Snowfakery MCP Server

iterative_recipe_gen

Iteratively draft, validate, and correct Snowfakery recipes until a valid version is produced, using the language model to fix errors.

Instructions

Create a recipe iteratively with validation.

This tool uses the LLM (via sampling) to draft a Snowfakery recipe, validates it, and if it fails, asks the LLM to fix it. Returns the final valid recipe or the last attempt.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "goal": "<goal>"
    },
    "name": "iterative_recipe_gen"
  }
}

Input Schema

Name	Required	Description	Default
`goal`	Yes
`max_iterations`	No

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Jul 17, 2026

TDQS

A3.9/5.0

Behavior4/5

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

Discloses LLM usage, validation, and retry behavior; no annotations to contradict. Adds value beyond the openWorldHint.

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?

Concise but could be tighter; two sentences plus bullet-like format is efficient.

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?

Covers main flow but lacks details on parameter roles and failure behavior; output schema exists but is not shown.

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

Parameters2/5

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

Schema has 0% description coverage and the description does not explain the 'max_iterations' parameter meaning or the role of 'goal' beyond implied intent.

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 tool creates a recipe iteratively with validation, and distinguishes it from sibling tools like validate_recipe and run_recipe.

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?

The description implies usage for iterative recipe generation, but lacks explicit when-not or alternatives compared to siblings.

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

Deploy Server