Aivana Database Engineer

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---
name: advisor-confidence-grader
description: Grade advisory recommendations by evidence strength and identify missing proof before production change.
---

# Advisor Confidence Grader

Run:

```bash
node runtime/runTool.js advisor_confidence_grader '{"evidence":{"hasLivePlan":true,"hasWaits":true,"hasRollback":true}}'
```

Returns evidence grade, score, missing evidence, and required next evidence.

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---
name: ai-anomaly-triage
description: Correlate query stats, telemetry, policy decisions, and replay memory into deterministic incident hypotheses and next-best actions.
---

# AI Anomaly Triage

Use this skill when an operator asks why database behavior changed, whether a
deployment caused a regression, or what to investigate first during an incident.

Run:

```bash
node runtime/runTool.js ai_anomaly_triage '{"engine":"postgres","database":"analytics","deploymentId":"deploy-42","incidentWindowMinutes":45}'
```

The tool is offline and deterministic. It combines workload stats,
telemetry-correlation output, policy-memory signals, and recent replay context.
It returns an anomaly score, root-cause hypotheses, next-best actions, and
explainability fields listing the exact signal families used.

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---
name: ai-data-contract-guardian
description: Check schema drift, required columns, PII declaration, retention, and governance controls against a declared data contract.
---

# AI Data Contract Guardian

Use this skill when validating table contracts before deploys, migrations, or
data product releases.

Run:

```bash
node runtime/runTool.js ai_data_contract_guardian '{"engine":"postgres","database":"analytics","schema":"public","table":"events","contract":{"requiredColumns":["event_id","user_email","created_at"],"piiColumns":["user_email"],"retentionDays":90}}'
```

The output includes contract findings, a contract status, required governance
controls, and evidence from catalog metadata. It is deterministic and does not
call an external AI service.

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---
name: ai-decision-simulator
description: Simulate database agent decisions against evidence, policy, and approval constraints.
---

# ai_decision_simulator

Use this skill to simulate how an AI database agent should decide under evidence, policy, and approval constraints.

Governance:
- Simulation only.
- No production apply or autonomous DDL.
- Human approval requirements always override dry-run readiness.

Output contract:
- `usp: "ai_decision_simulator"`
- `proposedAction`, `simulatedDecisions`, `decision`
- `evidence`, `confidence`, `source: "analysis"`

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---
name: ai-guarded-sql-generator
description: Generates bounded read SQL with tenant, policy, audit, and performance guardrails.
---

# AI Guarded SQL Generator

Run:

```bash
node runtime/runTool.js ai_guarded_sql_generator '{"intent":"list recent paid orders","table":"orders","filters":{"status":"paid"},"limit":100,"tenantId":"tenant-a"}'
```

Returns generated SQL, guardrails, and risk classification.

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---
name: ai-migration-risk-radar
description: Score migration blast radius and produce a rollback rehearsal plan before schema changes reach production.
---

# AI Migration Risk Radar

Use this skill before proposing, signing, or applying migrations.

Run:

```bash
node runtime/runTool.js ai_migration_risk_radar '{"engine":"sqlserver","database":"app_prod","schema":"public","migrationSql":"CREATE INDEX ix_orders_status ON orders(status)"}'
```

The tool computes blast radius from catalog metadata, risk classification,
PII sensitivity, table size hints, and policy preflight. It returns a release
recommendation and dry-run rollback rehearsal checklist.

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---
name: ai-query-rewrite-lab
description: Generate safe query rewrite candidates with deterministic explainability without executing SQL.
---

# AI Query Rewrite Lab

Use this skill to propose safer or cheaper SQL variants before running EXPLAIN
or executing a statement.

Run:

```bash
node runtime/runTool.js ai_query_rewrite_lab '{"engine":"postgres","database":"analytics","schema":"public","table":"events","sql":"SELECT * FROM events WHERE user_email = ''a@example.com''"}'
```

The lab never executes SQL. It returns rewrite candidates, expected impact
ranges, applied rewrite rules, and a safety block that marks the output as
analysis-only.

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---
name: ai-roi-narrative-generator
description: Explain database tuning ROI from supplied measurements and explicitly labeled estimates.
---

# ai_roi_narrative_generator

Use this skill to translate AI database operations evidence into an executive ROI narrative.

Governance:
- Narrative and scoring only.
- Keep ROI claims tied to provided evidence.
- Do not present estimates as audited finance results.

