monzo_spending

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

With no annotations, the description carries the full burden. It discloses the auto-sync side effect, the behavior of account_type in results, and the detail flag's effect. This goes beyond a basic 'what' and informs the agent of important behavioral nuances.

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 concise, front-loaded with the purpose, and uses a structured Args block. Every sentence adds value, covering behavior, parameters, and output characteristics without redundancy.

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?

Despite multiple optional parameters and an output schema, the description covers the essential behavior: auto-sync, output characteristics (account_type echoing), and parameter effects. The presence of an output schema means return values need not be described, and the description is complete for invocation purposes.

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 coverage is 0%, so the description fully compensates. It provides format (YYYY-MM), examples for category, allowed values for account_type, and the effect of detail, making each parameter's meaning clear beyond the schema's bare titles.

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 analyzes spending from cached Monzo transactions, using a specific verb ('Analyse spending') and resource. It distinguishes itself from sibling tools like list_transactions and search_transactions by focusing on aggregated spending analysis rather than raw transaction listing.

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 (cached transactions, auto-sync when stale) and implies when to use it (for spending summaries). It does not explicitly name alternatives or exclusions, but the distinction from sibling tools is evident.

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