AC tokenrouter-video-usaging
Guide the agent to perform tokenrouter channel and model configuration checks for video generation tasks. First, check whether the workspace already has a tokenrouter channel whose baseurl contains `https://api.tokenrouter.com` or `https://open.palebluedot.ai`. If no such channel exists, stop and instruct the user to visit `https://www.tokenrouter.com` to register and obtain tokenrouter configuration. If the channel exists, then check whether the requested video model (`MiniMax-Hailuo-2.3`, `kling-v3`, `kling-v2-6`, `dreamina-seedance-2-0-fast-260128`, or `dreamina-seedance-2-0-260128`) is already configured in the channel. If the model is missing, the agent should auto-configure the model route by inferring the existing schema and adding the smallest correct change. After confirming both the channel and the model are ready, use the configured route to create and query video generation tasks.
As a process C 52/100 · 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: 4. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
✓ No remarks against the Agent Skills spec
Process rating: all ten parameters 52/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 20When it triggers. No condition that starts the skill
- 40Consistency. Frontmatter name (tokenrouter-video-usaging) differs from the folder (tokenrouter-generate-video)
- 60Tools and files. Uses tools (bash, web) that frontmatter does not declare
- 70Execution cost. Instruction body is 4474 tokens
- 100Steps. 90 steps
- 100Failures and branches. 18 branches, has a failure section
- 100Running it twice. Mutating operations check current state
- 100Progress reporting. Reports progress
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
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 905: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +4Structure: 18 headings
- +3Step-by-step instructions: 90 items
- +4Has examples (16 code blocks)
- +4Reference files are cited in the instructions (1 of 1)
- +3All 1 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 88.