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anythink-cloud

Anythink-MCP

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Workflows: trigger

workflows_trigger

Start a workflow run now without waiting for its result, then check the outcome with workflows_jobs. Provide entity and optional payload.

Instructions

Manually trigger a workflow. Starts a run now and returns without the run's result; check the outcome with workflows_jobs. A Manual-trigger workflow needs entity (and entity_id for a specific record), and payload is a JSON object the steps read as $anythink.trigger.data.

Input Schema

NameRequiredDescriptionDefault
idYesWorkflow ID. Find it with workflows_list.
entityNoEntity name for the trigger (required for Manual-trigger workflows)
payloadNoOptional JSON record to pass to the workflow (available as $anythink.trigger.data)
entity_idNoOptional entity/record id to associate with the trigger

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.2.37
    • changedInput schema / properties / id / description
      Previous value: -"Workflow ID"New value: +"Workflow ID. Find it with workflows_list."
  2. Addedv0.2.27

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare the non-read-only, non-destructive, open-world profile, so the bar is lower. The description still adds important behavior beyond them: the call is asynchronous and returns without the run's result, which materially shapes how an agent sequences follow-up calls. It doesn't cover permissions or rate limits.

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?

Three short sentences, front-loaded with the action and effect, then the async caveat, then the input requirements. No filler or restated title.

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?

With no output schema, the description correctly explains what comes back (no run result) and where to get it, which is the main completeness risk for this tool. Minor gap: the schema types payload as a string while the description calls it 'a JSON object', which could confuse how the value is encoded.

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 baseline is 3. The description goes slightly beyond the per-property text by framing the conditional relationship between trigger type and the entity/entity_id pair, and reiterating that payload is read as $anythink.trigger.data.

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?

States a specific verb+resource ('Manually trigger a workflow') and immediately describes the effect ('Starts a run now'). It is clearly distinguishable from siblings like workflows_list, workflows_create, and workflows_jobs, and even names the sibling to use for results.

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?

Tells the agent what to do after triggering ('check the outcome with workflows_jobs') and states the prerequisite for Manual-trigger workflows (entity, plus entity_id for a specific record). It lacks an explicit when-not-to-use or trigger-type-exclusion statement, but the guidance is concrete and conditional.

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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