Token-Efficient MCP Server

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool retrieves a report and best practices, implying a read-only operation, but doesn't clarify aspects like authentication needs, rate limits, data freshness, or whether it's a summary or detailed analysis. For a tool with zero annotation coverage, this leaves key behavioral traits unspecified.

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 a single, efficient sentence that directly states the tool's purpose without any fluff or redundancy. It's front-loaded with the core action and resource, making it easy to parse quickly. Every word earns its place, achieving optimal conciseness.

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 the tool has 0 parameters, 100% schema coverage, and no output schema, the description is minimally adequate. It explains what the tool does but lacks details on output format, behavioral constraints, or usage context. For a report-fetching tool with no annotations, it should ideally provide more guidance on what the report contains or how to interpret it.

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 0 parameters, and schema description coverage is 100%, so there are no parameters to document. The description doesn't need to add parameter semantics, and it appropriately avoids mentioning any. A baseline score of 4 is applied as it handles the zero-parameter case correctly without unnecessary details.

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 clearly states the tool's purpose with a specific verb ('Get') and resource ('detailed token savings report and optimization best practices'), making it immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'list_token_efficient_tools' or 'search_tools', which might also relate to token optimization, preventing a perfect score.

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 no guidance on when to use this tool versus alternatives. It doesn't mention context, prerequisites, or exclusions, leaving the agent to infer usage based on the name alone. This lack of explicit direction is a significant gap in helping the agent select the right tool.

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