variotrip route eSIM configurator

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

Annotations already declare this a safe, idempotent read, so the bar is lower. The description adds real context by disclosing the shape of the data and the exact pricing basis used for comparison (1 GB · 7 days on a one-country route), which tells the agent what the numbers mean and how they can be used in a recommendation.

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?

It is a single sentence with no wasted padding, and the core content (networks + reference price) is front-loaded. The nested parentheticals make it dense and slightly meandering, but nothing is superfluous.

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 no output schema, the description must convey return contents, and it does so adequately: per-network operator name, 4G/5G availability, and a reference price. It leaves the precise comparison semantics (is the listed price the cheapest tier? does it change with currency/bucket?) to inference, but an agent can call it 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 100%, so the schema already explains destination, language, bucket, and currency. The description reinforces the single-country scope for destination but adds no syntax or format detail beyond what the schema provides, so baseline 3 applies.

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 names the resource precisely (mobile networks for one country) and enumerates the returned fields the agent cares about: operator name, 4G/5G, and a reference-route price. It is distinguishable from price_grid and quote_route by its per-network, single-country scope, though it never names a sibling 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 clause 'so you can say which network is the cheapest and what the others add' implies the use case: comparing networks within one country. There is no explicit when-not guidance, no mention of how this differs from price_grid or quote_route for other pricing questions, and no stated 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 readOnly, idempotent, non-destructive and closed-world, so safety is covered. The description adds genuine behavioral context — that content is returned 'in the shop's own words' and precisely which topics are included — which tells the agent what kind of answer to expect and that it is authoritative shop copy rather than computed output.

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 scoping statement is front-loaded before the topic list, and every clause earns its place by naming a covered subject. The single long enumerated sentence is dense but readable; a short structural break before the usage rule would improve scanning.

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 two-optional-parameter read tool with no output schema, the description is nearly complete: the agent knows what to ask it for and what it will not cover. The one remaining gap is the return shape — whether facts come back as prose paragraphs or keyed fields — which would help an agent consume the result.

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 100%, so bucket and language are already fully documented, including their currency/locale effects. The description adds nothing about either parameter, which is acceptable at baseline but no better.

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 resource (variotrip's own-words shop facts) and enumerates exactly what is covered — data pool, trip length, delivery, payment, hotspot, activation, top-ups, support. That enumeration lets an agent distinguish it from price_grid and quote_route without opening any 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?

The closing clause 'Use for any question that is not a price' gives a clear positive rule plus an exclusion, routing non-pricing intent here and pricing intent to the price siblings. It never names a sibling tool explicitly, so the routing is inferred rather than spelled out.

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 read-only, idempotent, non-destructive behavior, so safety is covered. The description adds useful return-content context: countries, selectable network counts, and the starting-price basis (1 GB, 7 days, cheapest network). It does not mention pagination or whether all countries are returned at once.

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?

Two sentences with no filler. The first front-loads what the listing contains, and the second gives use cases; the parenthetical pricing basis is informative 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?

There is no output schema, so the description must explain return values, and it names the key fields and pricing basis. Combined with annotations covering safety and schema covering parameters, it is adequate, though it does not fully describe the response shape.

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 coverage is 100%, so bucket, currency, and language are already documented in the schema. The description adds no parameter-specific semantics, but the baseline is 3 because the schema does the heavy lifting.

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 the resource clearly: every country variotrip can route, plus the returned metrics (selectable network count and starting price). It is distinguishable from sibling tools like get_networks and price_grid by being a country-coverage list, though it does not explicitly name those alternatives.

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?

Explicitly says to use it to check coverage or to see which countries of a trip are available. This gives clear usage context, but there are no explicit exclusions or guidance pointing to siblings for network or price detail.

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 read-only, idempotent, non-destructive, closed-world behavior, so the safety profile is covered. The description adds genuine context beyond that: prices are identical to quote_route, and each grid cell carries its own buy_url, which tells the agent what it gets back despite there being no output schema. It does not mention cost of a wide grid or any rate/size caveats beyond the caps already in the schema.

