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Tankerkoenig

by io.github.pipeworx-io

Tankerkoenig Prices

tankerkoenig_prices
Read-onlyIdempotent

Bulk current fuel prices (E5, E10, diesel in EUR per liter) for up to 10 German gas stations by station id — the efficient refresh call for price-watch and price-alert flows once station ids are known. MTS-K real-time Benzinpreise, Germany only. Example: tankerkoenig_prices({ station_ids: ["94e70fc4-b22f-4e5a-877f-bc1082cdae81", "278130b1-e062-4a0f-80cc-19e486b4c024"] })

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
_apiKeyNoOptional: your own free Tankerkoenig API key (creativecommons.tankerkoenig.de)
station_idsYesList of station UUIDs (1 to 10) from tankerkoenig_stations_nearby

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false. Description adds that it returns prices in EUR per liter for specific fuel types (E5, E10, diesel), is limited to Germany, and is efficient for refresh. No contradictions with annotations.

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?

Extremely concise: two sentences plus an example. Every sentence serves a purpose: first states what it does, second explains usage context, third shows example. Front-loaded with the most critical information.

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?

Despite no output schema, the description adequately describes return values (prices per fuel type in EUR/liter). It covers input constraints (up to 10 stations, Germany only), usage context (efficient refresh), and provides an example. No gaps remain given the tool's simplicity.

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 covers 100% of parameters with descriptions. Description provides a concrete example showing the exact format for station_ids (UUIDs) and optional apiKey. The example adds clarity beyond the schema's property descriptions.

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?

Clearly states it retrieves bulk current fuel prices for up to 10 German gas stations by station ID. Distinguishes from sibling tools like tankerkoenig_stations_nearby (which gets IDs) and tankerkoenig_station_details (which might get details for one). The phrase 'efficient refresh call' reinforces its specific role in price-watch flows.

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?

Explicitly states when to use: 'once station ids are known' and for 'price-watch and price-alert flows'. Implies you should first use tankerkoenig_stations_nearby to get IDs. Does not explicitly list alternatives or when not to use, but the context is clear enough 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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TDQS

A3.8/5.0
Disambiguation2/5

Multiple tools occupy nearly identical roles: ask_pipeworx, ask_pipeworx_beta (explicitly identical right now), ask_pipeworx_grounded, and deep_research all answer research questions; polymarket_edges, bet_research, and polymarket_arbitrage overlap heavily on prediction-market opportunities; entity_profile, compare_entities, and recent_changes overlap on company research. The detailed descriptions help, but the clusters create real misselection risk.

Naming Consistency4/5

Nearly all tools follow a readable snake_case convention, many with verb_noun structure (resolve_entity, list_subscriptions, validate_claim, scan_dependency). Minor deviations exist: tankerkoenig_stations_nearby plural vs tankerkoenig_station_details/prices singular, plus noun-style names like pipeworx_feedback and pipeworx_trending, but the overall pattern is predictable.

Tool Count2/5

34 tools is heavy, and the problem is compounded by the server being named Tankerkoenig: only 3 of the 34 tools relate to German fuel prices while the other 31 are an unrelated Pipeworx/Polymarket/memory/subscription toolkit. This is a sprawling, unfocused surface rather than a well-scoped set.

Completeness3/5

For the nominal Tankerkoenig domain, stations_nearby + station_details + prices cover core lookups, though station search by name and price history are missing. For the broader bundled data/prediction-market domain, coverage is extensive but has notable gaps such as no trade execution, no general web search, and several redundant access paths that complicate the surface.

Resources