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ops-query

Cross-references indexer data, broker telemetry, and CloudWatch logs to diagnose operational issues.

1|Updated Apr 11, 2026
Search Tags:#telemetry#investigate#diagnose#cloudwatch#indexer#production-issues#ops-query
One-click install
npx skills add https://github.com/Current-cmd/PlsTrustMe --skill ops-query-current-cmd
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: ops-query
Source: https://github.com/Current-cmd/PlsTrustMe/tree/main/.claude/skills/ops-query
Command: npx skills add https://github.com/Current-cmd/PlsTrustMe --skill ops-query-current-cmd

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Cross-reference on-chain indexer data, broker telemetry, and CloudWatch logs to investigate production and staging operational issues, understand why slashings happened, diagnose prover or service failures, and correlate market events with broker behavior. It is used when the user wants to investigate root causes on live networks and for tasks that require combining multiple data sources; do not use for debugging local code changes or reviewing PRs.

Core Features & Use Cases

  • Cross-source investigations: Join indexer, telemetry, and logs to form a coherent incident narrative.
  • Root-cause analysis: Identify why orders were skipped, dropped, or slashed and map to telemetry signals and logs.
  • Operational dashboards & workflows: Reproduce findings with time-bounded windows and present findings to stakeholders.
  • Use Case: When a production gap occurs, use this skill to assemble data from indexer, telemetry, and logs to explain the event and propose fixes.

Quick Start

Initiate a prod investigation by wiring together indexer, telemetry, and CloudWatch logs for a defined time window to identify root causes and recommended remediation.

Frequently Asked Questions about ops-query

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I investigate production slashings and correlate indexer data with broker telemetry?▼

To investigate production slashings, cross-reference on-chain indexer data, broker telemetry, and CloudWatch logs within a defined time window to identify why orders were skipped or dropped.

What is the best way to diagnose fulfillment rate drops across live Boundless environments?▼

Diagnosing fulfillment rate drops requires joining indexer market events with broker behavior and CloudWatch service logs to map operational failures to telemetry signals on live networks.

Do I need CloudWatch and indexer access to diagnose prover failures on staging?▼

Yes, diagnosing prover failures requires configuring MARKET_INDEXER_URL and obtaining both indexer access and CloudWatch log credentials via the Boundless runbook before querying data.

Can I use this cross-source investigation approach for debugging local code changes?▼

No, cross-source investigation is designed for diagnosing live network operational issues and correlating market events, not for debugging local code changes or reviewing pull requests.

How do I start a cross-source production issue investigation using telemetry and logs?▼

Start a production investigation by wiring together indexer data, broker telemetry, and CloudWatch logs for a specific time-bounded window to assemble an incident narrative and propose fixes.

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