treasury_debtCheck current US national debt with historical data points. Returns total public debt outstanding over time.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Number of records to return (default 10) |
| Name | Required | Description | Default |
|---|---|---|---|
| count | Yes | Number of records returned | |
| records | Yes | National debt records | |
| description | Yes | Description of the data |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Output schema / (root)Previous value: -nullNew value: +{
+ "properties": {
+ "count": {
+ "description": "Number of records returned",
+ "type": "number"
+ },
+ "description": {
+ "description": "Description of the data",
+ "type": "string"
+ },
+ "records": {
+ "description": "National debt records",
+ "items": {
+ "properties": {
+ "debt_held_by_public": {
+ "description": "Debt held by the public",
+ "type": "number"
+ },
+ "intragovernmental_holdings": {
+ "description": "Intragovernmental debt holdings",
+ "type": "number"
+ },
+ "record_date": {
+ "description": "Date of the record",
+ "type": "string"
+ },
+ "total_public_debt_outstanding": {
+ "description": "Total public debt outstanding",
+ "type": "number"
+ }
+ },
+ "type": "object"
+ },
+ "type": "array"
+ }
+ },
+ "required": [
+ "description",
+ "count",
+ "records"
+ ],
+ "type": "object"
+}Input schema / examplesAdded value: +[
+ {
+ "limit": 10
+ },
+ {
+ "limit": 20
+ }
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOperation, idempotent, non-destructive. Description adds context about returning historical data points, which is mildly helpful but adds little beyond what annotations and schema imply.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence that front-loads the purpose. Every word is functional; no unnecessary detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity, annotations, and presence of an output schema, the description is sufficiently complete. It explains the return value and historical nature, though no mention of date ranges or edge cases.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with clear description for the 'limit' parameter. Description does not add any additional meaning or constraints beyond the schema, meeting the baseline for full coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states verb 'check' and resource 'US national debt' with historical data points. The tool name and context distinguish it from sibling treasury tools, but no explicit differentiation is provided.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives such as treasury_avg_interest_rates or treasury_receipts. Lacks any when-to-use or when-not-to-use information.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most of the surface is dominated by overlapping meta-tools (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research) plus paired helpers (discover_tools/suggest_questions, ai_visibility_check/scan_competitor_ai_presence), so an agent can easily pick the wrong one. The seven treasury_* tools are clearly distinct, but they are a small island in a much larger ambiguous set.
Names are broadly snake_case and family-prefixed (treasury_*, polymarket_*, pipeworx_*), which helps, but the pattern is not consistently verb_noun: ask_pipeworx, bet_research, entity_profile, deep_research, search_within, and recent_changes mix verb, noun, and product-specific naming styles. Within families it is readable, but across the whole set it is inconsistent.
37 tools is too many for a server whose label is 'Treasury Fiscal'; only about six tools are treasury-specific and the rest are unrelated research, betting, memory, and subscription utilities. This is well into the 25+ heavy range and would make tool selection expensive and error-prone.
For a Treasury/Fiscal server the surface is thin: debt, receipts, customs duty, average rates, exchange rates, and net cost cover only a slice of Treasury data. Missing obvious components such as daily yield curves, auction calendars/results, federal outlays/spending by agency or function, and tax or appropriations data; the broad ask_pipeworx router softens but does not fill these as first-class tools.