optimize-initializing-speed
Skill373 starsChanged 22 days agoMITView on GitHub
Use when optimizing VM Initializing-to-Running latency while preserving functionality and low implementation complexity.
In this repository3 other files it gives its agents.
The file
We split this skill into the rules it gives an agent
3 rules. About 0 are common, 1 is distinctive, and 2 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈1
Distinctive · estimate
This author's own choices. Worth a look.
2
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 12
Keep Running gated only on program-start + agent-ready markers.
- Distinctive: line 15
Add fast-path checks (skip work when already installed/valid).
- Very specific: line 19
Keep guest-agent gate strict unless skip_guest_agent=true.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Optimize Initializing Speed
Goal
Minimize Create/Start -> Running latency without removing functionality. Base your decisions on what to optimize by using real measurements.
Priority Levers
- Keep
Runninggated only onprogram-start+agent-readymarkers. - Replace readiness polling with event-driven signaling
- Move heavy non-critical setup (kernel headers) off the critical path (ask permission from user if moving logic to async / could be still processing after Running is set).
- Add fast-path checks (skip work when already installed/valid).
- Parallelize independent init stages with simple barriers (no DAG engine). Avoid parallel tasks that are likely to conflict.
Guardrails
- Keep guest-agent gate strict unless
skip_guest_agent=true. - Preserve lifecycle semantics and blocked/allowed operations in
Initializing.
Measurement Protocol
- Measure baseline and candidate on the same host with the same 5-run harness.
- Report per-run samples + median/mean/min/max.
- Validate full regression suite before merge.
Required Outputs
- Exact before/after latency numbers.
- Short breakdown of biggest contributors.
- Risk notes, if any
Does it work?
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