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Microburbs Australian Property Data

by au.com.microburbs
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Income and tax by postcode

postcodes_economy_taxation
Read-onlyIdempotent

Individual tax-return statistics by postcode for each income year 2016-17 to 2023-24: taxpayers, taxable income (average and median), salary, deductions, net tax, rental income and losses, capital gains, super.

Coverage: About 2,570 postcodes across Australia; income years 2016-17 to 2023-24 (8 years). Current to 2024-06-30. Full description, field list and method: /v1/datasets/taxation.

Price: 10¢ per call.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "postcode": "<postcode>"
    },
    "name": "postcodes_economy_taxation"
  }
}

Input Schema

NameRequiredDescriptionDefault
toNoLast period to include, same formats as `from`.
fromNoFirst period to include: 2020, 2020-Q3, 2020-07 or 2020-07-01.
fieldsNoComma-separated subset of: individuals_count, taxable_income_count, taxable_income_total, total_income_count, total_income_total, salary_wages_count, salary_wages_total, net_tax_count, net_tax_total, medicare_levy_surcharge_count, medicare_levy_surcharge_total, help_debt_balance_count, help_debt_balance_total, govt_allowances_payments_count, govt_allowances_payments_total, govt_pensions_allowances_count, govt_pensions_allowances_total, gross_interest_count, gross_interest_total, dividends_franked_count, dividends_franked_total, work_related_expenses_count, work_related_expenses_total, work_related_car_count, work_related_car_total, work_related_self_education_count, work_related_self_education_total, interest_deductions_count, interest_deductions_total, gifts_donations_count, gifts_donations_total, total_deductions_count, total_deductions_total, reportable_employer_super_count, reportable_employer_super_total, personal_super_contributions_count, personal_super_contributions_total, net_capital_gain_count, net_capital_gain_total, gross_rent_count, gross_rent_total, rent_interest_deductions_count, rent_interest_deductions_total, rent_capital_works_count, rent_capital_works_total, rent_other_deductions_count, rent_other_deductions_total, net_rent_profit_count, net_rent_profit_total, net_rent_loss_count, net_rent_loss_total, net_rent_count, net_rent_total, business_net_income_count, business_net_income_total, private_health_insurance_count, average_taxable_income, median_taxable_income, average_salary_wages, median_salary_wages, average_net_rent, median_net_rent, average_total_income, median_total_income, average_total_deductions, median_total_deductions, average_business_income, median_business_income, average_net_tax, median_net_tax, average_super_balance, median_super_balance, share_with_net_rental_loss_pct, share_giving_to_charity_pct, share_with_private_health_insurance_pct. Omit for all.
postcodeYesFour-digit postcode, e.g. `2026`.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive and closed-world, so safety is covered. The description adds genuinely useful non-schema facts: 2,570 postcodes, eight income years 2016-17 to 2023-24, currency as of 2024-06-30, and a 10¢ per-call price. It does not mention response shape or whether multiple postcodes can be requested, which keeps it below a 5.

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 core purpose, then a clearly labelled coverage block and price, so an agent can stop after the first line. The prose is tight, though the metric list partly duplicates what the `fields` enum already enumerates.

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?

For a read-only statistical lookup with no output schema, the description supplies enough to call correctly: the entity key (four-digit postcode), the temporal window matching the `from`/`to` params, geographic scope and cost. Missing only return-shape/row-granularity detail, which is a minor gap given the fixed nature of the data.

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

Parameters3/5

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

Schema coverage is 100%, so `postcode`, `from`, `to` and the full `fields` enum are already documented. The description contributes mild semantic framing by grouping the available measures (averages and medians for income, deductions, rent, super), but adds no syntax or range detail beyond the schema, so the baseline of 3 applies.

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?

The description names a specific resource (individual tax-return statistics by postcode) and enumerates the measures returned: taxpayers, taxable/median income, salary, deductions, net tax, rental income, capital gains, super. It does not name or contrast any sibling such as postcodes_economy_taxpayer_age or postcodes_economy_income_distribution, so an agent must infer differentiation from the subject matter alone.

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?

Usage is only implied: an agent can infer this is the tool for postcode-level tax/income figures. There is no explicit statement of when to prefer it over adjacent tools (e.g. income_distribution or taxpayer_age), and no prerequisites or exclusions are given. The pointer to `/v1/datasets/taxation` is a documentation reference, not guidance.

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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