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Recipe Run

recipe_run
Destructive

Executes a recipe server-side with each step validated, verified, and audited; stops at first failure and reports per-step outcomes. Destructive recipes return a plan with a confirm token.

Instructions

Run a recipe server-side: every step is validated, verified and audited.

Stops at the first failed or unverified step and reports each step's outcome. Destructive recipes first return a plan with a confirm_token.

Input Schema

NameRequiredDescriptionDefault
nameYesRecipe name from recipe_list.
paramsNoRecipe parameters.
dry_runNoPlan only.
verboseNoFull receipts for every step.
confirm_tokenNoFor destructive recipes: token from the planned call.

Output Schema

NameRequiredDescriptionDefault
planNo
stepsNo
recipeYes
statusYes
outputsNo
duration_msNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.2/5.0
Behavior5/5

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

Beyond the annotations, the description discloses important behavior: every step is validated, verified, and audited; execution stops at the first failed or unverified step; outcomes are reported per step; and destructive recipes require a confirm_token from a plan call. This is exactly the kind of behavioral context an agent needs for a potentially destructive tool.

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 three short sentences with no wasted wording. It is front-loaded with the core action and then adds execution and destructive-recipe behavior in a logical order.

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 that an output schema exists, the description need not explain return values. With annotations covering safety hints and 100% schema coverage, the description adds the key behavioral details an agent needs: failure handling, auditing, and the destructive confirmation flow.

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

Parameters4/5

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

Schema coverage is 100%, so the schema already documents all five parameters. The description still adds useful meaning for confirm_token by explaining that destructive recipes first return a plan with that token. It does not elaborate on params, dry_run, or verbose, but the schema carries those details.

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

Purpose4/5

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

The description gives a specific verb and resource: 'Run a recipe server-side'. It clearly explains that the tool executes recipes and validates, verifies, and audits every step. It does not explicitly distinguish this from close siblings such as batch_run or workflow_write, but the core purpose is unambiguous.

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 description implies usage context by explaining that recipes are run server-side and that destructive recipes return a plan first. However, it does not say when to choose recipe_run over batch_run, workflow_write, or other execution-related siblings. The guidance is implicit rather than explicit.

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