Output contract:
- `usp: "ai_roi_narrative_generator"`
- `executiveNarrative`, `roiSignals`
- `evidence`, `confidence`, `source: "analysis"`

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---
name: ai-strategy-synthesizer
description: Build a database improvement roadmap from objectives, evidence, and operational constraints.
---

# ai_strategy_synthesizer

Use this skill to turn enterprise platform priorities into an AI database operations roadmap.

Governance:
- Analysis-only.
- No production apply, DDL, or live remediation.
- Keep recommendations tied to closed-loop dry-run evidence and human approval gates.

Output contract:
- `usp: "ai_strategy_synthesizer"`
- `positioning`, `objective`, `roadmap`, `guardrails`, `recommendations`
- `evidence`, `confidence`, `source: "analysis"`

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---
name: ai-trust-scorecard
description: Assess the evidence and explainability of database advisor recommendations.
---

# ai_trust_scorecard

Use this skill to score AI recommendations across explainability, safety, reproducibility, and governance.

Governance:
- Analysis-only scoring.
- Low trust requires more evidence before recommendation.
- Trust scores do not authorize production execution.

Output contract:
- `usp: "ai_trust_scorecard"`
- `trustScore`, `decision`
- `evidence`, `confidence`, `source: "analysis"`

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---
name: audit-query
description: "Generate audit-grade records for sensitive SQL operations including approvals, risk outcomes, and execution traces."
---

# Audit Query

## Use when
- User or policy requires immutable evidence trail for governance/compliance.

## Workflow
1. Capture request context, actor, environment, and policy context.
2. Attach parsed query fingerprint and risk decision.
3. Record outcomes, anomalies, and deviations.
4. Produce a signed audit artifact when applicable.

## Governance
- Ensure immutable append-only behavior.
- Redact secrets and raw sensitive literals in logs.

## Output
- `auditEntryId`, `requestFingerprint`, `decisionLog`, `approvalChain`, `trace`

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---
name: autonomous-dba-copilot
description: Orchestrates a DBA loop from evidence collection through confidence grading, experiment design, ticket prep, and rollback.
---

# Autonomous DBA Copilot

Run:

```bash
node runtime/runTool.js autonomous_dba_copilot '{"question":"Checkout is slow","sql":"SELECT * FROM orders","evidence":{"hasLivePlan":true,"hasWaits":true,"hasRollback":true}}'
```

Returns loop steps, decision package, next action, and evidence grade.

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---
name: autonomous-experiment-planner
description: Designs dry-run experiments across query rewrites, indexes, workload twins, and rollout gates.
---

# Autonomous Experiment Planner

## Use when
- An operator goal needs evidence before any change recommendation.

## Governance
- Experiments must be `dry_run`.
- Abort if an experiment requires real apply, lacks rollback, or has unknown tenant scope.

## Output
- `experiments`, `abortCriteria`, `decision`, `safeNextAction`

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---
name: autonomous-learning-backlog
description: Prioritize missing evidence and follow-up experiments from database advisor feedback.
---

# autonomous_learning_backlog

Use this skill to convert advisor feedback, incidents, and outcomes into prioritized AI learning tasks.

Governance:
- Analysis-only backlog generation.
- Do not mutate models, policies, or production systems.
- Prioritize rollback evidence, confidence calibration, incident patterns, and prompt safety.

Output contract:
- `usp: "autonomous_learning_backlog"`
- `executionMode: "analysis_only"`
- `learningBacklog`
- `evidence`, `confidence`, `source: "analysis"`

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---
name: autonomous-ops-briefing
description: Produces a board-level briefing for closed-loop autonomous database operations.
---

# Autonomous Ops Briefing

## Use when
- Operators need a concise final summary of decision, evidence, confidence, risks, and safe next action.

## Governance
- Positioning is autonomous operations without autonomous production risk.
- Briefings must expose missing evidence and approval boundaries.

## Output
- `boardSummary`, `decision`, `evidence`, `confidence`, `risks`, `safeNextAction`

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---
name: autonomous-verification-loop
description: Create prove-before-apply gates for migrations, indexes, rewrites, SLOs, replay, and rollback evidence.
---

# Autonomous Verification Loop

Use this skill before applying write-like database changes.

Run:

```bash
node runtime/runTool.js autonomous_verification_loop '{"tool":"create_index","engine":"postgres","database":"analytics","schema":"public","table":"events","proposedSql":"CREATE INDEX ix_events_email ON events(user_email)"}'
```

The tool returns gates for policy, explain, replay, SLO, and rollback evidence,
plus a release decision.

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---
name: autonomy-boundary-enforcer
description: Enforces closed-loop dry-run boundaries and blocks autonomous production apply.
---

# Autonomy Boundary Enforcer

## Use when
- A proposed autonomous action must be checked against execution boundaries.

## Governance
- Production apply and real DDL execution require human approval.
- Only dry-run actions are autonomously allowed.

