Configures trace sampling rates and retention windows for DevOps workflows.
npx skills add https://github.com/AesopScott/mojo --skill trace-sampling
Please help me install this Agent Skill. Skill: trace-sampling Source: https://github.com/AesopScott/mojo/tree/main/harnesses/skills/trace-sampling Command: npx skills add https://github.com/AesopScott/mojo --skill trace-sampling
This Skill addresses the challenge of ballooning storage costs and excessive token usage by implementing intelligent sampling and retention policies for system traces.
Use the trace-sampling skill to define a new retention policy that limits trace storage to a maximum of thirty days for the production API harness.
High-intent search queries and answers about installing and using this skill.
Reduce trace storage costs by configuring intelligent sampling rates and retention windows to automatically age out unnecessary traces, preventing runaway storage expenses while maintaining observability.
Yes, you can sample a percentage of successful requests while retaining all error traces. This maintains debugging visibility for failures without the storage overhead of keeping every successful trace.
Configure trace retention by defining a structured policy that limits trace storage to a maximum age, such as thirty days for production, balancing auditability with resource efficiency to control costs.
Trace sampling balances observability and budgets by selectively capturing a subset of telemetry data based on configurable rates and audit logging thresholds, ensuring operational efficiency without losing critical visibility.
No dependencies are required to manage trace sampling and retention policies. The configuration applies directly to infrastructure engineering and DevOps workflows to handle budget-conscious telemetry management.
Avoid aggressive trace sampling when full auditability is required for compliance or when debugging intermittent high-traffic API issues, as low sampling rates may drop the exact traces needed for root cause analysis.
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