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automatelab-n8n-mcp

Build a replay workflow for one node

execution.replay
Read-onlyIdempotent

Isolates a specific node for debugging by building a replay workflow with pinned input items, eliminating the need to re-run the entire pipeline.

Instructions

Build a self-contained replay workflow that exercises a single node from a larger workflow. The replay workflow is Manual Trigger -> Replay Seed (Code node with pinned items) -> target node. Optional inputItems or an execution payload pins what the target sees. Useful for iterating on one stubborn node without re-running the whole pipeline. Returns workflow JSON ready to import or push via workflow.create.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nodeYesName of the node to replay.
workflowYesOriginal workflow JSON.
executionNoOptional execution payload — pulls real input the target saw last time.
inputItemsNoOptional explicit input items (each becomes `{ json: ... }`).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
workflowYesFull n8n workflow JSON (name, nodes, connections, settings, ...).
item_countYesNumber of input items the replay seed will feed the target.
target_nodeYesName of the node being replayed.
Behavior4/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and idempotentHint=true. The description adds that it returns a workflow JSON ready for import, does not mutate the original workflow, and explains the internal structure, providing good behavioral context beyond annotations.

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 concise, front-loads the action, and each sentence adds value with no wasted words.

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

Completeness4/5

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

Given the schema coverage, annotations, and presence of output schema, the description is largely complete. It explains the workflow structure, parameters, and use case, though it could mention that the node name must exist in the workflow.

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 parameters are documented. The description adds meaning by explaining optional parameters (e.g., inputItems become `{ json: ... }`) and how they affect the output.

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 builds a replay workflow for a single node, specifying the structure (Manual Trigger -> Replay Seed -> target node) and distinguishing it from sibling tools like workflow.create and execution.list.

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 explains it is 'useful for iterating on one stubborn node without re-running the whole pipeline' and mentions optional inputs. However, it does not explicitly state when not to use it or compare to 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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