Content
57%Scale 1-3Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
The skill is well-structured and concise with good progressive disclosure to external resources. However, it severely lacks actionability - the instructions read as a high-level checklist rather than executable guidance. Without concrete code examples, specific commands, or detailed implementation patterns in the main skill file, Claude would struggle to actually implement a backtesting system.
Suggestions
Add at least one concrete, executable code example showing a minimal backtesting loop structure (e.g., event-driven simulation skeleton)
Include specific validation checkpoints in the workflow, such as 'Verify no lookahead bias by checking data timestamps before each signal'
Provide concrete examples of what 'realistic cost models' and 'point-in-time data pipelines' look like in practice, even if brief
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is lean and efficient, avoiding unnecessary explanations of concepts Claude already knows. Each bullet point earns its place without padding or verbose context. | 3 / 3 |
Actionability | The instructions are vague and abstract with no concrete code, commands, or executable examples. Phrases like 'Build point-in-time data pipelines' and 'Implement event-driven simulation' describe rather than instruct. | 1 / 3 |
Workflow Clarity | Steps are listed in a logical sequence but lack validation checkpoints, feedback loops, or specific criteria for when to proceed. No guidance on how to verify each step was completed correctly. | 2 / 3 |
Progressive Disclosure | Clear overview structure with well-signaled one-level-deep reference to the implementation playbook. Content is appropriately split between overview and detailed resources. | 3 / 3 |
Total | 9 / 12 Passed |