MCP Datastore 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 only states what the tool does operationally, without mentioning whether it's read-only or mutating (though 'run' suggests read-only), performance characteristics, error conditions, authentication needs, or output format. For a query tool with 4 parameters and no output schema, this leaves significant behavioral gaps.

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 unnecessary words. It's appropriately sized for a tool with clear parameters documented elsewhere, and the information is front-loaded with no wasted verbiage.

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's complexity (aggregation operations with filters and namespaces), lack of annotations, and absence of an output schema, the description is insufficient. It doesn't explain what the tool returns (aggregation results), how errors are handled, or performance implications. For a data query tool with multiple parameters and no structured output documentation, more contextual information is needed.

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 description mentions 'aggregation query (count, sum, avg)' which aligns with the 'aggregations' parameter's enum values, adding minimal context beyond the 100% schema coverage. It doesn't explain the relationship between parameters (e.g., how filters apply before aggregation) or provide examples. With complete schema documentation, the baseline is 3, and the description adds only slight value.

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: 'Run an aggregation query (count, sum, avg) on Datastore entities'. It specifies the verb ('run'), resource ('Datastore entities'), and operation type ('aggregation query'), distinguishing it from siblings like datastore_query (likely general queries) and datastore_get (single entity retrieval). However, it doesn't explicitly differentiate from datastore_query beyond mentioning aggregation types.

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 when to choose aggregation queries over regular queries (datastore_query) or other siblings like datastore_listKinds. There's no context about use cases, prerequisites, or exclusions, leaving the agent with no usage direction beyond the basic purpose statement.

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