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

With no annotations, the description carries the burden of behavioral disclosure. It explains that the package is pre-written, data-verified, and generated from live SupplyMaven data, and that every number traces back to a live source. It does not mention rate limits or side effects, but the described behavior is non-destructive and well-documented.

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 composed of four sentences, each adding meaningful detail: purpose, contents, data verification, and usage context. It is appropriately sized and front-loaded with the verb+resource, though slightly verbose in enumerating every data context element.

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?

No output schema exists, so the description must explain return values. It does so comprehensively, covering the article formats, word counts, tweet count, and the inclusion of signal headline and data context. It is complete enough for an agent to know what to expect, though it could specify whether return is raw text or file paths.

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, so the schema is trivially covered at 100%. The description goes beyond schema by detailing exactly what the returned content includes (headline, data context, platform-specific formats), adding value for a parameterless tool.

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 opens with a specific verb ('Get') and identifies the resource as the weekly 'Signal of the Week' content package. It clearly differentiates from sibling data-retrieval tools by specifying that it returns a marketing bundle (Substack, LinkedIn, Twitter/X) rather than raw data, making its purpose unmistakable.

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 provides clear context: it is generated every Monday and is designed for automated content distribution via Claude Desktop + platform MCP servers. This implies when to use it, but it does not explicitly name alternatives or exclusion criteria, stopping short of a full 5.

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