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The Jawz Dashboard: where the world stands, in six readings. Regime (GREEN / YELLOW / RED: consumer mood and money together), Money (PLENTIFUL / STEADY / SCARCER: the Fed, ECB, Bank of Japan and PBoC balance sheets in dollars), Business cycle (SPRING / SUMMER / FALL / WINTER: growth, a vote of factory output, jobs and investment, crossed with prices), Financial conditions (LOOSE / EASING / NEUTRAL / TIGHTENING / TIGHT: rates and credit), Store of value (RISING / MIXED / FALLING: gold and bitcoin) and Investment (BOOMING / STEADY / FADING: the AI build-out, from data centres, chips, the four big builders' capital spending and power). Each card carries its rule in one sentence, the badge with the date it has held since, the badge's last three prints, and the rows behind it, each with its last three prints (date, word and value as the card writes it) and a data-quality status (ok, stale or unavailable). The summary has the six badges, what set each, and the biggest risk in one line. Returned three ways: the dashboard object as structured content, a short card as markdown text (one line per reading with what set it and since when, the biggest risk, and the link to the full dashboard), and the full card as a PNG image. as_of (YYYY-MM-DD, optional) returns the dashboard as Jawz would have read it that day, using only data published by then, with today's rules applied: rules_note says so and, when Jawz's daily snapshot for that date is on file, what Jawz published that day. as_of reaches back 365 days and excludes today, which is the default; a future date or one before the window returns an error stating the supported range. In a dated read every row carries point_in_time. The Investment card's Data centres and Chips rows are not point in time (the Census tables behind them keep only their revised figures, so a dated read shows those months as revised since) and point_in_time_note names them; every other row is as published by that date. The detail behind the cards is in get_macro_regime, get_financial_conditions, get_growth_indicators and get_inflation_indicators; get_indicator_history gives any card or row over time. Read-only, no account needed. Information, not investment advice.

Input Schema

NameRequiredDescriptionDefault
as_ofNoOptional past date, YYYY-MM-DD, within the last 365 days: the dashboard as Jawz would have read it that day, from data published by then. Omit (or pass today) for today's dashboard.

Output Schema

NameRequiredDescriptionDefault
as_ofNo
staleNo
blocksNo
summaryNo
versionNo
rules_noteNo
generated_atNo
method_notesNo
presentationNo
pending_blocksNo
as_of_requestedNo
point_in_time_noteNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.7/5.0
Behavior5/5

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

Annotations already declare readOnly/openWorld/destructive, but the description goes well beyond them: read-only and no account needed, three return renderings (structured content, markdown card, PNG image), error behavior for out-of-window dates, and nuanced point-in-time semantics including the specific rows that are not point in time and the point_in_time_note. That is substantial disclosure the annotations cannot carry.

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?

The opening sentence and the card enumeration are front-loaded and every clause carries substantive information about badges, rows, and dated reads. It is, however, long and somewhat prose-heavy, and the explanation of the three return renderings partially duplicates the output schema, costing a point on tightness.

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

Completeness5/5

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

For a high-complexity, multi-card tool with an output schema and clean annotations, the description covers purpose, routing, dated-read semantics, caveats, and error behavior. Nothing an agent needs to invoke it correctly is missing.

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 coverage is 100% and the single as_of parameter is documented, yet the description adds real meaning beyond it: the 365-day reach, exclusion of today as the default, the error on future/too-old dates, rules_note behavior, per-row point_in_time, and the Investment card's Data centres/Chips exception. This is more than the schema conveys.

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 names a specific resource (the Jawz Dashboard) and enumerates exactly what it contains: six readings (Regime, Money, Business cycle, Financial conditions, Store of value, Investment) with their badge vocabularies and per-card rows. It explicitly differentiates itself from sibling detail tools (get_macro_regime, get_financial_conditions, get_growth_indicators, get_inflation_indicators, get_indicator_history), so an agent can route correctly without opening a schema.

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?

It clearly routes: this tool gives the overview, while the named siblings give 'the detail behind the cards' and get_indicator_history gives a card or row over time. It also states when as_of applies and its constraints. It does not spell out explicit exclusions beyond the date-window error, so it falls just short of a 5.

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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