## Output
- `boundary`, `requiredApprovals`, `decision`, `safeNextAction`

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---
name: benchmark-ab-runner
description: Compare baseline and candidate query performance metrics and declare a benchmark winner.
---

# Benchmark A/B Runner

Run:

```bash
node runtime/runTool.js benchmark_ab_runner '{"baseline":{"p95Ms":300,"cpuMs":80},"candidate":{"p95Ms":190,"cpuMs":55}}'
```

Returns deltas, winner, and verdict.

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---
name: change-ticket-exporter
description: Export approval-ready production change tickets with problem, recommendation, risk, rollback, and checklist.
---

# Change Ticket Exporter

Run:

```bash
node runtime/runTool.js change_ticket_exporter '{"title":"Add checkout index","problem":"p95 breach","recommendation":"create index","rollback":"drop index"}'
```

Returns ticket fields, approval checklist, labels, and export formats.

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---
name: cognitive-schema-mapper
description: Infer candidate business concepts from supplied database schema metadata.
---

# cognitive_schema_mapper

Use this skill to map database schema names and domain terms into a business ontology for AI reasoning.

Governance:
- Analysis-only semantic mapping.
- Do not infer sensitive data access permissions.
- Flag domain terms that lack schema evidence as semantic gaps.

Output contract:
- `usp: "cognitive_schema_mapper"`
- `ontology`, `semanticGaps`, `recommendations`
- `evidence`, `confidence`, `source: "analysis"`

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---
name: confidence-budget-manager
description: Scores whether enough evidence exists to recommend, defer, or escalate an autonomous operator decision.
---

# Confidence Budget Manager

## Use when
- The operator must decide whether it has enough evidence to proceed with dry-run recommendation.

## Governance
- Below-threshold evidence must return `needs_more_evidence`.
- Thresholds do not permit production apply.

## Output
- `confidenceBudget`, `decision`, `missingEvidence`, `safeNextAction`

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---
name: counterfactual-risk-engine
description: Compares do-nothing, dry-run-change, rollback, and defer scenarios for an operating objective.
---

# Counterfactual Risk Engine

## Use when
- A team needs to know the likely result of acting, waiting, rolling back, or deferring.

## Governance
- Produces scenario analysis only.
- Recommends dry-run validation before any apply path.

## Output
- `scenarios`, `recommendedScenario`, `decision`, `safeNextAction`

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---
name: cross-agent-consensus-builder
description: Compare supplied advisor recommendations and report agreement and unresolved disagreements.
---

# cross_agent_consensus_builder

Use this skill to combine performance, cost, security, compliance, and rollout agent findings into a consensus packet.

Governance:
- Analysis-only consensus.
- Preserve disagreements instead of hiding them.
- Disagreement should defer to more evidence or human review.

Output contract:
- `usp: "cross_agent_consensus_builder"`
- `consensus`, `disagreements`, `decision`
- `evidence`, `confidence`, `source: "analysis"`

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---
name: decision-evidence-compiler
description: Builds an executive-grade decision evidence packet from runtime signals and confidence checks.
---

# Decision Evidence Compiler

## Use when
- A dry-run recommendation needs an approval-ready evidence packet.

## Governance
- Missing evidence must be explicit.
- Confidence must be stated separately from recommendation.

## Output
- `executivePacket`, `missingEvidence`, `confidence`, `safeNextAction`

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---
name: dry-run-action-critic
description: Critiques proposed dry-run actions for blast radius, rollback gaps, tenant risk, and weak evidence.
---

# Dry-Run Action Critic

## Use when
- A candidate remediation needs adversarial safety review before recommendation.

## Governance
- Destructive or schema-changing actions must be escalated.
- Missing rollback, tenant, or live-plan evidence must be reported.

## Output
- `criticisms`, `decision`, `confidence`, `safeNextAction`

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---
name: enforce-policy
description: "Evaluate request against governance policies and either permit, gate, or block execution."
---

# Enforce Policy

## Use when
- Pre-execution gating is needed for write/read operations.
- User asks why an action is disallowed or delayed.

## Workflow
1. Resolve active policies for environment, user role, and data classification.
2. Evaluate action against allow/deny and approval matrix.
3. Return decision and required controls to proceed.
4. Persist decision in audit trail.

## Governance
- Deny-by-default across critical policy mismatches.
- Escalate critical violations to Compliance Agent workflow.

