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osherai

AgencyAnalytics MCP Server

by osherai

create_campaign

Create a new client campaign in AgencyAnalytics using a website URL and company name, and get back the campaign data.

Instructions

Create a new campaign (client) in AgencyAnalytics.

Args: url: The website URL for the campaign company: The company/client name

Returns: JSON object with created campaign data

Examples: - create_campaign(url="https://example.com", company="Acme Corp")

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYes
companyYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

With no annotations provided, the description carries the full burden. It discloses that it creates a campaign and returns a JSON object, and gives an example. However, it omits behavioral details such as potential errors, idempotency, or authentication requirements. This is adequate but not rich.

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 well-structured with a summary line, Args, Returns, and Examples sections. Every sentence provides useful information, and there is no redundancy or fluff. It is appropriately sized for the tool's complexity.

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?

For a simple create tool with two parameters, the description is nearly complete: it specifies the arguments, return type, and an example. Given that an output schema exists, return details are not needed. The only minor gap is ambiguity around 'campaign (client)' and lack of edge-case handling, but overall it is sufficient.

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 input schema has 0% description coverage, only providing titles 'Url' and 'Company'. The description compensates fully by explaining 'url: The website URL for the campaign' and 'company: The company/client name', and also provides a concrete example. This adds clear meaning beyond the schema.

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 'Create a new campaign (client) in AgencyAnalytics' with a specific verb and resource, distinguishing it from sibling tools like update_campaign, delete_campaign, and get_campaign. The parenthetical '(client)' adds useful context.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides an example call and clearly indicates the action (create new campaign), so when to use it is implied. However, it does not explicitly mention alternatives or when not to use it (e.g., for updating existing campaigns use update_campaign).

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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