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

Annotations already declare this as a read-only, idempotent, non-destructive, open-world operation. The description adds useful behavioral context by explaining that it combines three datasets and returns a compact tabular comparison, but it does not cover rate limits, data freshness handling, or authentication requirements.

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?

The description is front-loaded with the core purpose and then organized into Args and Returns sections. It is appropriately sized, though some material such as the Args section partially duplicates schema information and the Returns section overlaps with the output schema.

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?

For a read-only comparison tool with rich annotations and an output schema, the description is largely complete: it states the comparison basis, the combined datasets, and the output nature. Its main gap is not mentioning the response_format option, but the schema and output schema cover most remaining details.

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?

The description names the main inputs (stations and year) and repeats the 2–10 station constraint, but much of this is already present in the schema. It omits the response_format parameter entirely, even though that parameter controls whether output is markdown or JSON, so it only partially compensates for the low top-level schema description 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?

States a specific verb and resource ('Vergleicht mehrere SBB-Bahnhöfe') and specifies the comparison dimensions (Passagierfrequenz und Perrondaten). It clearly distinguishes itself from single-dataset siblings like sbb_get_passenger_frequency and sbb_get_platform_data by comparing multiple stations and combining three datasets, though it does not name those alternatives explicitly.

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?

Gives clear usage contexts ('Planungsentscheide, Präsentationen und Standortanalysen'), which tells the agent when this tool is appropriate. It does not state when not to use it or explicitly compare it with alternatives such as sbb_get_passenger_frequency, so it falls short of full routing guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Die Annotationen decken bereits readOnly, idempotent, openWorld und non-destructive ab. Die Beschreibung ergänzt nützlichen Kontext: jährliche Aktualisierung, enthaltene Kennzahlen (DTV/DWV/DNWV), Rückgabeschema und Paginierungshinweis. Angaben zu Auth oder Rate Limits fehlen, sind aber angesichts der Annotationen nicht kritisch.

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?

Die Zweckbeschreibung steht vorne, gefolgt von strukturierten Args- und Returns-Abschnitten. Die Länge ist für ein Tool mit sechs Parametern angemessen, wenngleich die Parameterliste das Schema teilweise wiederholt.

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?

Für ein Datensuchtool mit Output-Schema, klaren Annotationen und sechs Filterparametern ist die Beschreibung weitgehend vollständig: sie erklärt Zweck, Aktualisierungsfrequenz, Filter und Rückgabefelder. Es fehlt lediglich eine Einordnung, wann dieses Tool gegenüber den Geschwistern zu verwenden ist.

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?

Da die Schema-Beschreibungsabdeckung als 0% angegeben ist, muss die Beschreibung die Parameter erklären. Sie listet alle Filter (station_name, canton, year, limit, offset, response_format) mit Typen, Beispielen und Standardwerten auf und kompensiert damit die Lücke, auch wenn sie teilweise das Schema dupliziert.

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?

Die Beschreibung nennt ein klares Verb (abrufen) und eine spezifische Ressource (Passagierfrequenzdaten für SBB-Bahnhöfe). Sie grenzt sich inhaltlich von Geschwistern wie sbb_get_trains_per_segment oder sbb_compare_stations ab, benennt aber keine konkreten Alternativen.

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?

Es wird nicht gesagt, wann dieses Tool gegenüber Alternativen wie sbb_compare_stations oder sbb_search_stations zu wählen ist. Die Filterparameter implizieren eine Nutzung, aber es fehlen explizite Einsatzbedingungen oder Abgrenzungen.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations already declare readOnlyHint=true, idempotentHint=true, openWorldHint=true, and destructiveHint=false, so the safety profile is fully covered. The description adds that results can be paginated (limit/offset) and returned as markdown or json, but discloses no rate limits, auth requirements, or data-freshness caveats beyond the annotations.

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?

Purpose is front-loaded and the Args block is useful given the low schema coverage, but the Returns section repeats a field schema that an output schema already defines, which is redundant. Structure is clear (purpose / args / returns) but not maximally economical.

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?

For a read-only tool with rich annotations and an existing output schema, the definition covers purpose and parameters adequately. The only substantive gap is the absence of usage guidance versus sibling tools, which the annotations cannot supply.

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 description coverage is reported at 0%, so the description carries the burden and largely does: it glosses station_name, platform_type, limit, offset, and response_format, and even supplies enum values ('markdown' oder 'json') and examples ('Zürich HB'). It slightly duplicates schema examples, but meaningfully compensates for the documentation gap.

