extremely-optimize

Solid

Use when asked to run a performance campaign against a measured floor. Not for hypothesis-only analysis without mutation: use fastopt.

AI & Automation 38 stars 0 forks Updated yesterday Apache-2.0

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Skill Content

# Extremely optimize ## Contract | Field | Bound contract | |---|---| | Trigger | Subsystem or repo-wide performance campaign against a measured floor; the user says "make this as fast as possible", "extremely optimize", or "grill every inefficiency" | | Authority | Reversible local: writes only VCS-tracked source targets (destructive; the exact set shown before mutation); rollback is version control. No remote mutation. | | Side effect | Hot-path source targets rewritten as atomic commits; non-wins reverted; boundary surfaces gated before any touch | | Done | Hot units rebuilt with an even win, cold units graded fixed/at-floor/left, residue gone, verifier green, target landed atomically | ## Inputs - A named subsystem path, or no path for a repo-wide survey. Repo-wide work is opt-in and never inferred. A bare invocation profiles the repo's own workload, then works the ranked list. - One runnable workload command exercising the target with representative input and taking at least one second of wall clock. Must be supplied or constructed before measurement begins. - The repo's own verifier command. Must be supplied or discovered before any target lands. ## Procedure 1. **Pin the workload and baseline.** Run `hyperfine --warmup 3 --min-runs 10 '<cmd>'`. Record median, stddev, min, max. Reject the measurement while stddev exceeds 20 % of median: pin CPU frequency, isolate the process, widen `--min-runs`, or enlarge the input until the noise clears. Use this number for ever...

Details

Author
OutlineDriven
Repository
OutlineDriven/odin-claude-plugin
Created
10 months ago
Last Updated
yesterday
Language
Python
License
Apache-2.0

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