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travelpulse

TravelPulse: Global travel intelligence API for AI agents: weather, hotel deals, theme-park wait times, translation, trip plans, visas, health, currency, insurance, points. Any destination + language. x402 USDC (Base + Solana); no accounts, no keys.

Coverage: Global

Endpoints: • waits ($0.05): Live park wait times • hours ($0.05): Park hours and schedule • crowds ($0.08): Crowd prediction • weather ($0.15): Travel weather forecast • deals ($0.08): Travel deals • plan ($0.20): Trip itinerary • visa ($0.08): Visa requirements by nationality and destination • insurance ($0.08): Travel insurance comparison and recommendation • pack ($0.10): AI packing list by destination, climate, and activities • budget ($0.10): Daily travel budget by destination and style • currency ($0.08): Currency exchange rates and money tips for destination • phrasebook ($0.05): Essential travel phrasebook by destination language • translate ($0.03): Real-time travel translation (menus, signs, conversations) • health ($0.08): Destination health advisories and vaccine requirements • fare-intel ($0.12): Flight fare intelligence — when to book, cheapest months • points ($0.12): Points & miles redemption optimizer • trip-check ($0.50): One-call pre-booking trip clearance (visa + health + safety + weather + money) • disruption ($0.25): Flight disruption risk for an airport and date • check ($0.05): Flight compensation eligibility — EU261 / UK261 / Canada APPR / Brazil ANAC 400 / Turkey SHY / India DGCA (deterministic) • letter ($2.00): Citation-backed flight compensation claim letter (6 regimes, ready to send)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toNoDestination currency or country name
dateNoYYYY-MM-DD, default today
daysNodays
fromNoHome currency (e.g. USD, EUR, GBP) — default: USD
goalNoRedemption goal, e.g. 'business class to Japan' or 'free hotel week in Europe'
langNolang
parkNoPark name or slug e.g. magic-kingdom, universal-studios-florida, europa-park
textNoText to translate
cabinNoeconomy | premium_economy | business | first
datesNoTravel window, free-form (e.g. 2026-09-10 to 2026-09-20)
focusNoPhrase focus area (transport, food, emergency, shopping, all)
routeNoRoute, e.g. 'LHR-JFK' or 'London to Tokyo'
styleNostyle
actionYesWhich endpoint to call. Options: waits | hours | crowds | weather | deals | plan | visa | insurance | pack | budget | currency | phrasebook | translate | health | fare-intel | points | trip-check | disruption | check | letter
amountNoAmount to convert for reference calculation
budgetNobudget
reasonNoCause per the carrier (default unknown — burden of proof is the carrier's)
regionNoCountry/region the user holds cards/programs in
airlineNoAirline name for the letter
airportNoAirport IATA code or city (e.g. JFK, Heathrow, Frankfurt)
contextNoContext hint (menu, sign, conversation, product)
purposeNoVisit purpose (tourism, business, nomad, transit)
to_langNoTarget language (default: English)
bag_typeNoLuggage constraint
durationNoTrip duration in days
passportNoPassport nationality (e.g. US, UK, India, Brazil, Nigeria). `nationality` accepted as an alias.
programsNoComma-separated list of programs/cards the user holds
from_langNoSource language (auto-detected if omitted)
trip_typeNoTrip type — determines coverage priorities
activitiesNoPlanned activities (e.g. hiking, beach, business, diving, winter sports)
disruptionNodelay | cancellation | denied_boarding | baggage_delay | baggage_damage | baggage_loss (default delay)
claim_valueNoBaggage claims: documented damages with currency (e.g. '480 USD') — demanded in the letter, capped by the Montreal limit
delay_hoursNoArrival delay at final destination in hours (e.g. 4.5)
destinationNodestination
distance_kmNoGreat-circle distance override for airports outside the reference table
flexibilityNoexact | ±3days | month
flight_dateNoFlight date YYYY-MM-DD
nationalityNoTraveler nationality — some vaccines required only for specific nationals
notice_daysNoCancellations: days of advance notice
carrier_sizeNoCanada APPR carrier size (default large)
duration_daysNoTrip duration in days
flight_numberNoFlight number (e.g. LH400)
trip_cost_usdNoTotal prepaid trip cost in USD — for cancellation coverage sizing
trip_durationNoTrip duration (affects prophylaxis recommendations)
month_or_datesNoTarget month or dates
passenger_nameNoPassenger name (placeholder used if omitted)
carrier_countryNoOperating carrier home country ISO code, or EU (default EU)
block_time_hoursNoIndia DGCA cancellations: scheduled block time in hours (estimated from distance if omitted, labeled [ESTIMATE])
bag_received_dateNoBaggage claims: date the bag was returned/received (YYYY-MM-DD) — computes the Art. 31 complaint deadline

