EVM MCP Server

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

The description adds valuable behavioral context beyond annotations: it explains the performance benefit ('reduces latency and RPC usage'), mentions the underlying implementation ('Uses the Multicall3 contract'), and notes network compatibility ('deployed on all major networks'). While annotations cover safety (readOnlyHint, idempotentHint), the description provides practical implementation details that help the agent understand when this optimization is appropriate.

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 perfectly concise and front-loaded: the first sentence states the core functionality, the second explains benefits, and the third provides implementation context and use cases. Every sentence adds value with zero wasted words, and the structure moves from general to specific.

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 rich annotations (readOnlyHint, idempotentHint) and comprehensive schema coverage, the description provides excellent contextual completeness. It explains the tool's optimization purpose, implementation details, and ideal use cases. The only minor gap is lack of output format explanation (no output schema exists), but the annotations sufficiently indicate safe read behavior.

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?

With 100% schema description coverage, the schema already documents all parameters thoroughly. The description doesn't add specific parameter semantics beyond what's in the schema, but it contextually explains the purpose of batching calls, which helps understand the 'calls' parameter's role. This meets the baseline for high schema coverage.

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 specific verbs ('batch multiple contract read calls') and resources ('single RPC request'), distinguishing it from siblings like read_contract (single call) and write_contract (write operations). It explicitly mentions it's for read operations only, which differentiates it from write tools.

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 explicit guidance on when to use this tool: 'when querying multiple functions' and for specific use cases like 'portfolio analysis, price aggregation, and querying multiple contract states efficiently.' It implicitly distinguishes from read_contract (single calls) and write_contract (write operations) by focusing on batch read optimization.

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