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fork_from_failure

Fork failed workflows from a chosen step or last failure to re-execute after a fix, reusing recorded outputs of prior steps.

Instructions

Fork multiple failed workflows from a specific point.

Creates new workflows that re-execute from a chosen point, reusing the recorded outputs of all prior steps. Useful for retrying a batch of failed workflows after deploying a fix.

IMPORTANT: You must set exactly one of from_last_failure, from_last_step, from_step, or from_step_name.

Args: application_name (string, required): Name of the DBOS application workflow_ids (array of strings, required): IDs of the workflows to fork application_version (string, optional): Application version for the new workflows (defaults to current version) queue_name (string, optional): Enqueue the forked workflows onto this queue queue_partition_key (string, optional): Partition key for the queue from_last_failure (bool, optional): Fork from the last failed step (default: false) from_last_step (bool, optional): Fork from the last executed step (default: false) from_step (int, optional): Fork from this specific step number from_step_name (string, optional): Fork from the step with this function name

Returns: workflow_ids (array of strings): IDs of the newly created forked workflows count (int): Number of workflows forked

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
from_stepNo
queue_nameNo
workflow_idsYes
from_last_stepNo
from_step_nameNo
application_nameYes
from_last_failureNo
application_versionNo
queue_partition_keyNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

Without annotations, the description takes on the full burden. It clearly discloses that new workflows are created, prior step outputs are reused, and exactly one of the from_* parameters must be set. It does not mention permissions, reversibility, or effects on the original workflows, but core behavior is transparent and there is no contradiction.

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 front-loaded with a clear summary, followed by a succinct usage context, a complete parameter list, and return value explanation. Each sentence earns its place without redundancy.

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 tool's complexity (9 parameters, no annotations), the description covers purpose, usage, parameters, and return values. It lacks edge-case behaviors like error conditions or prerequisites, but the presence of an output schema and detailed Args make it largely complete.

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

Parameters5/5

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

The description provides a detailed Args section explaining every parameter, including defaults and semantics, such as 'application_version' defaulting to the current version and 'queue_name' enqueueing forked workflows. This fully compensates for the 0% schema description coverage.

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 opens with 'Fork multiple failed workflows from a specific point' and elaborates 'Creates new workflows that re-execute from a chosen point, reusing the recorded outputs of all prior steps.' This clearly identifies the verb, resource, and scope, distinguishing it from singular fork_workflow or resume_workflow.

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 explicitly states 'Useful for retrying a batch of failed workflows after deploying a fix' and enforces a critical constraint on the from_* parameters. However, it does not name alternative tools or provide when-not-to-use guidance, so it stops short of a 5.

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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