## Output
- `decision`, `requiredControls`, `exceptions`, `auditReference`

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---
name: erp-crm-advisor
description: Use when diagnosing ERP or CRM performance, integration failures, tenant isolation, reporting or customization risks using scoped evidence and explicit vendor-coverage gaps.
---

# ERP / CRM Advisor

Use when the user asks about ERP/CRM bottlenecks, vendor-specific data semantics,
integration failures, upgrades, reports, duplicate postings or tenant/company leakage.
Codex performs the interpretation; no separate LLM API key is required.

Resolve the plugin root two directories above this file. Read
`ERP_CRM_ANALYSIS.md` and `runtime/erp-crm-catalog.json` relative to that root.
Invoke its absolute `runtime/runTool.js` path; use JSON via stdin (`-`) for inputs.
Install missing dependencies with `npm ci` in the plugin root.

1. Run `erp_crm_vendor_catalog` with `{}`. Select an exact product profile; do not
   equate Dataverse with Finance and Operations or Business Central, or SAP ECC
   with S/4HANA. Obtain product release, instance ID, environment and deployment.
2. Run `erp_crm_evidence_plan` with the selected `product`. Identify installed
   modules, customizations and affected business processes. Separate application
   execution from database, API and reporting costs.
3. Inspect authorized, redacted exports and traces using available read-only
   tools. Do not invent credentials, assume native SaaS connectors, or send SOQL,
   SuiteQL, ABAP or HANA syntax to the SQL Server/PostgreSQL adapter.
   Use `erp_crm_import_diagnostics` for supported exports. For Dataverse traces or
   Salesforce query plans, use `erp_crm_collect_api` only with a configured
   provider URL, matching system ID, access token and explicit API version.
   A collector implementation is not proof that the customer's tenant was tested.
4. Build evidence bundles with matching context, trace references and actual
   observation timestamps. Populate supported numeric diagnostics from exports.
   For qualitative observations, assess the relevant code/configuration with an
   explanation tied to a trace or file reference; use `manual_review` for your
   interpretation. Never convert absent evidence into `false`, and never pretend
   a user assertion is a live measurement. Preserve provenance in the answer.
5. Run `erp_crm_risk_analyzer`. Explain prioritized findings, business impact,
   evidence, owner and next verification step. Include unresolved/conflicting
   checks and coverage of this finite catalog. Check the cited manufacturer
   guidance against the actual release before making product-specific claims.
6. For an optimization claim, run `benchmark_evidence_compare` on comparable,
   timestamped samples with case IDs, result hashes and row counts. Reject faster
   results with semantic differences or errors. Explain sampling and uncertainty;
   do not replace measured benchmarks with estimated advisor scores.
   Also run `workload_regression_guard` with the same runs to detect individual
   cases hidden by aggregate gains. Its defaults are a 10 percent per-case budget
   and a 1 ms noise floor; set these from the workload requirements. Repeat flagged
   cases under controlled load. A flag is not statistical proof or apply approval.
   Supply `caseBudgets` when the process owner provides absolute deadlines:
   `[{"caseId":"case-0","businessProcess":"Order posting","maxDurationMs":100}]`.
   Review existing as well as newly breached budgets. Unassessed cases are not
   evidence of business-SLO compliance. Preserve the returned policyHash with the
   benchmark inputHash so threshold changes remain distinguishable.

Review order-to-cash, procure-to-pay, period close and reporting where applicable:
company keys, document/line grain, status transitions, currencies/units, effective
dates, soft deletes, replication freshness and retry idempotency. Use control
totals from the business owner; a faster query that changes business meaning is
not an optimization.

Run `business_reconciliation_compare` for business control export

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---
name: estimate-cost
description: "Estimate compute, IO, and runtime cost for a candidate query, migration, or schema operation."
---

# Estimate Cost

## Use when
- User needs execution cost estimate before confirmation.

## Workflow
1. Run dry estimates from plan/cost model plus historical baselines.
2. Convert to understandable unit economics (CPU, IO, storage, lock occupancy).
3. Provide confidence interval and alternative lower-cost variants.
4. Attach optimization preconditions.

## Governance
- Flag high-cost operations and require explicit human confirmation.
- Include environmental impact assumptions used in estimate.

## Output
- `estimatedCost`, `confidence`, `assumptions`, `optimizationLevers`

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---
name: evidence-pack-generator
description: Build a DBA-ready performance case file with SQL, plan, waits, recommendation, rollback, and evidence grade.
---

# Evidence Pack Generator

Run:

```bash
node runtime/runTool.js evidence_pack_generator '{"question":"Why is checkout slow?","sql":"SELECT * FROM orders","recommendation":"add covering index"}'
```

Returns executive summary, case file sections, evidence grade, and missing evidence.

