AC Smart Router
Intelligent multi-model router — automatically selects the best AI model based on task type (vision, image generation, video generation, audio, reasoning, code, general chat) via any OpenAI-compatible API endpoint. Supports 35+ models across 7 categories with @alias shortcuts. Use when: user sends an image for analysis, requests image/video/audio generation, needs deep reasoning or math proofs, wants to use a specific model, or prefixes message with @alias (e.g. @gpt52, @o3, @sora, @imagen).
As a process C 56/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- 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: 6. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
name-formatname should be kebab-case (lowercase letters, digits, hyphens) - note
frontmatter-keyunknown frontmatter key "read_when"
Process rating: all ten parameters 56/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 3 mutating operations with no state check
- 40Consistency. Frontmatter name (Smart Router) differs from the folder (smart-models)
- 100Tools and files. Tools declared in frontmatter
- 100Steps. 20 steps
- 100Failures and branches. 4 branches, has a failure section
- 100Execution cost. Instruction body is 1330 tokens
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)
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +3Description length 496: enough signal without eating the budget
- +4Structure: 17 headings
- +3Step-by-step instructions: 20 items
- +4Has examples (6 code blocks)
- +3All 2 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 81.