TDQS

A3.7/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It reveals useful behavioral traits: per-call pricing for every endpoint, payment via 'x402 USDC (Base + Solana)', 'no accounts, no keys', and 'deterministic' for the check endpoint. However, it does not explicitly state read-only nature, output format, rate limits, or side effects, leaving transparency incomplete.

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 and front-loaded: a compact intro, coverage line, and an alphabetized bullet list that combines endpoint name, price, and purpose in one line each. Every sentence and bullet adds value with no filler or redundant elaboration.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 49 parameters, 20 actions, and no output schema, the description gives a strong overview but lacks per-endpoint parameter requirements and output details. For example, it does not clarify which parameters apply to the 'check' or 'letter' actions versus 'visa' or 'health', leaving an agent to infer parameter-action relationships.

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 coverage is 100%, but many parameter descriptions are tautological ('days', 'style', 'destination', 'budget'). The description adds meaning by explaining endpoint purposes (e.g., 'visa: Visa requirements by nationality and destination'), which hints at relevant parameters, but it does not map specific parameters to each of the 20 actions, a serious gap given 49 parameters.

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 'Global travel intelligence API for AI agents' and enumerates 20 distinct endpoints with specific purposes such as 'Live park wait times', 'Trip itinerary', and 'Flight compensation eligibility'. This is a specific verb+resource framing that distinguishes it from travel-related siblings and makes the tool's function obvious.

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

Usage Guidelines3/5

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

The endpoint list implies when to use each sub-function (e.g., 'visa: Visa requirements by nationality and destination'), but there is no explicit guidance about when to prefer this tool over alternatives, which sibling tool to use instead, or exclusions. Usage guidance is purely implicit through endpoint descriptions.

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

B3.2/5.0
Disambiguation4/5

Each tool has a unique domain prefix (e.g., airdroppulse, alphapulse, arbipulse) making them mostly distinguishable at a glance. A few adjacent verticals like careerpulse vs talentpulse or marketpulse vs dealpulse have overlapping themes, but their descriptions clarify the distinct focus. The utility tools (catalog_search, discover, get_openapi_spec, x402_troubleshoot) are also clearly distinct in role. However, the sheer number of similar 'pulse' names could still cause misselection without reading descriptions.

Naming Consistency4/5

The dominant naming convention is `<domain>pulse` (e.g., climatepulse, cryptopulse, edupulse), which is highly consistent and predictable. Exceptions like catalog_search, discover, get_openapi_spec, x402_troubleshoot, and stateedge break the pattern, but these are few and serve obvious utility purposes. Overall, the convention is clear and easily learnable.

Tool Count2/5

With 80 tools, the server presents an extremely large and potentially overwhelming surface. While each tool represents a distinct intelligence vertical and navigation aids exist (catalog_search, discover, get_openapi_spec), the count far exceeds the typical 3-15 range for coherent agent use and even the 'heavy' 16-25 range. The burden of selecting the correct vertical from 80 options is significant, despite clear naming.

Completeness5/5

The server offers an exceptionally broad and deep coverage of domains, from finance and health to agriculture and gaming. Each vertical includes multiple endpoints that address core operations for its domain, such as search, analysis, comparisons, deterministic checks, and even action-oriented tools like letter generators and physical mail. The presence of free discovery and troubleshooting tools fills potential gaps, leaving no obvious dead ends in the overall tool surface.