cache_stats
Retrieve metadata cache statistics to monitor cache performance, detect misses, and guide tuning for AI agent tool calls.
Instructions
Metadata cache statistics.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Retrieve metadata cache statistics to monitor cache performance, detect misses, and guide tuning for AI agent tool calls.
Metadata cache statistics.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered by structured data. The description adds nothing beyond that: it does not say whether the call is cheap, whether it reflects live or cached state, or what kind of counts are reported. With annotations in place the bar is lower, but no added behavioral context is present.
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?
It is a single four-word fragment with no waste, but it is under-specified rather than genuinely concise. There is no front-loaded verb or scope statement to anchor the reader.
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?
There is no output schema, so the description carries the burden of conveying what the statistics contain. For a diagnostic tool with no annotations describing its return shape, 'statistics' is too thin to tell an agent what it will receive or whether the result is worth requesting.
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 takes zero parameters, which is the baseline-4 case per the rubric. The description correctly implies no input is needed, and there is no parameter surface to misdescribe.
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 fragment 'Metadata cache statistics' names a resource (the metadata cache) and the kind of data returned (statistics), but supplies no verb and does not specify what 'statistics' means. It is distinguishable from write siblings like create_record, but not clearly distinguished from the nearest sibling, server_status.
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?
There is no statement of when to call this tool, when not to, or how it relates to alternatives such as server_status or model_info. The agent is left to infer that this is a diagnostic/introspection call.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.