mssql-performance-review

SQL Server Performance Review Orchestrator Skill

Purpose

A dispatch skill that turns a mixed pile of SQL Server artifacts (or a symptom description) into a single, evidence-backed performance review. It does not redefine any checks — it routes work to the 18 specialised review skills, then synthesises their findings into one consolidated report.

The orchestrator is strictly offline: it reads files the user provides, generates capture-script bundles when artifacts are missing, and emits analysis reports. It never opens a connection to a SQL Server. All execution against the database is the user's action.

This skill applies eleven cross-cutting primitives that distinguish it from a naive dispatcher:

Tier 1 — agentic core:

• Evidence chain (E-tags) — every finding cites the source artifact, the specialised check ID, the observed value, and the threshold violated, so any recommendation is reproducible from the input set
• Risk-aware recommendations — every recommended fix carries action, effort, blocking window, risk class, side effects, explicit rollback, and post-deployment verification
• Adversarial root cause check — after the primary hypothesis is identified, a deliberate pass tries to disprove it; contradicting evidence escalates an alternative hypothesis instead of being suppressed
• Confidence-driven early termination — once three or more specialised skills converge on the same root cause with HIGH confidence and no active contradiction, additional probes are skipped as redundant

Tier 2 — routing and intelligence:

• Multi-model routing — each phase runs on the right model (Haiku for classification and triage, Sonnet for synthesis and deep dive, Opus for the adversarial pass). See references/model-routing.md.
• Skill-graph DAG — replaces fixed phase ordering with a dynamic dependency DAG built from artifact types and probe findings. Probes that depend on each other sequence correctly; everything else runs in parallel. See references/skill-dag.md.
• Domain memory — per-instance facts (MAXDOP, cores, AG topology, partitioning, RCSI status) loaded from a user-managed JSON file inform every recommendation: redundant recommendations rejected, environment-aware escalators applied. See references/domain-memory.md.
• Follow-up Q&A — after the report, the orchestrator stays in the session and answers questions ("why this index ordering?", "why was MAXDOP not recommended?") from the in-context evidence chain. Most follow-ups need no new dispatch. See references/followup-qa.md.