Content
35%Scale 1-5Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This skill reads more like a product specification or design document than an actionable skill for Claude. It describes what should happen at each step but rarely provides executable code, concrete algorithms, or specific implementation details. The safety principles section is well-structured and valuable, but the core analysis workflow lacks the specificity needed for Claude to actually perform the described tasks.
Suggestions
Replace the pseudocode risk calculation with executable Python code that reads from the specified JSON files and computes actual risk scores with defined inputs and outputs.
Add concrete validation steps with error handling: specify what to check after reading family-health-tracker.json, what constitutes invalid data, and how to handle missing or malformed entries.
Provide a complete working example showing input data structure from the JSON files and the expected output report format, rather than isolated fragments.
Remove or condense the trigger conditions and overview sections—Claude doesn't need to be told when to use the skill in this level of detail; focus tokens on implementation specifics.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill contains significant verbosity: explaining trigger conditions, listing obvious validation items (age reasonableness, data consistency), describing what a report contains at a high level without adding actionable detail. The overview section restates the description. Much of the content describes concepts rather than providing executable instructions. | 2 / 5 |
Actionability | The skill is mostly descriptive rather than executable. The risk calculation formula is pseudocode that isn't directly usable—it references undefined variables like '家族聚集度' without specifying how to compute them. The JSON example for recommendations is illustrative but not part of a working implementation. Steps like 'data validation' and 'genetic pattern recognition' are listed as bullet points without concrete implementation guidance. | 2 / 5 |
Workflow Clarity | There is a clear 8-step sequence, which provides reasonable structure. However, there are no validation checkpoints or feedback loops between steps. For a health analysis skill that generates reports and risk assessments, there should be validation after data reading (step 2/3) before proceeding to analysis, and verification of output correctness. The steps themselves are vaguely defined—e.g., 'data validation and cleaning' just lists three bullet points without specifying what to do when validation fails. | 3 / 5 |
Progressive Disclosure | The content is structured with clear sections and headers, which aids navigation. However, there are no bundle files or referenced external documents despite the skill being fairly long (~100 lines). The detailed report generation logic, ECharts configuration, and risk calculation algorithms could benefit from being split into separate reference files. Everything is inlined in a single document at a medium level of detail—not deep enough to be actionable, not concise enough to be an overview. | 3 / 5 |
Total | 10 / 20 Passed |