finance

Analytics: Get daily averages

get_daily_averages

Read-onlyIdempotent

    Get daily average income, spending, and net for a date range.

    Computes the averages server-side, handling partial months and
    year-to-date ranges correctly, and provides a monthly breakdown.

    Phase 114 — the start date is **clamped to the user's first
    transaction date** when that's later than what was requested.
    Without this, a user with two months of activity who asks for
    the YTD average sees the daily averages roughly halved (divided
    by ~120 days when only ~60 had activity). The response carries
    ``clamped_to_first_activity`` (bool) and ``requested_start_date``.
    When ``clamped_to_first_activity`` is True, the averages cover
    only the days since the first transaction (e.g. 55 days of data),
    not the full requested range.

    Args:
        start_date: YYYY-MM-DD (defaults to Jan 1 of current year)
        end_date: YYYY-MM-DD (defaults to today)

    Returns:
        Daily averages with monthly breakdown showing income, expenses,
        and net for each month in the range, plus the two clamping
        metadata fields.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_daily_averages"
  }
}

Input Schema

Name	Required	Description	Default
`end_date`	No
`start_date`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedSep 22, 2026

TDQS

A3.8/5.0

Behavior4/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive), yet the description adds real value: server-side computation, partial-month/YTD handling, and the Phase 114 start-date clamping rule with its rationale and the returned metadata fields. It stops short of mentioning rounding, currency, or timezone behavior.

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

Conciseness4/5

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

Front-loaded with the purpose, then Args/Returns sections that are easy to scan. The clamping explanation is repeated (the halving example, then a restatement of the same effect), which is mild redundancy in an otherwise well-organized description.

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?

With no output schema, the description correctly describes the return payload (monthly income/expense/net breakdown plus the two clamping metadata fields), and params are documented. Completeness is good for the tool's complexity, with minor gaps around numeric formatting and currency assumptions.

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?

Schema coverage is 0%, so the description carries the load, and it does: it documents both parameters with format (YYYY-MM-DD) and defaults (Jan 1 of current year; today). That fully compensates for the bare schema, though it adds no constraint/interaction detail between the two dates.

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

Purpose4/5

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

States a specific verb and resource plus the computed metrics (daily average income, spending, net) and the scoping dimension (date range). It is clearly distinguishable from most siblings, though it never names an alternative analytics tool to contrast against.

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 when the tool applies (YTD/partial-month averaging, default Jan 1–today) but gives no explicit when-to-use/when-not guidance and never routes the agent to a sibling such as get_period_summary or get_cash_flow. Usage context is inferable but not stated.

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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