SKILLEMALL.ai

AC vercel-to-cloudflare

Migrate Next.js projects from Vercel to Cloudflare Workers with Supabase/Hyperdrive support. Use when user wants to move a Next.js app off Vercel to reduce costs, deploy to Cloudflare Workers, configure Hyperdrive connection pooling, or fix Supabase connectivity issues on Cloudflare. Triggers on phrases like "migrate to Cloudflare", "Vercel too expensive", "deploy Next.js on Cloudflare Worker", "Cloudflare Hyperdrive setup", "Supabase on Cloudflare", "从Vercel迁移到Cloudflare", "Vercel太贵了", "部署到Cloudflare Worker".

modbender/skill-library-mcp Agent Skills author: modbender MIT 4 files body ≈ 869 tokens Open the sourcegithub.com analyzed 2 d ago

Migrate Next.js projects from Vercel to Cloudflare Workers with Supabase/Hyperdrive support. Use when user wants to move a Next.js app off Vercel to reduce…

As a process C 57/100 · Has gaps — weak spots: result and completion, inputs and preconditions, failures and branches

ProcedureCloudflareSupabasePostgreSQLInfrastructureSoftware developmenttype and topics are labelled automatically from the skill text
JSON
Technical rating
A
98/100
safety, quality, tests
Safety 60%
100
Quality 40%
96
Run on models
none yet
Process rating
C
57/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
the three weakest of ten parameters · all ten

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: 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 57/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 70When it triggers. States when to use, but not when not to
    • 85Steps. 10 steps, 2 vague phrases
    • 100Tools and files. No external tools needed
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 869 tokens
    • 100Running it twice. No mutating operations

    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
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 8 example trigger phrases
    • +3Description length 515: enough signal without eating the budget
    • +4Structure: 9 headings
    • +3Step-by-step instructions: 10 items
    • +4Has examples (6 code blocks)
    • +4Reference files are cited in the instructions (2 of 2)
    • +3All 1 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 96.