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---
name: explain-query
description: "Run structured explain/explain-analyze workflows and convert plan output into explainable optimization insights."
---

# Explain Query

## Use when
- User asks why query is slow.
- Planner needs operator-level bottleneck explanation.

## Workflow
1. Parse query intent and classify risk (read-only preferred mode).
2. Collect `EXPLAIN` and `EXPLAIN ANALYZE` output in deterministic form.
3. Annotate scan patterns, joins, sort/hash/temp spills, and lock indicators.
4. Produce rewrite hypotheses with confidence scores.

## Governance
- Default to dry-run style if query could mutate data.
- Provide "why" and "impact estimate" before any recommendation.

## Output
- `plan`, `bottlenecks`, `rewriteHints`, `estimatedCost`, `confidence`

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---
name: fleet-health-scorecard
description: Ranks database fleet health by latency, error-budget burn, and replication lag.
---

# Fleet Health Scorecard

Run:

```bash
node runtime/runTool.js fleet_health_scorecard '{"databases":[{"name":"prod-a","p95Ms":800,"errorBudgetBurnRate":3,"replicationLagSeconds":10}]}'
```

Returns ranked scorecard and health status.

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---
name: hotfix-risk-assessor
description: Rates emergency database hotfix risk and blocks unsafe production changes.
---

# Hotfix Risk Assessor

Run:

```bash
node runtime/runTool.js hotfix_risk_assessor '{"change":"ALTER TABLE orders ADD COLUMN priority int NOT NULL DEFAULT 0","environment":"production","hasRollback":false}'
```

Returns risks and decision.

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---
name: incident-analysis
description: "Correlate lock, query, and replication signals into causal incident hypotheses with prioritized remediation guidance."
---

# Incident Analysis

## Use when
- User asks why an incident happened or wants a causal chain.
- Response to operational regressions in latency, deadlocks, or replication lag.

## Workflow
1. Pull recent lock, query, and replication signal snapshots.
2. Correlate temporal overlap and severity transitions.
3. Build top incident hypotheses with confidence and remediation order.
4. Return expected validation probes and rollback readiness.

## Governance
- Do not trigger any destructive action.
- Mark confidence clearly before making any operational recommendation.

## Output
- `timeline`, `incidentHypotheses`, `confidence`, `recommendedActions`

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---
name: index-portfolio-optimizer
description: Optimize the whole index portfolio by finding redundant, overlapping, unused, and high-write-cost indexes.
---

# Index Portfolio Optimizer

Run:

```bash
node runtime/runTool.js index_portfolio_optimizer '{"indexes":[{"name":"ix_a","columns":["status"],"reads":100,"writes":50},{"name":"ix_ab","columns":["status","created_at"],"reads":200,"writes":60}]}'
```

Returns redundant indexes, drop candidates, create candidates, and action order.

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---
name: index-roi-simulator
description: Ranks index candidates by read benefit, write penalty, storage cost, and maintenance risk.
---

# Index ROI Simulator

Run:

```bash
node runtime/runTool.js index_roi_simulator '{"candidates":[{"id":"idx_events_user_email","readBenefitMs":180,"readQps":40,"writePenaltyMs":3,"writeQps":8,"storageMb":512}]}'
```

Returns ranked candidates, ROI score, break-even signal, and benchmark recommendation.

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---
name: knowledge-gap-detector
description: Identify missing database evidence before recommending an operational action.
---

# knowledge_gap_detector

Use this skill before AI recommendations to detect missing schema, plan, telemetry, policy, or rollback evidence.

Governance:
- Do not recommend apply actions when required evidence is missing.
- Prefer a dry-run collection action as the next step.
- Treat missing policy or rollback proof as a reason to defer.

Output contract:
- `usp: "knowledge_gap_detector"`
- `decision`, `knowledgeGaps`, `safeNextAction`
- `evidence`, `confidence`, `source: "analysis"`

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---
name: llm-prompt-risk-auditor
description: Inspect database operation requests for ambiguity and unsafe intent using deterministic rules.
---

# llm_prompt_risk_auditor

Use this skill to audit natural-language AI prompts or generated SQL instructions for dangerous ambiguity and unsafe production intent.

Governance:
- Never execute the prompt.
- Block or escalate destructive, broad, or production-scoped instructions.
- Rewrite unsafe requests as scoped dry-run diagnostics.

