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vigneshv1cky

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by vigneshv1cky
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

government_actions

Retrieve recent government actions: agency rulemaking, Fed announcements, Treasury auction results. Filter by source, agency, or type to track regulatory moves.

Instructions

WHAT THE GOVERNMENT JUST DID — agency rulemaking, the Federal Reserve's own announcements, and Treasury auction results.

sources is a comma-separated pick from: agencies (the Federal Register), fed, treasury. Default is all three.

READ at_precision BEFORE YOU REASON ABOUT TIMING. The Federal Register is a DAILY publication, so an agency row's stamp is a DATE ("day") and the decision was frequently announced before it appeared there — a market reaction can precede this row by days. Fed rows carry a real moment ("second"). Treating a day stamp as a moment will tell you a stock moved before the news, which is simply the publication lag.

agencies takes the Federal Register's own slugs, so any of its 473 agencies can be asked for by name — "surface-transportation-board", "federal-energy-regulatory-commission", "food-and-drug-administration". The default shortlist is the agencies whose actions move listed companies, and it LEAVES OUT the FAA on purpose: measured, it filed 47 of 92 rules in a fortnight, nearly all airworthiness directives naming one aircraft model. Ask for it by name if you want it.

types picks from RULE, PRORULE (proposed), NOTICE, PRESDOCU (presidential documents); the default is rules and proposed rules, because notices are the bulk of the Register and mostly routine.

NOT HERE: FDA drug approvals. openFDA's date filter matches an application rather than the submission inside it, so asking for this month returns approvals from 1993 — do not substitute it. FDA RULES do come through the agency source above.

A source that could not be read is named in unavailable and never reported as a source with nothing in it. This is public government data, keyless — not a vendor, not scraped.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
daysNo
limitNo
typesNo
sourcesNo
agenciesNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.1

TDQS

A4.9/5.0
Behavior5/5

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

With no annotations, the description carries full responsibility for disclosing behavior. It explains the publication lag, that unavailable sources are named in the `unavailable` field, that the data is keyless public government data, and the semantics of default selections. It also clarifies that the tool does not return FDA drug approvals. This is thorough and transparent.

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?

Though long, every sentence adds value. The structure is logical: main purpose, source details, timing warning, agency specifics, type defaults, exclusions, and error behavior. It is front-loaded with the core purpose and uses formatting (bolding, backticks) to highlight key concepts. There is no redundancy.

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 tool with no output schema, no annotations, and five parameters with zero schema coverage, this description is exceptionally complete. It covers input semantics, output characteristics (including the `unavailable` field), timing nuances, and exclusions. An agent can call this tool correctly without further documentation.

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?

Schema coverage is 0%, so the description must compensate. It explicitly defines `sources` (comma-separated pick from agencies, fed, treasury), `agencies` (Federal Register slugs with examples), and `types` (RULE, PRORULE, NOTICE, PRESDOCU, default). It does not explicitly explain `days` and `limit`, but their names and defaults make them self-explanatory. Given the heavy lifting done for three parameters, this is strong but not perfect.

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 opens with a clear, specific statement of what the tool does: it retrieves recent government actions (agency rulemaking, Fed announcements, Treasury auction results). It distinguishes itself from siblings like news_story or economic_calendar by focusing on government-specific data sources. The purpose is unambiguous and actionable.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit when-to-use and when-not-to-use guidance. It warns about timing interpretation (day vs. second precision), explains the default source shortlist and why the FAA is excluded, and explicitly states 'NOT HERE: FDA drug approvals' with a reason not to substitute openFDA. This gives clear direction for an agent.

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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