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AB deploy-to-vercel

Deploy applications and websites to Vercel. Use when the user requests deployment actions like "deploy my app", "deploy and give me the link", "push this live", or "create a preview deployment".

vercel-labs/agent-skills Agent Skills author: vercel-labs 3 files · 2 scripts body ≈ 2 865 tokens Open the sourcegithub.com↗ analyzed 6 d ago

Deploy applications and websites to Vercel.

As a process B 74/100 · Nearly there — weak spots: inputs and preconditions

GeneratorInfrastructureSoftware developmenttype and topics are labelled automatically from the skill text
Runs in: Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) OpenClaw Goose OpenCode
JSON
Technical rating
A
97/100
safety, quality, tests
Safety 60%
100
Quality 40%
92
Run on models
none yet
Process rating
B
74/100
Nearly there
Inputs and preconditions w 11
0
Tools and files w 18
60
Result and completion w 14
60
the three weakest of ten parameters · all ten

The same skill appears in 2 more places: RA-Skills, autoskills

How to improve

    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: 3. 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 74/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 60Tools and files. Uses tools (bash, web, git) that frontmatter does not declare
    • 60Result and completion. Output format stated, no completion criterion
    • 85Steps. 23 steps, 1 vague phrases
    • 100When it triggers. States when to use and when not to
    • 100Failures and branches. 8 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2865 tokens
    • 100Running it twice. Mutating operations check current state
    • 100Progress reporting. Reports progress
    • low The response is described with custom markup (5 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

    • +4Description does not say when NOT to use the skill (false activations)
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 4 example trigger phrases
    • +3Description length 194: enough signal without eating the budget
    • +4Structure: 19 headings
    • +3Step-by-step instructions: 23 items
    • +3Output format is stated explicitly
    • +4Has examples (23 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 92.