get_money_supply_data_month

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

No annotations are provided, so the description carries the full burden. It states the tool fetches data and returns a markdown table or error, but lacks critical behavioral details: it doesn't specify data sources, update frequency, rate limits, authentication needs, error conditions beyond generic 'error message', or whether the date range is inclusive/exclusive. For a data-fetching tool with no annotations, this is insufficient.

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 clear sections (purpose, args, returns) and uses minimal sentences. Every sentence adds value: the first states the purpose, the next two document parameters, and the last specifies the return format. It could be slightly more concise by integrating parameter details into a single sentence, but it's efficiently front-loaded.

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 moderate complexity (2 optional parameters, no annotations, but has output schema), the description is partially complete. It covers purpose and parameters well, and the output schema likely handles return values, so the description doesn't need to detail the table structure. However, it lacks behavioral context (e.g., data freshness, error specifics) and usage guidelines, leaving gaps for an AI agent.

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?

Schema description coverage is 0%, so the description must compensate. It explicitly documents both parameters (start_date, end_date) with format details ('YYYY-MM'), optionality, and their role in defining the date range. This adds significant value beyond the bare schema, though it doesn't explain default behavior when parameters are null or how missing dates are handled.

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 fetches monthly money supply data (M0, M1, M2) within a date range, providing a specific verb ('fetches') and resource ('monthly money supply data'). It distinguishes from sibling 'get_money_supply_data_year' by specifying 'monthly' versus 'yearly', but doesn't explicitly differentiate from other data-fetching siblings like 'get_balance_data' or 'get_cash_flow_data' beyond the data type.

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 sibling tools like 'get_money_supply_data_year' for yearly data or other financial data tools, nor does it specify prerequisites, constraints, or typical use cases beyond the basic functionality.

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