Content
92%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.
An exemplary skill body: dense, executable guidance with a clear decision table, complete working examples for every approach, built-in validation and gotcha handling, and bulk reference material correctly externalized into two real one-level-deep reference files. The only improvement space is minor redundancy in the testing section.
Suggestions
In 'Test workspace tools', state the return_schema validation behavior once — the auto-checks bullet and the 'Add test_examples and return_schema' paragraph both explain that 'tu test' validates result["data"] against return_schema.
Consider trimming the duplicated search-example code between the workspace and plugin Python sections to just the key differences, since the 'Key differences' list already enumerates them.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is code-forward with essentially no explanation of concepts Claude already knows, but the testing section states the return_schema validation behavior twice (in the auto-checks list and again in the guidance below it), and the workspace-vs-plugin Python patterns overlap somewhat — minor trimmable redundancy that fits the 4 anchor rather than the lean 5 anchor. | 4 / 5 |
Actionability | Fully executable, copy-paste-ready examples throughout: complete JSON configs, complete Python classes for both workspace and plugin patterns, and concrete commands ('tu test MyAPI_search '{"q": "test"}'', 'pip install -e /path/to/my_project_root', 'tu info MyAPI_search') covering the common cases. | 5 / 5 |
Workflow Clarity | A decision table routes the user to one of three approaches, each path is sequenced create → test → verify with explicit validation checkpoints ('tu test' auto-checks, 'tu info' to confirm the tool loaded, manual urllib pre-verification of test_examples) and error-recovery guidance for the empty-results gotcha — matching the anchor requiring explicit validation and feedback loops. | 5 / 5 |
Progressive Disclosure | The body is a genuine overview with well-signaled, one-level-deep references — both [references/json-tool.md] and [references/python-tool.md] are real files (315 and 673 lines) that hold the bulk detail — so the split is appropriate and navigation is easy. | 5 / 5 |
Total | 19 / 20 Passed |