PocketLedger MCP

Get spending report

get_report

Read-onlyIdempotent

Return a grouped expense spending report by category, merchant, day, week, month, or currency, with chart-ready structured data. Do not use the natural-language query as a keyword filter.

Input Schema

TableJSON Schema

Name	Required	Description
`query`	No	Optional natural-language report intent for display/context only.
`period`	No	Preset reporting period. Use 'custom' only together with date_from and date_to.
`date_to`	No
`category`	No	Expense category name selected from list_categories when possible.
`currency`	No	ISO 4217 currency code, e.g. USD, EUR, GBP.
`group_by`	No
`merchant`	No	Merchant or payee name in plain text, preferably in English when the user asks to save in English.
`timezone`	No	IANA timezone used to interpret dates and relative words like today or yesterday, e.g. 'UTC'.
`date_from`	No
`chart_type`	No
`keyword_filter`	No	Explicit keyword filters requested by the user. Do not derive this from the general query text.
`reporting_currency`	No	ISO 4217 currency code, e.g. USD, EUR, GBP.

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

TDQS

A4.3/5.0

Behavior4/5

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

Annotations already indicate readOnlyHint, idempotentHint, and non-destructive behavior. The description adds value by stating the output is 'chart-ready structured data' and clarifying the query parameter's role (display/context only), providing behavioral context beyond the annotations.

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 consists of two concise sentences that front-load the core functionality. Every word serves a purpose, with no redundant or irrelevant information.

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

Completeness3/5

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

Given the tool's complexity (12 parameters, 0 required), the description is somewhat minimal. It lacks guidance on parameter interactions (e.g., using date_from/date_to with custom period) and default behavior when no group_by is specified. Output schema exists, so return values are covered, but more context on how parameters combine would improve usability.

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

Parameters4/5

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

With 67% schema description coverage, the description adds important nuance for the 'query' parameter (not a keyword filter). While it doesn't detail every parameter, this key clarifications helps correct usage. The schema itself covers most parameters adequately.

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 the verb 'Return' and the resource 'grouped expense spending report', specifying grouping dimensions (category, merchant, day, week, month, currency) and output format (chart-ready structured data). It distinguishes from sibling tools like get_summary by focusing on grouped reports with multiple grouping options.

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

Usage Guidelines4/5

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

The description includes a specific instruction: 'Do not use the natural-language query as a keyword filter,' which guides proper parameter usage. However, it does not explicitly compare to sibling tools like get_summary or search_transactions to clarify when to prefer this tool over alternatives.

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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TDQS

A3.7/5.0

Disambiguation4/5

Tools are mostly distinct with clear purposes. Potential confusion between get_report and get_summary or log_transaction and record_expense is mitigated by detailed descriptions explaining their specific use cases.

Naming Consistency5/5

All tools follow a consistent verb_noun pattern in snake_case (e.g., delete_transaction, get_report, parse_expense_text), making the set predictable and easy to navigate.

Tool Count5/5

With 13 tools covering CRUD operations, account management, and utility functions, the count is well-scoped for a personal expense tracking server without being excessive.

Completeness4/5

The tool surface covers essential expense lifecycle operations (create, read, update, delete, restore) and account settings, though a direct get_transaction by ID or bulk operations are missing but not critical.

Resources

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