 'Communication' section could be trimmed) and limited actionability since the referenced scripts aren't shown and formulas are plain text rather than executable code. The workflow clarity and organization are strong points.
Suggestions
Remove or significantly trim the generic 'Communication' and 'Output Artifacts' sections which add boilerplate without skill-specific value.
Provide a minimal executable code snippet showing how to calculate engagement rate programmatically, rather than relying solely on formula notation and external scripts that may not exist.
| 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, interpretation tables, and proactive triggers add bulk. The 'Communication' section with generic quality verification language and the 'Output Artifacts' table feel like boilerplate rather than actionable content specific to this skill. | 2 / 3 |
Actionability | The skill provides concrete formulas, benchmark tables, and sample input/output JSON which is helpful. However, the actual tool commands reference scripts (calculate_metrics.py, analyze_performance.py) without showing their implementation or confirming they exist. The formulas are presented as plain text rather than executable code. The guidance is more of a reference framework than copy-paste executable instructions. | 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 progressing from workflow to metrics to ROI to benchmarks, and appropriately references external files (references/platform-benchmarks.md, assets/sample_input.json, assets/expected_output.json) at one level deep. Related skills are listed at the bottom for cross-referencing. | 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
f567c61
- Reviewed
Table of Contents
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