system_reset_cache

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

With no annotations provided, the description carries full responsibility. It thoroughly explains the action (clear all cache), the consequences (forces fresh API requests, temporary performance impact), the return value (number of cleared entries, with response fields), and provides caution. This is comprehensive and transparent.

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 well-structured with a clear main sentence, bullet points for use cases, a caution, and response details. It is somewhat long but every sentence adds value. It front-loads the core action, making it efficient for scanning.

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 fully explains return values (message, previousSize, timestamp). It also covers use cases, caution, and the nature of the operation. It is complete for the tool's simplicity.

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 input schema has no parameters, and schema description coverage is 100% (trivially). The description does not add parameter semantics because none exist. According to the rubric, when coverage is high, baseline is 3.

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 'Clear all cached data from the MCP server,' providing a specific verb ('Clear') and resource ('cached data'). It distinguishes itself from sibling tools, which focus on CRUD operations for entities like activities, deals, etc., by being the only cache management tool.

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 explicitly lists use cases ('Debugging cache-related issues', 'Forcing refresh of stale data', etc.) and includes a CAUTION about performance impact. It does not mention when not to use it, but the context is clear enough for an AI agent to decide appropriately, given no alternative for cache reset.

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