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Adaga Network — Direct Booking Federation

network_search

Search the WHOLE Adaga network at once for a stay: fans out to every matching establishment and returns real-time availability with exact total prices (euro cents), sorted by price — like Booking.com but machine-native and commission-free. Workflow: (1) call this, (2) pick an offer (tenant_slug + room_id), (3) call network_book with traveler name and email, (4) hand the payment instructions to the human. Constraints: dates YYYY-MM-DD, checkin < checkout, checkin not in the past, max 30 nights. A tenant that does not answer within 6 s is skipped (reported in errors).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cityNoFilter by city (e.g. Luxembourg); omit to search everywhere
typeNoEstablishment type filter, e.g. 'hotel'
checkinYesArrival date YYYY-MM-DD
checkoutYesDeparture date YYYY-MM-DD
max_total_centsNoBudget cap for the whole stay, in euro cents

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.6/5.0
Behavior4/5

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

With no annotations, the description carries the full behavioral burden and does well: it discloses real-time availability, sorted-by-price output, a 6-second per-tenant timeout, and that non-responding tenants are skipped and reported in errors. It stops short of covering auth requirements or result-set size/pagination limits, so it is not fully exhaustive for a network-fan-out read tool.

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?

Front-loaded with the core capability, then workflow, then constraints — a logical progression with no filler sentences. It is on the dense side, but every clause (price units, sort order, timeout, workflow steps) carries actionable 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?

For a 5-parameter search tool with no output schema, the description supplies the missing return-value context (availability + prices sorted, errors for skipped tenants) and the full calling workflow. An agent can execute the whole book flow from this description alone.

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 description coverage is 100%, so the baseline is 3. The description nonetheless adds semantics beyond the schema: the checkin < checkout and not-in-the-past constraints, the 30-night maximum, and the euro-cents unit for prices/budget, which help the agent form valid calls rather than just valid field types.

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?

States a specific verb+resource ('search the WHOLE Adaga network for a stay') with explicit scope (fans out to every matching establishment) and output characteristics (real-time availability, exact total prices in euro cents, sorted by price). The sibling tools network_book and network_directory are clearly differentiated — this one searches, the description even calls out network_book as the downstream step.

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?

Provides an explicit numbered workflow (call this, pick offer with tenant_slug + room_id, call network_book, hand payment instructions to the human) that tells the agent exactly when and how this tool fits into a larger task. Constraints (date format, checkin < checkout, no past checkin, max 30 nights) further delimit valid 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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