Content
87%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
The body is concise, actionable, and well-organized with real executable commands and a complete output schema, supported by a one-level-deep reference bundle. The main gap is the absence of an explicit validate-and-retry feedback loop in the workflow.
Suggestions
Add an explicit validation/feedback step (e.g., on malformed or PARTIAL data quality, inspect the offending thesis file, correct it, and re-run) to raise workflow clarity to the top anchor.
Document how a caller should react to each data_quality value (OK, PARTIAL, EMPTY_STATE) so the gate behavior after a degraded run is unambiguous.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is lean and structured with executable CLI commands, a config snippet, and a concrete output example, with no padding explaining concepts Claude already knows. | 3 / 3 |
Actionability | It provides fully executable `python3 ...` commands with real flags, a complete JSON config example, and a copy-paste-ready output schema, matching the executable-and-complete anchor. | 3 / 3 |
Workflow Clarity | A clear four-step sequence with graceful-degradation and data-quality checkpoints is present, but there is no explicit validate→fix→retry feedback loop, so it sits just below the top anchor. | 2 / 3 |
Progressive Disclosure | SKILL.md is an overview that points one level deep to a confirmed reference (references/circuit_breaker_framework.md) and script (scripts/check_circuit_breaker.py), both of which exist, keeping detail appropriately externalized. | 3 / 3 |
Total | 11 / 12 Passed |