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by io.github.rationalbloks
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Update Schema

update_schema
Idempotent

Update a project's schema (saves to database, does NOT deploy).

⚠️ CRITICAL: Follow ALL rules from create_project: • FLAT format (no 'fields' nesting) • string: max_length (default 255) • decimal: precision + scale (default 10, 2) • Use "datetime" NOT "timestamp" • DON'T define: id, created_at, updated_at • NEVER create users/customers/employees tables (use app_users)

⚠️ MIGRATION RULES: • New fields MUST be "required": false OR have "default" value • Cannot add required field without default to existing tables • Safe: {new_field: {type: "string", max_length: 100, required: false}}

WORKFLOW:

  1. Use get_schema to see current schema

  2. Modify following ALL rules

  3. (optional) Call update_schema with dry_run=true to preview the migration first

  4. Call update_schema (saves only)

  5. Call deploy_staging to apply changes

  6. Monitor with get_job_status

DRY RUN: pass dry_run=true to preview what a deploy WOULD change — renames, drops, creates — without saving or deploying anything. The response flags destructive operations (dropped tables/columns) so you can review before applying.

NOTE: Without dry_run this only saves the schema. You MUST call deploy_staging afterwards to apply changes.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
schemaYesNew JSON schema in FLAT format (table_name → field_name → properties). Every field MUST have a 'type' property.
dry_runNoPreview the planned migration (renames/drops/creates) without saving or deploying. Nothing is applied.
project_idYesProject ID (UUID)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / dry_run
      Added value: +{
+  "description": "Preview the planned migration (renames/drops/creates) without saving or deploying. Nothing is applied.",
+  "type": "boolean"
+}
  2. First observed

TDQS

A4.9/5.0
Behavior5/5

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

The description discloses the persistence side effect ('saves to database'), the non-deployment behavior, dry_run behavior (preview without saving/deploying), and the migration risk of adding required fields without defaults. It also states that deploy_staging must be called afterward to apply changes. This goes well beyond what the annotations provide, and no contradiction exists.

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 and well-structured into CRITICAL, MIGRATION RULES, WORKFLOW, DRY RUN, and NOTE blocks. It is somewhat long and repeats the 'does not deploy / must call deploy_staging' message several times, but that repetition is justified given the risk of misuse. No section is extraneous.

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?

For a complex tool with nested object parameters and no output schema, the description covers the full operating context: how to inspect current state, how to preview changes safely, what constraints apply, what side effects occur, and what to do after saving. Nothing essential for correct invocation is missing.

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?

The input schema already describes all three parameters at 100% coverage, and the description adds substantial meaning on top: FLAT format, no 'fields' nesting, type-specific defaults, prohibited fields/tables, and the required/default migration rule. The dry_run parameter's behavior is also explained in context. This is far richer than the schema alone.

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 first sentence states the exact operation: update a project's schema, with the critical distinction that it saves to the database but does NOT deploy. This clearly separates it from deploy_staging and from the graph-related sibling tools. The follow-up rules about FLAT format and migration constraints reinforce that this is the project schema-update tool.

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

Usage Guidelines5/5

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

The WORKFLOW section explicitly orders the steps: get_schema first, optionally dry-run, then update_schema, then deploy_staging, then get_job_status. It names the sibling tools and tells the agent exactly when to use dry_run and when deployment is required. This is explicit when-to-use versus alternatives guidance.

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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