Measure skill execution duration and record performance metrics.
npx skills add https://github.com/sfc-gh-myoung/ai_coding_rules --skill skill-timing
Please help me install this Agent Skill. Skill: skill-timing Source: https://github.com/sfc-gh-myoung/ai_coding_rules/tree/main/skills/skill-timing Command: npx skills add https://github.com/sfc-gh-myoung/ai_coding_rules --skill skill-timing
This timing instrumentation enables measurement of skill execution duration, checkpoint tracking, and token-cost estimation to support performance analysis and optimization.
Start timing a skill with a target and model, then end timing to embed results.
High-intent search queries and answers about installing and using this skill.
Timing instrumentation measures wall-clock execution duration and records performance metrics to identify slow steps. You apply this to CI/CD pipelines by enforcing performance expectations through start, checkpoint, and end sequencing during production runs.
Identifying bottlenecks across multiple agents requires applying checkpoints within your timing instrumentation. Checkpoints surface specific gate overhead and slow steps, enabling precise performance analysis and cross-platform optimization.
To estimate token cost and track model calls during performance baselining, apply timing instrumentation that captures token usage alongside execution duration. This establishes baseline metrics to gauge cost improvements over time across multiple models.
You can generate performance reports in JSON, CSV, markdown, and human-readable formats. Timing instrumentation outputs persistent timing data in these formats after you end the measurement sequence, supporting flexible reporting and analysis.
The timing instrumentation supports cross-platform and multi-agent safe execution. It applies consistently to experiments and production runs across multiple models and agents, ensuring reliable performance metrics and wall-clock timing data.
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