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get_whats_new

Get the daily what-changed digest for the newest data day, in one call with links deeper: every agency series that published a new reading, every agency value restated (derived signals that recomputed are listed separately by name), every projection graded against its printed actual, and the day's Market Wire editions. Designed to be the first call of an agent's day: if date hasn't advanced since your last look, nothing moved. Empty days are reported empty with the reason, never padded. Try: {}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A4.5/5.0
Behavior4/5

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

With no annotations, the description carries the full burden. It discloses the digest's components, how restated values are listed separately, that empty days are reported with a reason and never padded, and that 'nothing moved' when the date hasn't advanced. This is rich behavioral context, though it does not cover return format or rate limits.

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 is tightly structured: purpose first, a scannable list of contents, then usage guidance. Every sentence earns its place with no redundant or filler wording.

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 zero-parameter tool with no annotations or output schema, the description fully explains what the digest contains, when to call it, and how empty days are handled. The 'Try: {}' example confirms invocation, leaving no significant gaps for an agent.

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?

The tool has zero parameters and an empty schema, so there is nothing to explain. The description adds a 'Try: {}' invocation example, which is the only meaningful addition. Baseline for 0 parameters is 4.

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 'Get the daily what-changed digest for the newest data day' and enumerates its contents (new readings, restated values, projections, Market Wire editions), making the tool's purpose explicit and distinguishing it from the more specific sibling get_* tools.

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 explicitly frames itself as 'the first call of an agent's day' and explains the 'if date hasn't advanced since your last look, nothing moved' check, providing clear when-to-use context. It does not name alternatives or when-not scenarios, but the digest role makes its usage intent obvious.

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

A4/5.0
Disambiguation3/5

Most tools have distinct purposes, but several clusters overlap: ask/brief/get_index all answer questions, get_revisions/get_vintages both cover historical data, and get_provenance/get_receipts/get_citation all support verification. Descriptions clarify some boundaries, but an agent could easily misselect between ask and get_index for tariff or cost questions.

Naming Consistency4/5

The naming pattern is largely consistent verb_noun with a strong get_ prefix (get_freshness, get_vintages, run_calculator, search_calculators). However, ask and brief break the convention as bare verbs, and lookup_tariff/optimize_sourcing use different verbs, creating minor but noticeable deviations.

Tool Count4/5

17 tools is at the high end of reasonable for a broad domain covering calculators, live data series, tariffs, sourcing optimization, and verification. It feels slightly heavy but each tool has a real function, and the count is justifiable given the breadth.

Completeness4/5

The tool surface covers the full research workflow: search, lookup, calculate, optimize, verify, cite, and monitor data freshness/revisions. Minor gaps include the lack of a direct series browser (search_site covers it) and the index family being collapsed into a single get_index tool rather than exposed individually.

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