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slouchd

CyberChef API MCP Server

by slouchd

batch_bake_recipe

Apply a series of operations to multiple data inputs in a batch. Use a recipe to transform each input item through the defined steps.

Instructions

Bake (execute) a recipe (a list of operations) in order to derive an outcome from a batch of input data

:param batch_input_data: the batch of data in which to perform the recipe operation(s) on
:param recipe: a list of operations to 'bake'/execute on the input data
:return:

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
batch_input_dataYes
recipeYes
Behavior2/5

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

No annotations provided, so the description carries the full burden. It states it executes/derives outcomes but does not disclose side effects, permissions required, error handling, or return behavior. For a mutation tool, this is insufficient.

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?

Reasonably concise with a clear purpose statement followed by parameter descriptions. The docstring style is appropriate, though the :param lines are somewhat redundant with the schema.

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

Completeness2/5

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

Missing critical context: no output schema, no error behavior, no mention of batch vs single differences. Given the complexity of executing recipes on batches, more detail is needed to ensure correct usage.

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 coverage is 0%, so the description adds value by explaining parameters: 'batch_input_data' as the batch to operate on, 'recipe' as a list of operations. However, it lacks details like allowable data types (already in schema) or constraints on recipe structure.

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 clearly states it bakes/executes a recipe on batch input data. The verb 'Bake' is specific, and the resource 'recipe' is well-defined. However, it does not explicitly differentiate from sibling tools like 'bake_recipe' (single vs batch).

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

Usage Guidelines2/5

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

No guidance on when to use this tool versus its siblings (bake_recipe, perform_magic_operation). Lacks context for appropriate invocation scenarios or alternatives.

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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