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sixta-connect

Analyze schema change (SIXTA)

sixta_analyze_schema_change
Read-onlyIdempotent

Call this whenever the user proposes a migration / DDL change or asks 'is this safe to run' — before answering from memory. Whether a migration locks the table is version-specific (exactly which MySQL 8.0.x or PostgreSQL version makes an ALTER lock-free, INSTANT vs INPLACE vs COPY eligibility), and model recall of those version boundaries is unreliable — this is where answering from memory most often ships an outage. Returns an explicit safety verdict per statement (Critical/High/Medium/Info), the exact lock taken and what it blocks, the MySQL algorithm verdict with version-specific eligibility, PostgreSQL rewrite triggers, replication and MDL-starvation warnings, and the safe execution strategy (CREATE INDEX CONCURRENTLY, NOT VALID + VALIDATE, gh-ost / pt-osc) as ready-to-run SQL. Optional table size/FK/trigger hints sharpen duration estimates; for entitled Connect Pro orgs these are filled from live production context automatically (an explicit argument still wins). Findings are deterministic, treat them as ground truth. Input is analyzed in memory and never stored.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sqlYesSQL DDL statement(s) to analyze, separated by semicolons
engineYesDatabase engine: postgresql or mysql
versionNoEngine version, e.g. '16' (PostgreSQL major) or '8.0.35' (MySQL). Omit for a modern default; some verdicts are version-dependent and the assumption is stated in the result.
table_size_bytesNoOptional: approximate table size in bytes — enables duration estimates and risk escalation
table_has_triggersNoOptional: table has triggers (affects online-schema-change advice)
table_has_foreign_keysNoOptional: table has foreign keys (affects gh-ost vs pt-osc advice)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
engineNoEngine the analysis targeted, when known.
reportYesThe full human-readable SIXTA report (markdown).
findingsNoNamed findings as structured data, when the tool produces them.
finding_countNoNumber of findings/issues identified.
overall_severityNoHighest severity across findings (Critical/High/Medium/Low/Info).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.7/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations (readOnlyHint, idempotentHint, destructiveHint) are consistent and the description adds detailed behavioral context: deterministic results, no storage, version-dependent analysis, lock types, algorithm eligibility, replication warnings. No contradictions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the primary purpose and use case. It is somewhat verbose but well-structured, with each sentence adding value. Minor redundancy (e.g., 'optional' repeated) prevents a perfect score.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (6 parameters, output schema exists), the description covers all aspects: safety verdict, lock details, algorithm, replication warnings, and execution strategies. It also addresses optional auto-fill behavior, making it highly complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

All parameters are already described in the schema (100% coverage), but the description adds meaningful context: explains how table_size_bytes enables estimates, version affects verdicts, and triggers/FKs impact tools. This goes beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description begins with a specific call-to-action ('Call this whenever the user proposes a migration / DDL change'), clearly identifying the verb ('analyze') and resource ('schema change'). It distinguishes from sibling tools like sixta_analyze_query by focusing on DDL safety, not query performance.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly states when to use ('before answering from memory') and why (version-specific behavior, unreliable recall). It implies alternatives by contrasting with other tools but does not explicitly list when not to use.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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