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SupplyMaven-SCR

SupplyMaven API Pro

Official

get_weekly_content_package

Retrieve weekly marketing content packages with verified supply chain data for automated publishing on Substack, LinkedIn, and Twitter/X.

Instructions

Get the weekly 'Signal of the Week' content package — a pre-written, data-verified marketing bundle generated every Monday from live SupplyMaven data. Returns a Substack article (~500 words), LinkedIn post (~200 words), and Twitter/X thread (4-5 tweets), all built from verified supply chain data. Every number in the content traces back to a live data source. Designed for automated content distribution via Claude Desktop + platform MCP servers. The content package includes the signal headline, full data context (GDI, SMI, commodities, ports, signals), and platform-specific formatted content ready for publishing.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

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 clearly describes what the tool returns (content package with specific formats) and mentions it's data-verified with traceable numbers. However, it doesn't disclose potential limitations like rate limits, authentication requirements, or error conditions that would be important for operational use.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is efficiently structured in two sentences that pack substantial information about what the tool provides, its source, components, and intended use. Every sentence adds value, though it could be slightly more concise by combining some clauses.

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

Completeness3/5

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

For a tool with no parameters, no annotations, and no output schema, the description does a reasonable job explaining what it returns. However, it lacks details about the return structure, potential errors, or how to handle the content package programmatically, which would be helpful given the complexity of the multi-format output.

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 tool has 0 parameters with 100% schema description coverage, so the baseline is 4. The description appropriately doesn't discuss parameters since none exist, focusing instead on what the tool delivers.

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 the tool retrieves a specific weekly content package ('Signal of the Week') with detailed components (Substack article, LinkedIn post, Twitter/X thread) and emphasizes it's built from verified supply chain data. It distinguishes from siblings by focusing on pre-packaged marketing content rather than raw data monitoring or alerts.

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 the content is generated every Monday and designed for automated content distribution via Claude Desktop + platform MCP servers, providing clear context for when to use it. However, it doesn't specify when NOT to use it or mention alternatives among the many sibling tools.

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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