CC auto-model-selector
(no description)
As a process C 51/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- Add a description to the frontmatter: without it the skill never triggers.
For the model run — optional
- Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
- A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.
Guard findings · 0
✓ No critical or high findings
Files scanned: 10. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- error
description-missingSKILL.md: no `description` — the skill can never trigger - warning
frontmatter-yamlSKILL.md: the frontmatter is not valid YAML (YAML parse error: Implicit keys need to be on a single line at line 2, column 1: name: auto-model-selector 根据用户问题的复杂度自动选择合适的AI模型进行处理。使用本地模型处理简单任务，云端模型处理复杂任务。 ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value
Process rating: all ten parameters 51/100
- 0Result and completion. Does not say what the result is
- 0When it triggers. No condition that starts the skill
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Failures and branches. Linear process with no failure handling
- 0Progress reporting. Says nothing while it works
- 100Tools and files. No external tools needed
- 100Steps. 25 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 157 tokens
- 100Running it twice. No mutating operations
Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.
Quality signals
- +5Description has no quoted example phrases that should trigger the skill
- +4Description does not say when NOT to use the skill (false activations)
- +3Description length 0: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +4Structure: 11 headings
- +3Step-by-step instructions: 25 items
- +4Has examples (1 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 26.
External checks
ClawHub: suspicious
The skill mostly matches its model-routing purpose, but it needs review because it can automatically send prompts to a hard-coded private-network Ollama server and route work to cloud models without clear user control.
LLM: suspicious (high) · VirusTotal: · 29 May 2026