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Simba MCP Server

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by getsimba-ai

Validate Study Recipe

validate_study_recipe
Read-onlyIdempotent

Validate a study recipe before execution to resolve effective settings and provenance limits. Catch errors early without creating a run.

Instructions

Resolve and validate a recipe without creating a run. Returns effective settings and provenance limits.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
specificationYesBackend recipe envelope. api_mmm requires request; model_snapshot requires model_hash and is review-only. Unknown fields are forwarded for backend validation.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.5.0

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the description does not need to restate safety. It adds value by specifying 'without creating a run' (a behavior beyond mere read-only) and by describing the output ('returns effective settings and provenance limits'). This provides useful context beyond what annotations convey, without contradiction.

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

Conciseness5/5

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

The description is a single, efficient sentence that front-loads the primary action ('Resolve and validate a recipe') and immediately states the key differentiator ('without creating a run') and the output. Every word earns its place; no filler.

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

Completeness3/5

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

The tool has a single parameter with rich schema documentation and an output schema exists, which covers structural details. However, the description lacks explicit usage guidance (when to call this vs. related recipe tools) and does not clarify what 'resolve' or 'provenance limits' entail beyond the output mention. For a tool with nested parameters, this is a modest gap.

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?

Schema description coverage is 100% – the nested 'specification' parameter is thoroughly documented in the schema (explaining kind, request, model_hash, and the open-world behavior). The tool description itself adds no parameter-level detail. Since the schema carries the full burden, a baseline of 3 is appropriate.

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 clearly states the verb 'resolve and validate' on the resource 'recipe' and explicitly distinguishes it from creating a run, which is a distinct action. It also mentions the return value (effective settings and provenance limits), making the tool's purpose unambiguous. There is no other validation tool among the siblings, so no confusion with alternatives.

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

Usage Guidelines3/5

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

The phrase 'without creating a run' implies this tool is for validation before executing a run, but it does not explicitly state when to use it versus other recipe-related tools (e.g., create_study_recipe, revise_study_recipe). No alternatives or exclusion criteria are mentioned. The usage is implied rather than clearly prescribed.

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