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?

States a specific verb and resource: 'Ruft Perrondaten (Länge, Fläche, Typ) für SBB-Bahnhöfe ab', and enumerates what the data contains (length, net/gross area, type, barrier-free access). Clear enough to distinguish from siblings like passenger frequency or rolling stock, though it never names an alternative explicitly.

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?

The description says what the tool returns but offers no when-to-use guidance, no prerequisites, and no mention of alternatives among the eight sibling tools. The agent must infer the usage context entirely.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations already declare readOnlyHint=true, destructiveHint=false, openWorldHint=true and non-idempotence, so the safety profile is covered. The description adds the 5-minute refresh cadence, which is genuinely useful freshness context, but says nothing about rate limits, auth requirements, or failure behavior for a live open-world source.

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?

The prose leads with purpose and freshness, which is well front-loaded, but the Returns block restates the output schema that already exists and the Args block duplicates schema descriptions, adding length without new information.

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?

An output schema exists and annotations cover the safety profile, so the description need not explain return values (its restatement is redundant but harmless). With a single required params object and live data, the definition gives enough for an agent to call it correctly, missing only guidance on alternates and error handling.

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 description coverage is reported as 0% at the top level, but the Args block mirrors the nested property descriptions (limit 1-100 default 20, offset pagination, response_format markdown/json) without adding new semantics such as pagination interaction or format trade-offs. It compensates for the coverage gap at a minimum-viable level.

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?

States a specific verb and resource ('Ruft aktuelle Bahnverkehrsstörungen und -meldungen ab') with a clear scope qualifier (live, updated every 5 minutes). None of the sibling tools cover rail disruptions, so an agent can distinguish it without opening the schema.

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?

'Ideal für Echtzeit-Monitoring und Kommunikation bei Ereignissen' implies the intended use case, but there is no explicit when-to-use vs when-not guidance and no named alternative among the siblings. Usage is inferred rather than stated.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint, and destructiveHint=false, so the safety profile is fully covered by structured data. The description adds genuinely useful non-redundant context — daily refresh cadence and multilingual descriptions (DE/FR/IT/EN) — but omits auth requirements, rate limits, and pagination behavior, and partly restates the output fields.

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?

Purpose is front-loaded well, but the boilerplate Args and Returns blocks largely duplicate what the input and output schemas already define, adding length without new meaning. The Returns section in particular restates fields the output schema already carries.

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?

For a read-only, annotated, output-schema-backed data tool, the definition covers purpose, cadence, language coverage, filter dimensions, and pagination. Complete enough to invoke correctly, with only the phase-enum mismatch and absent auth/limit details as nits.

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 description coverage is reported at 0%, so the description must carry the parameter burden, and it mostly does: city with concrete examples, phase with example values, limit/offset semantics, and the two response_format options. Minor gap: the phase examples ('CONSTRUCTION', 'PLANNING') omit 'COMPLETED' which the nested schema lists, a small inconsistency an agent could trip over.

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?

States a specific verb (abrufen/retrieve), a precise resource (laufende SBB-Immobilien-Bauprojekte), and scopes it to Wohn- und Geschäftsbauten. Nothing in the sibling list overlaps with real estate projects, so an agent can immediately tell this apart from the station, rolling-stock, or disruption tools.

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?

Usage is implied by the resource itself, and the daily-update note hints at freshness expectations. However, there is no explicit when-to-use guidance, no statement of prerequisites, and no exclusions or alternatives named. For a standalone tool with no close sibling this is acceptable but thin.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint, so the safety profile is covered externally. The description adds only the field-level content of the response; it discloses no auth needs, rate limits, or pagination caveats beyond the bare offset/limit args.

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?

Front-loaded purpose followed by Args/Returns blocks. Some redundancy between the Args list and the actual schema, but given the 0% schema coverage that restatement is justified rather than wasteful.

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?

An output schema exists, so the description need not explain return values, yet it helpfully lists the response fields. For a simple read-only list query with full annotation coverage and simple params, the definition is complete enough to invoke correctly.

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 description coverage is 0%, so the description carries the param burden and it does so reasonably: it explains vehicle_type with concrete examples, limit as max results, offset as pagination, and response_format as markdown/json. The explanations are terse ('Max. Resultate') but functional.

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?

States a specific verb (retrieves) and a well-defined resource (technical data on SBB rolling stock: trains, multiple units, coaches) and lists the contained fields. It is clearly distinct from all siblings (disruptions, stations, frequency), though it never names or contrasts them explicitly.

