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Summarize congressional activity

politics_us_congress_aggregate
Read-onlyIdempotent

Return ticker-level totals from reported United States congressional transactions. The totals do not show current holdings or intent.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
daysNoThe lookback period in calendar days.
limitNoThe maximum number of results to return.
cursorNo
symbolsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYes
metaYes
billingYes
warningsYes

TDQS

B3.4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, which covers safety. The description adds the important caveat that totals do not show current holdings or intent, which is valuable context. It doesn't disclose pagination behavior or that data represents reported (potentially delayed) transactions.

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?

Two sentences, both informative and waste-free. The first sentence states the core function; the second adds an important limitation caveat. It's appropriately sized for the tool complexity.

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

Completeness3/5

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

The tool has an output schema (so return format is covered) and good annotations. However, given it's an aggregation/normalization tool with 4 parameters including pagination, the description could mention that results are sorted/deduped, or note the lookback default behavior. The caveat about holdings/intent partially compensates but pagination behavior and data recency are left implicit.

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 description coverage is 50%, and the description doesn't add anything about parameters beyond what the schema provides. The 'days' lookback, 'limit', 'cursor' pagination, and 'symbols' filter are all documented in the schema itself. With moderate coverage, the description adds no extra parameter meaning, meeting the baseline.

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 states 'Return ticker-level totals from reported United States congressional transactions' with a specific verb+resource+scope. It distinguishes the aggregate view from the sibling 'politics_us_congress_trades' tool by using 'totals' vs. individual trades. However, it doesn't explicitly name the sibling alternative or contrast them.

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 this is a summary/aggregate tool by using 'totals,' and the sibling name 'politics_us_congress_trades' suggests a distinction, but no explicit when-to-use/when-not-to-use guidance is given. The line 'The totals do not show current holdings or intent' adds a usage caution but no direction toward alternatives.

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

A3.7/5.0
Disambiguation5/5

Each tool targets a distinct resource-action combination (catalog items, datasets, macro data, market data, news, politics, account). Even within the market_ prefix, tools are clearly separated by resource type (quote, fundamentals, earnings, ratings, profile). No two tools appear to perform the same operation.

Naming Consistency4/5

The naming follows a consistent noun_verb pattern with domain prefixes: catalog_, datasets_, macro_, market_, news_, politics_. The verb style is consistent (describe, list, search, request, submit, return-type verbs like indicator and quote). Slight deviation with account_request_upgrade vs account_upgrade_status, and some verbs double as noun forms (quote, indicator, preview), but overall the convention is predictable.

Tool Count4/5

At 28 tools, the count is on the high side, but it serves a broad data platform spanning seven distinct domains (catalog, datasets, macro, market, news, politics, account). Each domain earns multiple tools to cover its surface, and the domains are broad enough to justify the volume. Slightly heavy, but reasonable given the scope.

Completeness4/5

The surface covers the full discovery-to-delivery workflow for data: list, describe, preview, request (catalog), plus direct dataset access. Market data has symbols search, quotes, price history, fundamentals, earnings, ratings, ETFs, and profile. Minor gaps include no bulk quote or multi-ticker endpoints, and there's no tool for reading an existing catalog request's status, but core workflows are well-covered.

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