Content
63%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 body is well-structured and actionable with executable commands and a full schema, but it suffers from input duplication and an inlined reference schema that hurts conciseness and progressive disclosure. Consolidating the input descriptions and moving the schema to a reference file would improve the score.
Suggestions
Merge the '## Inputs' prose and '## Input' table into a single section to remove duplication.
Move the full Input JSON Schema (including the AIGD.GameObjectRef $defs) into a references/ file and link to it from the body.
Replace the placeholder example values ('width': 0, 'height': 0) with realistic valid values that satisfy the stated constraints.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The Behavior section is lean, but the inputs are described twice (## Inputs prose and ## Input table) and the full GameObjectRef JSON schema is inlined, adding tokens that could be trimmed. | 3 / 5 |
Actionability | Provides copy-paste-ready bash commands (run-tool, --input-file, stdin) and a complete JSON schema, but the example uses placeholder values ('width': 0) that violate the stated >0 constraint. | 4 / 5 |
Workflow Clarity | As a simple single-action tool the action is unambiguous and the Behavior section sequences the internal steps clearly; minor gap is the lack of an explicit validation/verification checkpoint on the returned image. | 4 / 5 |
Progressive Disclosure | Sections are organized, but no bundle files exist and the large input JSON schema (with $defs) is inlined in SKILL.md rather than placed in a one-level-deep reference file. | 3 / 5 |
Total | 14 / 20 Passed |