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recommend_plans

Recommend up to a few real catalog plans for one destination. Ranks existing SKUs by trip days and usage (light≈0.5 / normal≈1.5 / heavy≈4 GB/day) — never invents prices or URLs. Prefer this for 'what should I buy?'.

Input Schema

NameRequiredDescriptionDefault
daysNoTrip length in days (optional). Prefers plans whose validity is close.
limitNoHow many plans to return (1–8, default 3).
usageNoData intensity: light≈0.5, normal≈1.5, heavy≈4 GB/day (ranking only).
countryYesDestination slug, e.g. 'japan', 'thailand', 'europe'.
max_price_usdNoOptional max USD price filter.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.8/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does meaningful work: it discloses the ranking inputs (trip days, usage multipliers), caps output ('up to a few real catalog plans'), and gives a grounding guarantee ('never invents prices or URLs'). It stops short of stating read-only/no-side-effect behavior or any auth or latency traits, which keeps it below a 5.

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?

Two sentences, front-loaded with the core action, then the ranking rule, then the selection hint. Every clause adds information; nothing is filler.

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

Completeness4/5

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

For a 5-parameter read-style tool with no output schema and no annotations, the description covers what is returned (ranked real plans with prices/URLs) and how ranking works. The exact response shape is not described, but the grounding statement implies its key fields.

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% and every parameter already carries a description, so the schema does the heavy lifting. The description's restatement of the usage multipliers (light≈0.5 / normal≈1.5 / heavy≈4 GB/day) duplicates the enum description rather than adding new meaning.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Recommend ... real catalog plans') plus the scope ('for one destination') and the ranking basis. An agent can tell it is a recommender rather than a raw search, though it never names the sibling it contrasts with (search_esim_plans / get_esim_plan).

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?

'Prefer this for "what should I buy?"' gives a clear intent cue for when to reach for it, but there is no explicit when-not guidance and no alternative tool is named, so routing between this and search_esim_plans is left partly to inference.

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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