skill-thiientv-godmode-performance-optimization · by Install
$ agentstack add skill-thiientv-godmode-performance-optimization ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
Verified badge
Passed review? Show it. Paste this badge into your README, it links to the public security report.
Links to your public security report.[](https://agentstack.voostack.com/security/report/skill-thiientv-godmode-performance-optimization) Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
Performance Optimization
Measure the bottleneck before optimizing it.
Workflow
- Define the user or system target: p50/p95/p99 latency, throughput, startup,
memory ceiling, frame budget, bundle size, query cost, or error budget.
- Build a representative and repeatable workload with realistic data,
concurrency, cache state, network, and device assumptions.
- Capture a baseline with profiler, trace, query plan, browser performance
panel, bundle analyzer, or resource metrics. Record variance and warm/cold state.
- Rank bottlenecks by user impact and cost. Form one falsifiable hypothesis.
- Make the smallest change, rerun the same workload, and compare effect and
regressions. Keep only improvements that meet the target without violating correctness, accessibility, cost, or operability.
- Add a regression budget/check where the risk is likely to recur.
Read [measurement.md](references/measurement.md). Do not optimize a benchmark that does not represent the user path, hide work by weakening correctness, or claim improvement from one noisy run.
Completion condition
The bottleneck, baseline, change, before/after result, variance, trade-offs, and remaining limits are documented.
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: thiientv
- Source: thiientv/godmode
- License: MIT
- Homepage: https://thiientv.github.io/godmode
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.