adobe/performance-tuning
plugins/aem/cloud-service/skills/dispatcher/performance-tuning/SKILL.md
Optimize performance of the Adobe Dispatcher Apache HTTP Server module and related HTTPD configuration for AEMaaCS cloud workflows only, with cloud-specific baseline and runtime verification.
$ install --global
skillsauthnpx skillsauth add adobe/skills performance-tuningInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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SKILL.md
- name:
- performance-tuning
- description:
- Optimize performance of the Adobe Dispatcher Apache HTTP Server module and related HTTPD configuration for AEMaaCS cloud workflows only, with cloud-specific baseline and runtime verification.
- license:
- Apache-2.0
- compatibility:
- Requires Dispatcher MCP configured for cloud variant (`AEM_DEPLOYMENT_MODE=cloud`).
- allowed-tools:
- validate lint sdk trace_request inspect_cache monitor_metrics tail_logs
- mcp-tool-contract:
- core-7-tools
Dispatcher Performance Tuning (Cloud)
Improve cache efficiency, latency, and throughput for cloud deployments that use the Adobe Dispatcher Apache HTTP Server module and related HTTPD configuration.
Variant Scope
- This skill is cloud-service-only.
- Scope is fixed by this skill directory; do not ask the user to choose deployment variant.
MCP Tool Contract
Use only these Dispatcher MCP tools:
validatelintsdktrace_requestinspect_cachemonitor_metricstail_logs
Workflow
- Capture baseline metrics and cache evidence.
- Apply cloud guardrails (immutable/default includes, reserved probe paths, and CDN-vs-Dispatcher ownership) before proposing changes.
- Prioritize low-risk/high-impact changes.
- Apply minimal edits.
- Verify with
validate,lint, andsdk. - Compare before/after runtime evidence.
Verification Scope Selection
Use shared references to select optimization evidence depth:
- mode-specific-verification-matrix.md
- test-case-catalog.md
Output Contract
Always return:
- baseline metrics snapshot
- prioritized optimization list with impact/risk
- changed files and intent
- executed checks + before/after evidence
- selected test IDs and outcomes
- rollback plan and open risks
Guardrails
- Do not claim improvement without measurable comparison.
- Keep high-risk tuning opt-in unless user explicitly requests it.
- Keep cloud assumptions explicit for each recommendation batch.
- Route edge/WAF/CDN-only concerns to CDN layer guidance instead of Dispatcher config changes.
References
- optimization-patterns.md
- performance-scenario-playbooks.md – scenario-driven tuning flows adapted from broader MCP prompt surfaces
- load-testing-guidance.md
- performance-monitoring-setup.md
- quick-start-execution-path.md – fast entry path for optimization requests
- repo-layout-workflows.md – map performance findings to cache, farm, vhost, and rewrite file families
- playbook-command-linkage.md – exact MCP command chains for tuning playbooks
- mode-specific-verification-matrix.md
- cloud-service-aemaacs-guardrails.md – cloud-service-only immutable/include/runtime boundary checks from AEMaaCS patterns
- test-case-catalog.md
- change-risk-and-rollback-template.md
- public-docs-index.md
- public-doc-citation-rules.md
- core-7-tools-reference.md
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