CC deploy-prototype
Generate a small app or tool and deploy it live to Vercel via API
Generate a small app or tool and deploy it live to Vercel via API
As a process C 55/100 · Has gaps — weak spots: result and completion, inputs and preconditions
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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 · 2
✓ No critical or high findings
Medium and low: 2
-
low Exfiltration
net-credential-useSKILL.md:150Credential used in a network call (verify the destination is the intended service) (quoted — discussed, not commanded)Otherwise POST the inline deployment built in step 6. Write the key as the literal `{VERCEL_TOKEN}` placeholder so `./secretcurl` substitutes it internally — a bare `$VERCEL_TOKEN` on the command linequoted -
low Exfiltration
net-credential-useSKILL.md:214Credential used in a network call (verify the destination is the intended service) (quoted — discussed, not commanded)Steps 1–7 are local — file writes and notify only. Step 8's deploy is the one outbound side-effect and it runs **in-run**: the Vercel deployment via `./secretcurl` with the `{VERCEL_TOKEN}` placeholdequoted
Files scanned: 1. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-no-whendescription does not say WHEN to use the skill (no "use when")
Process rating: all ten parameters 55/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 50When it triggers. No condition that starts the skill
- 50Failures and branches. 0 branches, has a failure section
- 60Tools and files. Uses tools (bash, web) that frontmatter does not declare
- 85Steps. 54 steps, 2 vague phrases
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 3512 tokens
- 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
- high The skill tells the model to perform an irreversible action with no human approval
- low The response is described with custom markup (19 tags): a typed call is more reliable
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 65: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- -5TODO / placeholder text left in the skill
- +1No license
- +2Single-language instructions
- +4Structure: 4 headings
- +3Step-by-step instructions: 54 items
- +4Has examples (8 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 64.