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malkreide

swiss-efv-mcp

by malkreide

fiscal_headline

Read-onlyIdempotent

Track fiscal time series for revenue, expenditure, balance, and debt ratios from 1990 to 2029, with actuals and forecasts. Filter by variable, household, and model to see how aggregates evolved.

Instructions

Headline fiscal time series: revenue, expenditure, balance and debt ratios over 1990–2029 (actuals plus budget/forecast years).

Use case: track how a federal aggregate evolved over time — e.g. "how did the Bund balance develop since the 2022 rate turnaround?". variable e.g. 'saldo', 'einnahmen', 'ausgaben', 'bruttoschuldenquote'. household: bund|ktn|gdn|staat|sv. model: fs|gfs. Every point flags is_projection. Call fiscal_list_dimensions first to discover valid values; an empty result carries a note with guidance.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelNofs
year_toNo
variableYes
householdNobund
year_fromNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
noteNoguidance when the result is empty or has a caveat (ARCH-003)
unitNoCHF mio / % (variable-dependent)
modelYesfs (Finanzstatistik) | gfs (GFS-Modell)
pointsYes
sourceNoData: Eidgenoessische Finanzverwaltung EFV — opendata.swiss (OGD Schweiz, frei nutzbar). Private, non-affiliated project. Kein Anspruch auf Vollstaendigkeit.
variableYes
householdYeshh: bund | ktn | gdn | staat | sv | bund_ktn_gdn
provenanceYesdump = freshly fetched CSV, cached = in-memory
Behavior4/5

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

Annotations already declare the tool read-only and idempotent, so the description adds value by explaining actuals vs. forecast years, the is_projection flag, and the empty-result note behavior. This goes beyond the structured hints and does not contradict them.

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?

The description is compact and logically structured: purpose, use case, parameter examples, and usage guidance. Each sentence contributes, though the dense multi-subject sentences could be slightly more scannable.

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?

For a read-only tool with good annotations and an output schema, the description covers the core purpose, usage context, key parameters, and a notable output flag. It does not mention year range defaults or detailed variable semantics, but overall is sufficiently complete for an agent to select and invoke the tool correctly.

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 has 0% parameter description coverage, so the description must compensate. It provides example values for variable (saldo, einnahmen), household (bund, ktn), and model (fs, gfs), but does not explain the meaning of year_from/year_to or what fs/gfs represent. Partial compensation only.

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 clearly identifies the tool as a 'headline fiscal time series' covering revenue, expenditure, balance, and debt ratios over a specific period. It distinguishes itself from siblings like fiscal_by_institution and fiscal_budget_breakdown by focusing on aggregate evolution, but lacks a direct action verb in the opening phrase.

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?

Provides a concrete use case ('track how a federal aggregate evolved over time') and explicitly directs users to call fiscal_list_dimensions first for valid values, which is helpful alternative guidance. Does not explicitly state when not to use this tool versus siblings, but the context implies appropriate usage.

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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