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by io.github.pipeworx-io
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Li Get Campaign

li_get_campaign
Read-onlyIdempotent

Get full details for a specific LinkedIn campaign (e.g., campaign ID "501234567"). Returns name, budget, spend, status, targeting, and performance metrics.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
campaign_idYesCampaign ID

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
idNoCampaign ID
nameNoCampaign name
errorNoError code if connection not found
spendNoCampaign spend details
budgetNoCampaign budget details
statusNoCampaign status
endDateNoCampaign end date
messageNoError message with guidance
startDateNoCampaign start date
targetingNoCampaign targeting parameters

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "properties": {
+    "budget": {
+      "description": "Campaign budget details",
+      "properties": {
+        "amount": {
+          "description": "Budget amount",
+          "type": "number"
+        },
+        "currencyCode": {
+          "description": "Currency code",
+          "type": "string"
+        }
+      },
+      "type": "object"
+    },
+    "endDate": {
+      "description": "Campaign end date",
+      "properties": {
+        "day": {
+          "type": "number"
+        },
+        "month": {
+          "type": "number"
+        },
+        "year": {
+          "type": "number"
+        }
+      },
+      "type": "object"
+    },
+    "error": {
+      "description": "Error code if connection not found",
+      "type": "string"
+    },
+    "id": {
+      "description": "Campaign ID",
+      "type": "string"
+    },
+    "message": {
+      "description": "Error message with guidance",
+      "type": "string"
+    },
+    "name": {
+      "description": "Campaign name",
+      "type": "string"
+    },
+    "spend": {
+      "description": "Campaign spend details",
+      "properties": {
+        "amount": {
+          "description": "Spend amount",
+          "type": "number"
+        },
+        "currencyCode": {
+          "description": "Currency code",
+          "type": "string"
+        }
+      },
+      "type": "object"
+    },
+    "startDate": {
+      "description": "Campaign start date",
+      "properties": {
+        "day": {
+          "type": "number"
+        },
+        "month": {
+          "type": "number"
+        },
+        "year": {
+          "type": "number"
+        }
+      },
+      "type": "object"
+    },
+    "status": {
+      "description": "Campaign status",
+      "type": "string"
+    },
+    "targeting": {
+      "description": "Campaign targeting parameters",
+      "type": "object"
+    }
+  },
+  "type": "object"
+}
  2. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "campaign_id": "501234567"
+  }
+]
  3. First observed

TDQS

A4.2/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint (false). The description adds that the tool returns specific fields like budget and performance metrics, which provides context beyond annotations but does not disclose behavioral nuances like rate limits or auth requirements. With strong annotations, a score of 3 is appropriate.

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 a single, concise sentence that front-loads the purpose and includes an example. Every word adds value, with no redundant or filler content.

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 simplicity (one parameter), the presence of an output schema, and thorough annotations, the description is nearly complete. It lists key return fields, but could optionally mention pagination or error handling for edge cases.

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?

The only parameter, campaign_id, has full schema coverage (100%). The description adds an example of the format ('501234567'), which clarifies what a campaign ID looks like beyond the schema's generic 'Campaign ID' description.

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 that the tool retrieves full details for a specific LinkedIn campaign, listing example fields (name, budget, spend, status, targeting, performance metrics). It uses a specific verb ('Get') and resource ('LinkedIn campaign'), and distinguishes from sibling tools like 'li_list_campaigns'.

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 specifies when to use the tool (to get full details of a specific campaign) and provides an example campaign ID. It implicitly differentiates from listing tools, but lacks explicit when-not-to-use guidance or alternative tool references.

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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