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by plori-ai

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JavaScript

Remote

Get workflow

get_workflow

Read-only

Retrieve a workflow's metadata and step projection to see the exact version pinned for execution, falling back to the current draft if not activated. Clarify which version runs before triggering.

Instructions

Get one workflow's metadata and step projection. The projection is the version pinned for execution (active_version), falling back to current_version for a draft that has not been activated.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`workflow_id`	Yes	The workflow's UUID (from list_workflows or create_workflow).

Output Schema

TableJSON Schema

Name	Required	Description
`id`	Yes
`name`	Yes
`engine`	Yes
`status`	Yes
`user_id`	Yes
`agent_id`	Yes
`hook_key`	Yes
`cron_expr`	Yes
`created_at`	Yes
`projection`	Yes	Arbitrary JSON owned by the producing engine.
`updated_at`	Yes
`description`	Yes
`notify_pref`	Yes
`next_fire_at`	Yes
`trigger_kind`	Yes
`paused_reason`	No
`template_slug`	No
`active_version`	Yes
`current_version`	Yes
`spend_cap_month`	Yes
`agent_deleted_at`	No

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedv0.16.0Sep 19, 2026

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "properties": {
+    "active_version": {
+      "maximum": 2147483647,
+      "minimum": -2147483648,
+      "type": [
+        "null",
+        "integer"
+      ]
+    },
+    "agent_deleted_at": {
+      "type": [
+        "null",
+        "string"
+      ]
+    },
+    "agent_id": {
+      "type": [
+        "null",
+        "string"
+      ]
+    },
+    "created_at": {
+      "type": "string"
+    },
+    "cron_expr": {
+      "type": "string"
+    },
+    "current_version": {
+      "maximum": 2147483647,
+      "minimum": -2147483648,
+      "type": "integer"
+    },
+    "description": {
+      "type": "string"
+    },
+    "engine": {
+      "type": "string"
+    },
+    "hook_key": {
+      "type": [
+        "null",
+        "string"
+      ]
+    },
+    "id": {
+      "type": "string"
+    },
+    "name": {
+      "type": "string"
+    },
+    "next_fire_at": {
+      "type": [
+        "null",
+        "string"
+      ]
+    },
+    "notify_pref": {
+      "type": "string"
+    },
+    "paused_reason": {
+      "type": "string"
+    },
+    "projection": {
+      "description": "Arbitrary JSON owned by the producing engine."
+    },
+    "spend_cap_month": {
+      "type": "integer"
+    },
+    "status": {
+      "type": "string"
+    },
+    "template_slug": {
+      "type": "string"
+    },
+    "trigger_kind": {
+      "type": "string"
+    },
+    "updated_at": {
+      "type": "string"
+    },
+    "user_id": {
+      "type": "string"
+    }
+  },
+  "required": [
+    "id",
+    "user_id",
+    "agent_id",
+    "name",
+    "description",
+    "engine",
+    "status",
+    "current_version",
+    "active_version",
+    "trigger_kind",
+    "cron_expr",
+    "next_fire_at",
+    "hook_key",
+    "spend_cap_month",
+    "notify_pref",
+    "created_at",
+    "updated_at",
+    "projection"
+  ],
+  "type": "object"
+}

Addedv0.7.0Aug 9, 2026

TDQS

A4.3/5.0

Behavior4/5

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

Annotations already declare readOnlyHint=true, so the agent knows it is a safe read operation. The description adds valuable behavioral context: it explains the projection selection logic (active_version pinned for execution, with current_version fallback for drafts), which goes beyond the annotation and helps the agent understand what data will be returned.

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 two sentences with zero redundancy. The core purpose is front-loaded, followed by a clarifying explanation of the projection behavior. Every word earns its place, making it exceptionally concise and structured.

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

Completeness5/5

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

With a single parameter, full schema coverage, presence of an output schema, and annotations covering the read-only safety profile, the description covers all essential aspects. The fallback logic for projections is explained, and nothing an agent needs to call the tool correctly is missing.

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 parameter 'workflow_id' is fully documented in the schema, including its source (list_workflows or create_workflow). The tool description adds no additional parameter guidance beyond the schema, so the baseline of 3 is appropriate.

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 states a specific verb ('Get') and resource ('one workflow's metadata and step projection'), and the projection is clearly defined. It distinguishes itself from siblings like list_workflows (which lists all) and get_workflow_version (which fetches a specific version) by focusing on the active execution projection.

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 clearly indicates when to use this tool (to retrieve metadata and the projection used for execution) and provides context on the projection fallback behavior. It does not explicitly name alternatives or exclusions, but the sibling list and context imply use cases, so it earns a 4 rather than a 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.