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FXMacroData

by io.github.fxmacrodata

Macro War Room Task

macro_war_room_task
Read-only

Build a multi-panel macro market cockpit that combines FX sessions, upcoming release queue, pair context, and generated risk alerts. Supports MCP Tasks for async execution when clients send task-augmented requests.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
baseNoBase currency for pair context, 3-letter ISO code (case-insensitive). Defaults to the release currency when omitted. Supported: AUD, BRL, CAD, CHF, CNH, CNY, DKK, EUR, GBP, ILS, JPY, NGN, NOK, NZD, PEN, SEK, THB, USD.
quoteNoQuote currency for pair context, 3-letter ISO code (case-insensitive). Supported: AUD, BRL, CAD, CHF, CNH, CNY, DKK, EUR, GBP, ILS, JPY, NGN, NOK, NZD, PEN, SEK, THB, USD.usd
currencyNoRelease currency used for queue and spotlight indicator. Supported: AUD, BRL, CAD, CHF, CNH, CNY, DKK, EUR, GBP, ILS, JPY, NGN, NOK, NZD, PEN, SEK, THB, USD.usd
end_dateNoOptional inclusive upper bound, YYYY-MM-DD.
indicatorNoSpotlight indicator slug for release context. Supported examples: average_hourly_earnings, average_hourly_earnings_mom, balance_on_goods, balance_on_services, breakeven_inflation_rate, broad_money, building_approvals, building_permits, business_confidence, capital_account_balance, cb_assets, commodity_price_energy, commodity_price_ex_energy, commodity_price_index, commodity_prices, consumer_confidence, core_inflation, core_inflation_median, core_inflation_mom, core_inflation_trim, core_pce, core_pce_mom, credit_growth, crude_oil_inventories, current_account_balance, dairy_exports, deposit_rates, durable_goods_orders, employment, exports, financial_account_balance, foreign_reserves, full_time_employment, fx_reserves, gdp, gdp_growth_q4_yoy, gold_reserves, gov_bond_10y, gov_bond_1y, gov_bond_20y, gov_bond_2y, gov_bond_30y, gov_bond_3y, gov_bond_40y, gov_bond_4y, gov_bond_5y, gov_bond_7y, government_debt, house_price_index, house_prices, household_credit, housing_starts, imports, inflation, inflation_linked_bond, inflation_mom, initial_jobless_claims, international_assets, international_liabilities, job_openings, m1, m2, m3, nairu, natural_gas_storage, net_foreign_asset_position, non_farm_payrolls, non_farm_payrolls_change, part_time_employment, participation_rate, pce, pce_mom, policy_rate, policy_rate_midpoint, policy_rate_mlf, policy_rate_mro, policy_rate_target_lower, ppi, ppi_mom, primary_income_balance, retail_sales, retail_sales_control_group, retail_sales_ex_autos, retail_sales_ex_autos_and_gas, risk_free_rate, secondary_income_balance, sight_deposits, snb_balance_sheet, tankan_capex, terms_of_trade, trade_balance, trade_weighted_index, trimmed_mean_inflation, unemployment, wage_price_index, wages.inflation
start_dateNoOptional inclusive lower bound, YYYY-MM-DD.

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already cover readOnlyHint=true and destructiveHint=false, so the safety profile is clear. The description adds behavioral context beyond that: the tool builds a composed dashboard and supports MCP Tasks for async execution. It does not describe return format or potential limitations, but the annotations lower the burden here.

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?

Two sentences with no filler. The first sentence front-loads the core purpose and output composition, and the second adds a distinct async execution capability. Every clause earns its place.

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 six optional parameters, full schema descriptions, and read-only annotations, the description covers the key decision points: what the tool returns (a composite cockpit) and when async execution is relevant. No output schema exists, but the description's listed panels sufficiently describe the return value for invocation purposes.

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 description coverage is 100%, so the baseline is 3. The description adds value by mapping parameters to output panels (e.g., base/quote to pair context, currency/indicator/dates to release queue), which helps an agent connect arguments to the cockpit's contents. It does not add syntax details, but the schema already handles those.

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?

Description uses a specific verb ('Build') and resource ('multi-panel macro market cockpit'), then enumerates the combined components: FX sessions, upcoming release queue, pair context, and generated risk alerts. This clearly distinguishes it from focused siblings like market_sessions, release_calendar, pair_intel_task, and release_risk_score_task.

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 states when async execution applies: 'when clients send task-augmented requests.' It also implies the primary use case—anyone wanting a consolidated multi-panel macro cockpit. However, it does not explicitly name alternative tools or state when not to use it, so it misses the top tier of usage 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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TDQS

A3.8/5.0
Disambiguation4/5

Most tools have clearly distinct purposes with detailed descriptions; the visual_artifact variants are explicitly duplicate payloads for chart rendering. However, several task and analysis tools (macro_briefing_task, macro_research_pack_task, indicator_intel_task) have overlapping scopes and could cause misselection despite different outputs.

Naming Consistency4/5

Tool names are consistently snake_case with systematic _task and _visual_artifact suffixes, making the pattern predictable. Minor deviations like 'ping', 'subscribe_for_mcp_access', and a few noun-only names (e.g., 'forex', 'commodities') break a strict verb_noun pattern but remain readable.

Tool Count2/5

At 48 tools, the surface is far beyond the typical well-scoped server and risks overwhelming agents. The broad macro/FX domain justifies some size, but 48 is excessive and could be consolidated (e.g., merging visual artifact pairs or grouping task tools).

Completeness5/5

The tool set covers the full macro/FX workflow: data discovery (data_catalogue), raw queries (indicator_query, forex, commodities), visual artifacts, release calendar, news, COT, sentiment, seasonality, backtesting, scenario modeling, portfolio risk, and reference tools. No obvious dead ends or missing lifecycle operations for a read-heavy data server.

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