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RationalBloks

by io.github.rationalbloks
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Deploy to Production

deploy_production

Promote staging to production (requires a paid plan): production's database migrates from the schema it runs to the one staging runs, and production runs staging's build. With staging unchanged since the last promotion, it rebuilds production with no schema change. The operation is ASYNCHRONOUS: poll the returned job_id with get_job_status. A plan that drops data is refused, naming every table, field, entity or relationship it would drop, and every field whose type change rounds or cuts its values (a decimal with a smaller scale or turned integer, a datetime turned date): deploy_destructive applies it, a tool of its own so a client asks before it runs. One operation runs on a project at a time: while another runs, the call is refused and the refusal names the running job; wait for it with get_job_status, then call again. While RationalBloks is being updated, the call is refused with 'RationalBloks is being updated': call it again in a few minutes.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
project_idYesProject ID (UUID)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • removedInput schema / properties / confirm_destructive
      Removed value: -{
-  "description": "Set true only after reviewing the plan: a deploy that drops tables, columns, entities, relationships or fields is refused without it",
-  "type": "boolean"
-}
  2. Changed1 schema field changed
    • addedInput schema / properties / confirm_destructive
      Added value: +{
+  "description": "Set true only after reviewing the plan: a deploy that drops tables, columns, entities, relationships or fields is refused without it",
+  "type": "boolean"
+}
  3. First observed

TDQS

A4.6/5.0
Behavior5/5

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

The description carries the full behavioral load beyond the annotations: it discloses the ASYNCHRONOUS nature and job_id polling, the one-operation-per-project lock with a refusal naming the running job, the RationalBloks maintenance refusal, and how a destructive plan is refused and deferred to another tool. These are real traits not expressed in the annotation flags.

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?

Purpose and the core async/polling behavior are front-loaded, and every sentence carries operational detail. The long parenthesized clauses and dense run-on sentences slightly reduce readability, but little is wasted.

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?

With no output schema, the description still explains the return contract (job_id) and the exact failure/refusal semantics an agent must handle. Nothing an agent needs to invoke or recover correctly is missing.

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

Parameters3/5

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

Only one parameter exists and the schema documents it at 100% coverage (UUID), so the baseline is 3. The description adds no format or constraint detail about project_id beyond what the schema already states.

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?

States a specific verb and resource ('Promote staging to production') and immediately scopes it ('requires a paid plan'). It is clearly distinguishable from siblings like deploy_staging, deploy_graph_production, and deploy_destructive without opening any schema.

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?

Explicitly routes to alternatives: poll with get_job_status, and use deploy_destructive when a plan would drop data. It also names the refusal conditions (concurrent operation, RationalBloks update) and prescribes the recovery action for each.

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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