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partymola

monzo-mcp

monzo_spending

Analyze Monzo spending by month, category, or account type, with automatic cache refresh. Get category summaries or individual transactions for detailed review.

Instructions

Analyse spending from cached Monzo transactions. Auto-syncs if the cache is stale (last sync before today).

Args: month: Month in YYYY-MM format (default: current month) category: Filter by category, e.g. "groceries", "eating_out", "transport" account_type: "personal" or "joint" (default: all) detail: If true, return individual transactions instead of category summary

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
monthNo
detailNo
categoryNo
account_typeNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations, the description must fully disclose behavior. It reveals auto-sync behavior and the toggle between category summary and individual transactions. No contradictions noted, but it could mention if any side effects (e.g., syncing triggers writes).

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise with a clear structure: a single-line purpose, then a bullet-like list of parameters. No wasted sentences; every word adds value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 4 parameters, no output schema, and no annotations, the description is quite complete. It explains the core functionality (analysis with optional detail) and the auto-sync behavior. However, it does not describe the output format (e.g., list of categories with totals) which is somewhat useful but not critical since output schema exists.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must provide parameter meaning. It explains all four parameters: month format (YYYY-MM), category examples (e.g., groceries), account_type enumeration ('personal' or 'joint'), and detail flag semantics. This adds crucial context beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Analyse spending from cached Monzo transactions,' specifying the verb ('analyse') and resource ('spending'). It also mentions auto-syncing, distinguishing it from siblings like monzo_list_transactions.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for spending analysis and mentions auto-sync, but does not explicitly state when to use this tool versus alternatives (e.g., monzo_search_transactions) or when not to use it. No exclusions or contextual conditions are provided.

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

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