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Techtide azure cosmosdb performance investigator

Skill TechTideOhio/techtide-harness-kit/skills/azure/techtide-azure-cosmosdb-performance-investigator

Use this skill for Azure Cosmos DB performance investigation, especially RU spikes, query latency, throttling, hot partitions, indexing inefficiency, partition-skew analysis, request-charge profiling, diagnostic-log review, and evidence-driven remediation planning.From its SKILL.md

Install
npx -y skills add TechTideOhio/techtide-harness-kit --skill techtide-azure-cosmosdb-performance-investigator

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SKILL.md

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Azure Cosmos DB Performance Investigator

Purpose

Investigate Azure Cosmos DB performance pathologies with evidence-first profiling instead of lazy “add more RUs” advice.

This skill is for deep performance work across:

  • RU inefficiency and unexpected request-charge spikes,
  • query latency and scan-heavy query behavior,
  • hot partitions and partition-key skew,
  • throttling, retry inflation, and client-perceived latency,
  • indexing gaps and poor query/index alignment,
  • container, partition, and workload-level profiling,
  • diagnostic-log and metrics-backed remediation planning.

When to use

Use this skill when the user asks for:

  • slow Azure Cosmos DB queries or workload latency,
  • high RU cost or suspicious request-charge behavior,
  • 429 throttling analysis,
  • hot partition or partition-skew investigation,
  • indexing or query-performance tuning,
  • a step-by-step Cosmos DB profiling plan.

Do not use this skill as a substitute for:

  • initial data-model design when the main problem is greenfield schema modeling,
  • pure account/platform governance review when performance is incidental,
  • generic application debugging unrelated to Cosmos DB workload behavior,
  • vector-search-specific Mongo vCore tuning unless the user explicitly asks for that API surface.

Lean operating rules

  • Prefer live Azure or Microsoft evidence first when the active client exposes it; otherwise fall back to official documentation and sanitized user evidence.
  • Separate confirmed facts from inference. If state was not queried or shown, say so.
  • Challenge throughput-first fixes that ignore partition skew, query scans, indexing, or client retry inflation.
  • Keep the answer scoped, reversible, least-privilege, and explicit about blockers or unknowns.

References

Load these only when needed:

  • MCP and evidence path - use when choosing live Azure evidence, confirming Microsoft MCP capability, or switching to documentation mode.
  • Workflow and output contract - use when executing the full investigation, applying stress checks, or formatting the final answer.
  • Data profiling playbook - use when you need the detailed step-by-step profiling sequence.
  • Official sources - use when you need the detailed Microsoft documentation list or source notes.

Response minimum

Return, at minimum:

  • the scoped target and evidence level,
  • the main performance pathologies observed or still unproven,
  • the safest next profiling or remediation steps,
  • the assumptions or blockers that prevent stronger conclusions.

What ships with it: 5 files

13.5 KB alongside SKILL.md

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