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Retrieve automation run history

get_run_history
Read-onlyIdempotent

Retrieve the 10 most recent runs for a Gumloop automation by workbook or saved item. Use it to review past execution outcomes and debug failures.

Instructions

This endpoint retrieves the run history for automations, either by workbook or saved item. Returns the 10 most recent runs. Read operation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
accountNoNamed private Gumloop account; selects private credentials and user/team identity.
user_idNoThe user ID. Required if project_id is not provided.
project_idNoThe project ID. Required if user_id is not provided.
workbook_idNoThe ID of the workbook to retrieve run history for. Required if saved_item_id is not provided.
saved_item_idNoThe ID of the saved item to retrieve run history for. Required if workbook_id is not provided.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.0.1

TDQS

B3.2/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, so the 'Read operation.' sentence is redundant with structured data. However, the description does add a genuinely useful behavioral detail not in the annotations: it returns only the 10 most recent runs, which is a meaningful limit an agent must know. No pagination or auth details are disclosed.

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?

Three short sentences, front-loaded with purpose, followed by the key return limit. The final 'Read operation.' sentence is redundant given the annotations and slightly dilutes efficiency, but the description is otherwise tight with no waste.

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?

For a read tool with full annotation coverage and a 100%-documented schema, the description is adequate. It covers purpose, the two lookup modes, and a return limit. It doesn't address pagination, whether the 10-run cap is configurable, or error cases, but these are minor given the structured data already present.

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%, so the schema already fully documents all 5 parameters including the conditional requirements (user_id or project_id; workbook_id or saved_item_id). The description adds no parameter semantics beyond what the schema provides, so the baseline of 3 applies.

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 states a clear verb+resource: 'retrieves the run history for automations, either by workbook or saved item.' This distinguishes it from sibling get_run_details (which presumably returns a single run) and from list_flows/list_workbooks. It doesn't explicitly name those siblings, so it stops short of a 5.

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 is given on when to use this tool versus alternatives like get_run_details or list_flows. The description mentions two lookup modes (workbook or saved item) but doesn't explain when to prefer one or what prerequisites apply. No when-not-to-use context.

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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