Output contract:
- `usp: "llm_prompt_risk_auditor"`
- `decision`, `risks`, `safeRewrite`
- `evidence`, `confidence`, `source: "analysis"`

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---
name: migration-twin-simulator
description: Builds a SQL Server to PostgreSQL migration twin and rates query-family performance risk.
---

# Migration Twin Simulator

Run:

```bash
node runtime/runTool.js migration_twin_simulator '{"sourceEngine":"sqlserver","targetEngine":"postgres","queries":[{"queryId":"q1","sql":"SELECT TOP 100 * FROM events"}]}'
```

Returns query risks, overall risk, and migration next actions.

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---
name: next-best-safe-action
description: Chooses the safest next dry-run diagnostic or experiment from candidate actions.
---

# Next Best Safe Action

## Use when
- Multiple actions are available and the operator must choose the safest next step.

## Governance
- Never select apply-mode actions as autonomous next steps.
- Prefer low-risk dry-run diagnostics and simulations.

## Output
- `safeNextAction`, `rejectedActions`, `decision`, `confidence`

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---
name: objective-to-ops-plan
description: Converts an enterprise database operations objective into measurable goals, guardrails, and closed-loop dry-run workflows.
---

# Objective To Ops Plan

## Use when
- A platform team gives a high-level reliability, latency, cost, or risk objective.

## Governance
- Closed-loop dry-run only.
- Never performs production apply or real DDL execution.

## Output
- `measurableObjectives`, `guardrails`, `candidateWorkflows`, `safeNextAction`

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---
name: operator-goal-monitor
description: Converts SLO, cost, compliance, and incident goals into ongoing watch criteria and escalation policy.
---

# Operator Goal Monitor

## Use when
- A platform team wants an autonomous operator to watch operating goals over time.

## Governance
- Monitoring can trigger dry-run experiments, not direct remediation.

## Output
- `watchCriteria`, `escalationPolicy`, `decision`, `safeNextAction`

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---
name: performance-pr-reviewer
description: Reviews schema and migration pull requests for performance, locking, index, and rollback risks before merge.
---

# Performance PR Reviewer

Run:

```bash
node runtime/runTool.js performance_pr_reviewer '{"pullRequest":"PR-42","changes":[{"type":"add_foreign_key","table":"orders","column":"customer_id","hasSupportingIndex":false}]}'
```

Returns merge decision, findings, and required checks.

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---
name: policy-gated-self-healing
description: Creates safe self-healing runbooks with policy, rollback, and approval gates instead of blind production changes.
---

# Policy Gated Self Healing

Run:

```bash
node runtime/runTool.js policy_gated_self_healing '{"incidentType":"lock_pressure","riskLevel":"high","environment":"production"}'
```

Returns execution mode and gated runbook.

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---
name: production-readiness-check
description: Check whether CodexDB Agent is safe to run in production with live database connections, signing, audit replay, drivers, and complete skill metadata.
---

# Production Readiness Check

Use this skill before enabling CodexDB Agent against production SQL Server or PostgreSQL.

Run:

```bash
node runtime/runTool.js production_readiness_check '{"environment":"production","engine":"postgres"}'
```

The tool returns:

- `ready`: true only when no production blockers remain.
- `blockingIssues`: hard deployment blockers.
- `warnings`: non-blocking operational risks.
- `checks`: individual readiness checks for manifests, skill docs, live mode, drivers, migration signing, and audit replay.

Production should set:

- `CODEXDB_REQUIRE_LIVE_CONNECTION=true`
- `CODEXDB_MIGRATION_SIGNING_KEY`
- engine-specific connection variables such as `CODEXDB_POSTGRES_CONNECTION_STRING` or `CODEXDB_SQLSERVER_SERVER`.

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---
name: production-rollout-orchestrator
description: Combine production readiness, verification gates, and migration risk into a Go/No-Go rollout decision.
---

# Production Rollout Orchestrator

Run:

```bash
node runtime/runTool.js production_rollout_orchestrator '{"environment":"production","engine":"postgres","database":"analytics","schema":"public","table":"events","proposedSql":"CREATE INDEX ix_events_created_at ON events(created_at)"}'
```

Returns rollout gates, evidence, a Go/No-Go decision, and next actions.

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---
name: query-contract-tester
description: Validates SQL against query contracts such as required columns, max rows, and read-only expectations.
---

# Query Contract Tester

Run:

```bash
node runtime/runTool.js query_contract_tester '{"sql":"SELECT id,total FROM orders LIMIT 50","contract":{"requiredColumns":["id","total"],"maxRows":100,"readOnly":true}}'
```

Returns contract status and violations.

