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bakom_medien_statistik

Read-onlyIdempotent

Query Swiss radio and television market statistics from BAKOM cubes. Retrieve market shares, reach, or program structure filtered by year, program, or region.

Instructions

Zahlen zum Schweizer Radio- und Fernsehmarkt aus den BAKOM-Cubes auf LINDAS.

Liefert Beobachtungen aus den Statistik-Cubes des BAKOM: Marktanteile, Reichweiten, Programm- und Themenstruktur, Ertragsstruktur — je nach Cube aufgeschluesselt nach Jahr, Programm, Sendergruppe, Sprachregion oder Konzessionierungsart.

thema ohne Wert listet alle verfuegbaren Auswertungen auf. Das ist der erste Aufruf, wenn unklar ist, welche Zahl es ueberhaupt gibt.

Drei Eigenheiten der Quelle, die das Ergebnis praegen:

  • Die Cubes decken die untersuchten Programme ab, nicht den Bestand. Ein Sender, der hier fehlt, existiert deswegen nicht weniger.

  • Durchschnitt ist ein Aggregat und kein Sender.

  • Derselbe Sender kann je nach Erhebung anders geschrieben sein ('Energy BE' und 'Energy Bern').

Args: params (MedienStatistikInput): Thema, Jahr, Limit, Format.

Returns: str: Beobachtungen mit Dimensionen und Messwert.

Schema: { "auswertung": str, "beobachtungen": [{"": str | float}], "total": int, "datenquelle": str, "provenance": "live_api", "hinweis": str | None }

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
paramsYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and non-destructiveHint, so the description doesn't need to restate these. The description adds valuable behavioral context about data source limitations (only examined programs, aggregate vs. sender, naming variations), which annotations don't cover. It doesn't discuss rate limits or detailed authorization, but for this stateless query tool the provided context is sufficient.

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: a clear purpose statement, usage guidance, key behavioral quirks listed concisely, and a summary of input/output schema. Every sentence adds value, with no redundancy or filler. The format is front-loaded with the most critical information (what the tool does) followed by usage tips.

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?

Given the tool's complexity (multiple cubes, dimensions, and data sources), the description is remarkably complete. It covers purpose, usage workflow, data caveats, parameter roles, and provides a full output schema. The sibling context and annotations further support correct selection and invocation. There are no obvious gaps in understanding what the tool does or how to use it.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate, and it does thoroughly. It explains that `thema` without value lists all available evaluations and describes the matching behavior (substring match on titles). It also mentions year and limit parameters with context, and the output schema is provided, so return value semantics are clear. The description adds meaning well beyond the bare schema.

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 provides Swiss radio and TV market statistics from BAKOM cubes on LINDAS, listing specific data types like market shares, reach, and program structure. It distinguishes itself from siblings by its unique focus on media statistics, while sibling names (e.g., bakom_mobilfunk_abdeckung, bakom_sendeanlagen_suche) suggest they cover different domains.

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 explicitly advises starting without `thema` to list available evaluations when unsure, providing a clear workflow. It also notes three data quirks (covered vs. actual programs, 'Durchschnitt' as aggregate, naming inconsistencies), helping the agent avoid common misinterpretations and use the tool correctly.

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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