workers-profiling

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Profile or debug CPU usage and memory allocation in deployed Cloudflare Workers and Durable Objects. Then use this information to optimize your code.

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Sourcecloudflare/skills
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NPX Install

npx skill4agent add cloudflare/skills workers-profiling

SKILL.md Content

Workers profiling

Find expensive functions or memory allocations in deployed code and come up with ways to fix them.

Retrieve the docs

Start with the production profiling guide to understand how Workers and Durable Objects profiling works.

Profiling steps

  1. Identify the symptom and affected workload: CPU usage, latency, allocation pressure, or memory growth.
  2. Confirm the account, Worker, environment, and deployed version with the user.
  3. For a Durable Object, also confirm its owning Worker, namespace, and instance.
  4. Choose CPU or heap profiling from the current guide's supported types and meanings.
Where possible, use the 
cf
CLI to capture profiles. If the user requests 
cf
, inspect the installed version's command help and schema where available.
If 
cf
isn't available, consider prompting the user whether they would like to install it.
The profiling API will return a pprof file which you can analyze directly, or using appropriate tools like Go's 
pprof
utility.

Inspect the evidence

  • Read the pprof file and analyse it for hotspots
  • Map hotspots to functions and source locations when evidence supports it; report missing symbols or source mappings.
  • If filenames and function names are pointing at the generated JavaScript, consider suggesting to the user to enable source maps and re-do the profiling.

Optimise

Propose the smallest code change supported by the capture which resolves the issues identified.

Report findings

Return a concise report with:
  • Evidence for each finding: file, function, source location, and metric with units, where available.
  • The smallest actionable change and how to check its effect.