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---
name: recommendation-ranker
description: Rank SQL performance recommendations by expected impact, operational risk, and implementation effort.
---

# Recommendation Ranker

Run:

```bash
node runtime/runTool.js recommendation_ranker '{"recommendations":[{"id":"narrow_projection","impact":"medium","risk":"low","effort":"low"}]}'
```

Returns ranked recommendations and score rationale.

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---
name: release-readiness-report
description: Produce a release readiness report across production blockers, connector status, and health assessment.
---

# Release Readiness Report

Run:

```bash
node runtime/runTool.js release_readiness_report '{"environment":"production","engine":"postgres"}'
```

Returns readiness sections, open blockers, and final ready flag.

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---
name: rollback-rehearsal-engine
description: Creates rollback rehearsal steps and proof checklist for database changes.
---

# Rollback Rehearsal Engine

Run:

```bash
node runtime/runTool.js rollback_rehearsal_engine '{"change":"CREATE INDEX ix_orders_status ON orders(status)","rollback":"DROP INDEX ix_orders_status","validationQueries":["SELECT count(*) FROM orders"]}'
```

Returns rehearsal status and ordered rollback validation steps.

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---
name: semantic-incident-predictor
description: Classify potential database incident risks from supplied signals using heuristic analysis.
---

# semantic_incident_predictor

Use this skill to predict likely database incident classes from semantic workload and telemetry signals.

Governance:
- Prediction only.
- Use results to choose dry-run diagnostics, not remediation.
- Escalate high-likelihood production risks to evidence collection.

Output contract:
- `usp: "semantic_incident_predictor"`
- `workload`, `predictions`, `decision`, `safeNextAction`
- `confidence`, `source: "analysis"`

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---
name: semantic-memory-index
description: Build a local token-vector memory index for deterministic retrieval without external embeddings.
---

# Semantic Memory Index

Use this skill to index runbooks, policy snippets, tickets, or schema notes for
local retrieval.

Run:

```bash
node runtime/runTool.js semantic_memory_index '{"documents":[{"id":"runbook-1","text":"orders latency after deploy compare query plans"}],"query":"deploy latency"}'
```

The tool stores index metadata in plugin memory and returns ranked token-overlap
matches.

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---
name: slo-impact-guard
description: Translates SQL latency regressions into SLO status, error-budget burn, impacted traffic, and executive summary.
---

# SLO Impact Guard

Run:

```bash
node runtime/runTool.js slo_impact_guard '{"sloTargetMs":300,"observedP95Ms":750,"requestsPerMinute":12000,"criticalPath":"checkout"}'
```

Returns SLO breach status, burn rate, impacted requests, and actions.

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---
name: sql-code-review-assistant
description: Reviews SQL like a senior DBA and returns PR-ready comments and decision.
---

# SQL Code Review Assistant

Run:

```bash
node runtime/runTool.js sql_code_review_assistant '{"sql":"SELECT * FROM orders WHERE LOWER(status) = ''paid''","context":"pull_request"}'
```

Returns review comments, severities, and review decision.

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---
name: sql-performance-advisor
description: Use when investigating SQL Server or PostgreSQL performance and guiding a case from scoped diagnosis to measured, business-correct verification.
---

# SQL Performance Advisor

For explicit tuning acceptance limits, supply `budgets` with `caseId` and
`maxCandidateMedianMs` and/or `maxRegressionMs`. Report every unbudgeted case.
Treat exceeded limits as a rejected candidate and context drift as inconclusive;
do not label observed median budgets as production SLO or percentile guarantees.

For ERP invariants, add lab cases with `assertion: "zero_violations"` using reviewed
control-query templates. Each must return one `violations` integer count. Treat
nonzero or malformed evidence as rejection even when both query results match.
State exactly which business rule and database principal were tested; never claim
universal ERP or cross-role correctness from these checks.

Use `run_tuning_lab` to combine before/after live context fingerprints with the
administratively qualified lab rewrite replay. Require all replay scope, registry,
template and edge-case coverage prerequisites. Reject result differences and treat
context drift as inconclusive. Median client duration is not server CPU or a proven
production improvement. Report the returned missing evidence before proposing a fix.

For SQL Server TempDB investigation use `collect_tempdb_health` with explicit
`engine: "sqlserver", database: "tempdb"`. Explain that TempDB is shared across
application databases. Review file settings, data/log counters and observed page
waits without inferring disk headroom, allocation contention or workload ownership.
Preserve unavailable/truncated sections. Never automatically shrink or resize files.

