Content
76%Weight 40%Scale 1-5Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
The SKILL.md body is highly actionable with executable commands, a complete JSON schema, and clear structure, but its workflow for destructive order placement lacks an explicit validation feedback loop, and some inline reference material could be split out.
Suggestions
Add an explicit validate-then-execute checkpoint: instruct Claude to run a dry-run first, review the alert/position output with the user, and only then re-run with --execute.
Move the detailed JSON output schema and/or the Architecture function inventory into a reference file under references/ to keep SKILL.md a lean overview.
Trim the opening restatement of the description and condense the JSON example to the essential fields.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is efficient and assumes Claude's competence (no basic-concept padding), with only minor trimming opportunities such as the long inline JSON output schema and the opening line that restates the description. | 4 / 5 |
Actionability | Provides copy-paste-ready commands with flag variants, a full arguments table, a complete JSON output schema, explicit order-ID naming conventions, and named architecture functions — fully executable guidance covering the common cases. | 5 / 5 |
Workflow Clarity | Steps are sequenced (run script, format report, report to user) and dry-run is the safe default, but for destructive/batch operations (placing/cancelling real orders) there is no explicit validate-then-execute feedback loop, which caps workflow clarity at 3. | 3 / 5 |
Progressive Disclosure | Well-organized into clear sections with the single bundle file (scripts/stop_loss.py) correctly referenced and no nested references; minor organization gaps since the JSON schema and architecture sections are inlined rather than split out. | 4 / 5 |
Total | 16 / 20 Passed |