AB volcengine-prepare
Use when the user wants to deploy a local directory or GitHub repository to Volcengine and needs the project analyzed, the app shape understood, and a ranked recommendation across ECS, VKE, and veFaaS before choosing an execution path. Also trigger when the user asks "what deploy mode should I use", "is this repo ready for Volcengine", or "check my repo before deploying". This skill prepares the decision; `volcengine-deploy` skill performs the chosen deployment, and `volcengine-iac` skill is used only when the user chooses Terraform/IaC or the task already has an IaC workflow.
Use when the user wants to deploy a local directory or GitHub repository to Volcengine and needs the project analyzed, the app shape understood, and a ranked…
As a process B 71/100 · Nearly there — weak spots: result and completion, 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: 5. 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 71/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 70When it triggers. States when to use, but not when not to
- 100Tools and files. No external tools needed
- 100Steps. 25 steps
- 100Failures and branches. 8 branches, has a failure section
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 3013 tokens
- 100Running it twice. Mutating operations check current state
- 100Progress reporting. Reports progress
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
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- +2Single-language instructions
- +5Description quotes 3 example trigger phrases
- +3Description length 583: enough signal without eating the budget
- +4Structure: 8 headings
- +3Step-by-step instructions: 25 items
- +4Has examples (12 code blocks)
- +4Reference files are cited in the instructions (1 of 1)
- +3All 2 scripts are documented
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 97.