Copilot Money MCP

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

The annotations declare readOnlyHint=true, and the description adds valuable behavioral context beyond this: it explains the response structure (including the 'accounts' array), describes how weekly/monthly modes downsample data, and mentions pagination through the limit/offset parameters. This provides useful operational details not covered by the simple read-only annotation.

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 efficiently structured in three sentences that each earn their place: first states the core purpose and response format, second explains the required granularity parameter and its effects, third mentions filtering options. No wasted words, front-loaded with essential information.

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?

For a read-only tool with comprehensive parameter documentation (100% schema coverage) but no output schema, the description provides good context: it explains the response structure, behavioral aspects of granularity modes, and filtering capabilities. The main gap is lack of explicit output format documentation, though the description does list the returned fields.

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 input schema already documents all 6 parameters thoroughly. The description adds some semantic context by explaining that granularity 'controls response size' and that weekly/monthly modes 'downsample by keeping the last data point per period,' but most parameter meaning comes from the schema itself.

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 ('Get daily balance snapshots') and resources ('accounts over time'), distinguishing it from siblings like get_accounts or get_transactions by focusing on historical balance data rather than current accounts or transactions.

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 clear context for when to use the tool (to retrieve balance history with date range and granularity controls) and mentions filtering capabilities. However, it doesn't explicitly state when NOT to use it or name specific alternatives among the sibling tools for different use cases.

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