get_weekly_content_package

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

With no annotations, the description carries full disclosure burden. It reveals the content is generated weekly (every Monday) and uses verified data, but doesn't detail potential limitations like update cadence or error handling. It is sufficiently transparent for a read-only content retrieval tool.

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

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

The description is comprehensive but slightly verbose. It front-loads the core purpose and adds context, but some details (e.g., 'every number traces back to a live data source') could be inferred. Still, it remains clear and well-structured.

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

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

Given no output schema, the description adequately explains the return content and frequency. It lacks details on error conditions or empty results, but for a straightforward retrieval tool with no parameters, this is acceptable.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters, and the input schema is empty. The description adds meaning by explaining what the tool returns, which compensates fully for the lack of parameters. Baseline 4 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description explicitly states the tool retrieves a weekly 'Signal of the Week' content package, detailing its components (Substack article, LinkedIn post, Twitter/X thread) and data source. This clearly differentiates it from sibling tools that return raw data.

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

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

The description notes the tool is designed for automated content distribution via Claude Desktop, implying when to use it. However, it does not explicitly state when not to use it or provide alternatives among siblings, leaving some ambiguity.

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