Content
86%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.
A thorough, highly actionable spec for a multi-agent generation skill, with copy-paste commands, explicit validation, and clean one-level references. The main weakness is mild redundancy that could be trimmed for token efficiency.
Suggestions
Remove the duplicated aspect-ratio allow-list in Main Agent Workflow step 3 by referencing the Input Specification table instead.
Consolidate the two-tier architecture description so it is stated once rather than repeated across the Architecture and Workflow sections.
Consider adding an explicit retry/recovery step for transient sn-text-optimize or sn-image-generate failures if auto-recovery is intended.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is mostly efficient and avoids explaining concepts Claude already knows, but repeats content such as the aspect-ratio allow-list (in Input Spec and again in Main Agent Workflow step 3) and restates the two-tier architecture, fitting anchor 4 rather than 5. | 4 / 5 |
Actionability | Provides copy-paste-ready executable commands (concrete `sn_agent_runner.py` invocations with explicit flags), exact temp-directory paths, and a precise JSON return contract covering the common cases, matching anchor 5. | 5 / 5 |
Workflow Clarity | Sequences the Main and Worker steps clearly with explicit validation (non-empty resume_content, aspect-ratio allow-list, non-zero exit / invalid-JSON checks) and error reporting, but errors 'stop and report' rather than retry, fitting anchor 4 rather than 5. | 4 / 5 |
Progressive Disclosure | Uses well-signaled one-level-deep references (prompts/resume.md, ../sn-image-base/references/api_spec.md) with clean section navigation and appropriately split content, matching anchor 5. | 5 / 5 |
Total | 18 / 20 Passed |