For PostgreSQL replication or WAL-retention investigations, use
`collect_replication_health` with explicit `engine: "postgres"` and `database`.
Report cluster-wide physical slots/archive statistics separately from database-local
logical slots. Preserve unavailable sections and decimal-string LSN distances;
never equate them with disk usage or replica delay. Findings request investigation,
not permission to drop slots or remove WAL. Subscriber health remains unverified.

For ERP/CRM vendor context, first follow `../erp-crm-advisor/SKILL.md` and select
the exact product profile. Do not infer that a vendor-managed SQL endpoint permits
index changes or that faster SQL preserves application business semantics.

Resolve the plugin root two directories above this SKILL.md and use its absolute
`runtime/runTool.js` path. Check Node.js and installed dependencies first; use
`npm ci` in that plugin root when dependencies are missing. Do not request an LLM
API key: Codex supplies the reasoning. Database credentials come from the user's
process environment or an explicitly selected private environment file.

For real database requests, require live evidence with
`CODEXDB_REQUIRE_LIVE_CONNECTION=true`. Never present mock samples, heuristic
scores, generated runbooks, or estimated improvements as measured facts. Report
connection failures and missing evidence explicitly. Start with read-only analysis;
do not execute generated writes without the user's authorization.

Use JSON via stdin (`runTool.js advisor_workflow -`) for structured inputs.
Keep persistent state outside the plugin cache using `CODEXDB_STATE_DIR`.

## Standard workflow

Use `collect_blocking_frame` for a real PostgreSQL frame with explicit `engine`,
`systemId`, `database`, and optional `connectionProfile`. Pass the returned `frame`
into `blocking_timeline` along with earlier frames from the same scope. The tool
captures session starts and pg_blocking_pids, not SQL text or usernames. Hidden
identities and excessive session counts fail closed. PID zero remains an unresolved
prepared-transaction blocker. This is on-demand collection; do not start frequent
polling or imply unattended monitoring. SQL Server/MySQL/MariaDB frame collection
is not supported by this c

Preview of the first 4,000 characters. Read full instructions →

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---
name: telemetry-correlation
description: "Correlate deployment, lock, query-plan, and replication telemetry into incident evidence."
---

# Telemetry Correlation

## Use when
- User asks whether a deployment or runtime signal caused a database incident.
- Incident response needs correlated observability evidence.

## Workflow
1. Collect lock, query-plan, and replication signals.
2. Build causal graph and severity summary.
3. Attach OpenTelemetry-compatible references for follow-up.

## Governance
- Use correlation as evidence for triage, not automatic proof.
- Escalate high-severity results through incident and compliance agents.

## Output
- `deploymentId`, `correlation`, `telemetryRefs`

View saved version →

---
name: validate-compliance
description: "Validate planned database operation against GDPR, HIPAA, SOC2, SOX, and ISO27001-aligned checks."
---

# Validate Compliance

## Use when
- Migration, retention, or query policy needs explicit compliance verification.

## Workflow
1. Map action to compliance domains.
2. Check for PII movement, retention conflicts, audit gaps, and access boundary breaches.
3. Generate compliance gap list and mandatory remediation items.
4. Produce approval-ready summary.

## Governance
- Do not auto-approve if any unresolved compliance blocker exists.
- Require explicit acknowledgement of residual risk.

## Output
- `complianceStatus`, `violations`, `requiredFixes`, `approvalChecklist`

View saved version →

---
name: vendor-feature-mapper
description: Maps competitor capabilities to plugin USPs and differentiators.
---

# Vendor Feature Mapper

Run:

```bash
node runtime/runTool.js vendor_feature_mapper '{"vendor":"Redgate","capability":"schema compare and SQL monitor"}'
```

Returns coverage map and differentiators.

View saved version →

---
name: workload-impact-analyzer
description: Rank workload queries by latency, call volume, and CPU impact to identify optimization hotspots.
---

# Workload Impact Analyzer

Run:

```bash
node runtime/runTool.js workload_impact_analyzer '{"queries":[{"queryId":"q1","p95Ms":900,"calls":20,"cpuMs":70}]}'
```

Returns top impact queries and hotspots.

View saved version →

---
name: workload-twin
description: Simulate workload scenarios such as traffic growth, added indexes, dropped indexes, and PII-sensitive workload risk.
---

# Workload Twin

Use this skill to estimate how workload behavior changes under a proposed
traffic or indexing scenario.

Run:

```bash
node runtime/runTool.js workload_twin '{"engine":"postgres","database":"analytics","schema":"public","table":"events","scenario":{"trafficGrowthPct":30,"addIndex":["user_email"],"dropIndex":[]}}'
```

The tool returns baseline and projected p95, scenario findings, and a recommended
experiment.