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Show HN: profiler-md converts performance profiles to Markdown

Hi HN! profiler-md is a CLI and JS library that converts performance profiles to Markdown across 17 formats (e.g. pprof), 29 profilers (e.g. py-spy), 22 languages (e.g. Rust), and 4 profile types (call stack profiles, call graphs, heap snapshots, and traces). Earlier this year I tried using AI agents for performance optimization. They weren't very effective because they frequently: - Speculated about why something was slow from just reading the code - Made changes, measured the wall time before

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Source record

Recorded metrics

points · 2 votes
2026-11-15 16:37:15.509Z
cumulative since publication

Research analysis

Project record

Repository: TomerAberbach/profiler-md. Source account: Hi HN! profiler-md is a CLI and JS library that converts performance profiles to Markdown across 17 formats (e.g. pprof), 29 profilers (e.g. py-spy), 22 languages (e.g. Rust), and 4 profile types (call stack profiles, call graphs, heap snapshots, and traces). Earlier this year I tried using AI agents for performance optimization. They weren't very effective because they frequently: - Speculated about why something was slow from just reading the code - Made changes, measured the wall time before

Observed adoption & comparisons

Source votes: 2 votes (Nov 15, 2026 UTC; cumulative since publication) Recent records to compare: “Show HN: A local-first AI agent for the desktop, no Electron, any LLM endpoint” (Hacker News, Nov 15, 2026); “Show HN: db-branch – database branches in seconds for AI agents and CI, via ZFS” (Hacker News, Nov 15, 2026). Shared themes are navigation hints; they have not been verified as the same need or independent corroboration.

Adoption decision

Evaluate it against the tool or manual workflow it would replace. The stored record supports discovery; it does not yet establish reliability, lower operating cost or commercial adoption.

Unverified requirements

Not verified: license permissions, required hardware, installation steps, maintenance status and a representative task with its failure cases.

Next test

Choose one real task and a current alternative. Record the commit, environment, input, output, elapsed time and failure behavior; retain the result before recommending adoption.