Content
57%Weight 40%Scale 1-3Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
The content is well-organized with good progressive disclosure and concrete examples, but it bloats with concept explanations and lacks explicit validation checkpoints in its multi-step workflow.
Suggestions
Remove textbook explanations Claude already knows (e.g., the bearish/bullish meaning of put/call ratios) to tighten token efficiency.
Add explicit validation checkpoints between pipeline steps (e.g., verify credentials loaded, confirm API response, sanity-check OI totals before analyzing) to lift workflow clarity.
Either inline a minimal executable snippet for options_flow.py or clearly point to where its interface is defined, so the numbered steps are copy-paste ready rather than descriptive.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is mostly efficient and well-structured, but it explains concepts Claude already knows (e.g., defining that a put/call ratio above 1.0 is bearish) and the prerequisites and error table include some padding that could be trimmed. | 2 / 3 |
Actionability | It gives concrete CLI examples and clear command flags, but the numbered instructions reference a script (options_flow.py) and tool invocations whose exact behavior is not shown inline, leaving some steps at the describe-rather-than-instruct level. | 2 / 3 |
Workflow Clarity | The ten steps are clearly sequenced and an error-handling table exists, but there are no explicit validation/verification checkpoints between steps for a multi-step data pipeline, which caps the score at 2. | 2 / 3 |
Progressive Disclosure | The body is a concise overview with a clearly signaled one-level-deep reference ("See ${CLAUDE_SKILL_DIR}/references/implementation.md") and real bundle files (errors.md, examples.md, implementation.md) in ./references/, so navigation is well organized. | 3 / 3 |
Total | 9 / 12 Passed |