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?

Usage is implied by the data it returns, but there is no explicit when-to-use, when-not-to-use, or alternative-tool guidance relative to the eight sibling tools. The agent must infer that this is the tool for vehicle technical specifications.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint and destructiveHint=false, so the safety profile is fully covered structurally. The description adds useful content-scope context (multiple operators, passenger + freight, track km, electricity consumption) but nothing about rate limits, auth, or pagination behaviour beyond restating offset/limit.

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?

Front-loaded summary followed by a compact scope paragraph and structured Args/Returns blocks. It is somewhat repetitive relative to the schema, but every part is legible and there is no padding.

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?

With an output schema present, the description need not explain return values, but it still names the returned fields, and it covers the query dimensions an agent needs to know. It is complete enough to call correctly; only the missing sibling routing keeps it from being fully self-sufficient.

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?

The Args block essentially restates the schema, which already carries descriptions for year, operator, line_name and traffic_type. It adds no format hints, matching semantics, or enum details beyond what the schema provides, so it sits at the baseline for schema-documented parameters.

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?

The description gives a specific verb and resource ('Ruft Anzahl Züge pro Streckenabschnitt und Verkehrstyp ab') and clarifies scope by naming the covered operators (SBB, BLS, SOB, DB) and the fact that both passenger and freight traffic are included. It does not, however, differentiate itself from the closest sibling sbb_get_passenger_frequency, which likely overlaps in subject matter.

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?

The description explains what data the tool returns but offers no guidance on when to choose it over siblings such as sbb_get_passenger_frequency or sbb_get_platform_data. There are no stated preconditions, exclusions, or alternative-routing cues beyond an implied context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint and destructiveHint=false, so the safety profile is fully covered. The description adds the return shape (dataset_id, title, records_count, update_frequency, themes), which is useful context, but says nothing about pagination, result size, or whether the list is unfiltered/complete beyond 'alle'.

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?

The purpose and use case are front-loaded in two short sentences, which is efficient. The trailing 'Returns:' block is somewhat redundant since an output schema already exists, but it is brief and does not bloat the definition.

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?

For a no-parameter catalog listing tool with annotations covering the safety profile and an output schema covering the return type, the description supplies enough to call it correctly. The only gap is that it restates return fields already documented in the output schema while omitting any note on result volume.

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?

The tool takes zero parameters, so there is nothing for the description to disambiguate. Baseline of 4 applies for a no-argument tool.

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?

States a specific verb and resource ('Listet alle verfügbaren SBB Open Data Datensätze ... auf') and names the source domain (data.sbb.ch). It is clearly distinguishable from the sibling getters by resource (a catalog of datasets vs. domain-specific data), though it never explicitly contrasts itself with them.

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?

'Nützlich zur Übersicht und Entdeckung neuer Datensätze' implies a discovery/overview use case, which is reasonable guidance. However, it gives no explicit when-to-use vs. when-not conditions, no mention of how it relates to the sibling retrieval tools, and no prerequisites.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint and destructiveHint=false, so safety is covered structurally and the description doesn't need to repeat it. The description usefully adds the data scope (UIC numbers, coordinates, cantons, operator info) and the return format, but omits any note on auth, rate limits, or result completeness.

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?

Purpose is front-loaded and the Args/Returns structure is easy to scan. There is mild redundancy between the Args list and the Returns schema line, but no wasted filler.

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?

For a single-object, four-parameter read tool with an output schema, the description covers purpose, parameters, and the returned fields (name, uic, canton, operator, coordinates). Nothing essential to invoking it correctly is missing.

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?

Reported schema description coverage is 0%, so the description must carry parameter meaning, and it does: it enumerates query (min 2 chars, examples), canton (canton code examples), limit, and response_format with its allowed values. This compensates well for the thin coverage, though it doesn't explain limit's max of 100 or canton's exact format constraints.

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?

States a specific verb (Sucht) and resource (Bahnhöfe und Haltestellen der Schweiz) and clarifies the scope as the BAV DiDok list covering all ÖV stops, not just SBB. This disambiguates from an SBB-only assumption, but it never contrasts itself with the related sibling sbb_compare_stations or the other get_* tools.

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?

Usage is implied by the scope clarification ('alle ÖV-Haltestellen, nicht nur SBB'), which tells the agent when this tool is appropriate for broad stop lookups. However there are no explicit when-to-use/when-not rules and no mention of alternatives such as sbb_compare_stations for comparing two stops.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.