Content
85%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.
Highly actionable, well-sequenced content with a rigorous preflight workflow and a clean one-level-deep bundle split. The main cost is token efficiency: the createModel legal-values rules and the 'never assume enabled' warning are each restated in three to four places, which could be consolidated into one canonical section without losing the guardrail effect.
Suggestions
Consolidate the four-legal-values rule for createModel into one canonical section (the STOP table) and reduce the 'Available Providers and Models' and Best Practice #3 repetitions to one-line cross-references.
State the 'never assume a model is enabled' rule once in preflight ② and reference it from the STOP table, Providers section, and Best Practice #2 instead of restating the full DescribeAIModels/DescribeManagedAIModelList/UpdateAIModel procedure in each place.
Consider moving the provider roster detail in 'Available Providers and Models' (per-vendor model lists, resource-point quota behavior) into a reference file, keeping only the routing decision (which group to use) in SKILL.md.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | No filler or explanations of concepts Claude already knows, but core guardrails are repeated verbatim across sections: the four legal createModel values appear in the STOP section, again in 'Available Providers and Models', and again in Best Practice #3, while 'never assume a model is enabled' appears in four places. Consolidating these would cut substantial tokens, so the body is mostly efficient but could be tightened rather than merely having minor trim spots. | 3 / 5 |
Actionability | Fully executable throughout: exact MCP tool calls with parameters (e.g. callCloudApi(service="tcb", action="DescribeAIModels", params={ EnvId })), explicit pass conditions, a ready-to-send user-facing failure message with the purchase URL, a complete UpdateAIModel payload, install/init code, and concrete timeout ranges per operation type. | 5 / 5 |
Workflow Clarity | The two-step preflight is a clearly sequenced workflow with explicit validation checkpoints and feedback loops — pass/fail branches for the resource-pack check, 'Do not write createModel("cloudbase") yet' gates, a numbered 5-step decision procedure, and a re-check loop after the user purchases — and Best Practice #13 adds self-verification before claiming done. | 5 / 5 |
Progressive Disclosure | The body keeps the always-needed routing and preflight logic inline and appropriately splits bulk material into references/api-reference.md (full API examples and types) and references/custom-onboarding.md (onboarding flow) — both real files, clearly signaled, one level deep with no nested references, and indexed in a closing Reference index. | 5 / 5 |
Total | 18 / 20 Passed |