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cliwant

mcp-sam-gov

by cliwant

treasury_debt_to_penny

Read-only

Retrieve daily US public debt outstanding figures from Treasury Fiscal Data. Get total debt, debt held by public, and intragovernmental holdings for the latest day or a custom date range.

Instructions

Daily total US public debt outstanding ('Debt to the Penny', keyless Treasury Fiscal Data). Returns record_date + totalPublicDebtOutstanding, debtHeldByPublic, intragovernmentalHoldings (USD). latest (default true) ⇒ the single most-recent day; set latest=false with startDate/endDate (ISO YYYY-MM-DD) for a date range, newest-first. Amounts are coerced to number|null (a null amount is 'no value reported', never 0).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
latestNotrue (default) ⇒ only the single most-recent day (page[size]=1). false ⇒ the startDate/endDate range, newest-first.
endDateNoRange mode only: ISO YYYY-MM-DD upper bound on record_date (inclusive).
pageSizeNoRange mode: rows per page, 1..500, default 100.
startDateNoRange mode only: ISO YYYY-MM-DD lower bound on record_date (inclusive).
pageNumberNoRange mode: 1-based page number, default 1.
Behavior5/5

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

Beyond the readOnlyHint and openWorldHint annotations, the description adds valuable behavioral details: the tool is 'keyless' (no authentication required), amounts are coerced to number|null with a note that null means 'no value reported' (not zero), and the ordering is newest-first in range mode. No contradictions with annotations.

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 well-structured: first identifies the dataset and returned fields, then explains the two modes (latest vs. range), and finally clarifies null handling. Every sentence adds critical information without waste.

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?

The description covers the returned fields, the two operation modes, date format, pagination parameters and defaults, and the null coercion behavior. Although there is no output schema, the agent can infer the output structure. It is self-contained enough for effective use.

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 100%, so the baseline is 3. The description restates some schema fields (start/end date format) but adds the ordering (newest-first) and the default for latest. This provides marginal added value beyond the schema descriptions.

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 the tool returns 'Daily total US public debt outstanding' from the 'Debt to the Penny' dataset, specifying the exact fields returned (record_date, totalPublicDebtOutstanding, debtHeldByPublic, intragovernmentalHoldings). It distinguishes this tool from siblings like treasury_monthly_statement by focusing on daily data.

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 explains the two usage modes (latest=true for single most-recent day vs. latest=false with date range) and the parameters involved, but does not explicitly tell the agent when to prefer this tool over alternatives like treasury_monthly_statement or treasury_avg_interest_rates. The usage context is implied but not contrasted.

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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