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?

Two sentences, both load-bearing: the first front-loads the grid shape and caps, the second covers the pricing source and per-cell output. No filler and nothing repeated from the title.

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 six parameters, full schema coverage, and complete annotations, the remaining burden is explaining what a call returns — and the buy_url-per-cell sentence does that without an output schema. An agent could call this correctly; only an explicit contrast with quote_route 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?

Schema description coverage is 100%, so the schema already explains route, days, gb, bucket, currency, and language. The description only restates the max-8 days and max-6 gb caps and gives one example ('e.g. to compare with other providers'), adding little meaning beyond the field descriptions. Baseline 3 is appropriate.

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 states a specific verb and resource ('the same route priced') plus the exact grid dimensions it returns: several trip lengths (days, max 8) by several pool sizes (gb, max 6) in one call. That is enough for an agent to tell it apart from the single-price sibling quote_route, which the description explicitly references as the per-quote equivalent.

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?

It gives two concrete situations to use it: 'to compare with other providers' and 'to find the best fit'. It also implies the relationship to quote_route ('same server prices as quote_route'), though it never states the inverse condition — when a single quote is preferable to the grid — so the routing guidance is clear but not complete.

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?

Beyond the read-only/idempotent annotations, the description explains that this returns the server price the customer would pay, that the quote should be used as returned, and that the result carries a buy_url for reference rather than initiating purchase. This is meaningful behavioral context about pricing semantics and output usage. It does not contradict 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?

The description is dense but front-loaded: it opens with the usage scenario, then defines the quote, then gives the critical 'never compute' instruction, then points to checkout. Every sentence earns its place, and the longer length is justified by the complexity of route quoting and the need to prevent wrong pricing behavior.

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?

Given the output schema exists, the description need not explain return values, but it still usefully notes the buy_url. Combined with 100% schema description coverage and annotated safety hints, the definition gives an agent everything needed to call quote_route correctly and route the customer onward to checkout when appropriate.

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 coverage is 100%, so the baseline is 3, but the description adds useful conceptual meaning: the route is a sequence of 1–8 countries in travel order, a single country is a route of one, and the data pool is shared across the whole route. These details help an agent understand how the parameters combine beyond their individual schema descriptions.

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 states a specific verb and resource: quoting the exact price of ONE eSIM for a whole multi-country route. It defines the quote's scope precisely (countries in travel order, networks, one shared data pool, trip length) and distinguishes it from purchase flow by naming start_checkout. An agent can distinguish it from siblings such as price_grid or recommend_config without opening their schemas.

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?

It explicitly says when to use it: while the customer is still deciding and asks 'how much is …?'. It also states when to switch tools: when the customer wants to buy, call start_checkout, and the schema additionally points unsure agents to recommend_config. It gives a clear exclusion: do not compute, add up, or scale the quoted price yourself.

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 cover the safety profile (readOnly, idempotent, non-destructive), and the description goes well beyond them: it discloses the derivation logic (pool sized from trip length), the exact three-tier output with multipliers, the per-option payload (pool GB, price, reason, buy_url), budget marking, and price parity with quote_route.

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?

Two dense sentences with the trigger condition front-loaded and zero filler; every clause (sizing basis, multipliers, per-option fields, budget check, price parity) carries decision-relevant 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?

For an eight-parameter read-only recommender with no output schema, the description supplies the missing return-value picture (three tiers, their contents, buy_url, budget flags) and the sizing rule, leaving nothing an agent needs before calling.

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 100%, so all eight parameters are already documented, including usage→GB/day mapping and the gb_per_day-wins-over-usage rule. The description only restates the country/days/usage inputs at a high level and adds no syntax or precedence detail beyond the schema, so baseline 3 applies.

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?

Specific verb and resource: it sizes a shared data pool from a described trip and returns three server-quoted routes (exact, ×1.5, ×2). It explicitly differentiates itself from the sibling quote_route by the input framing ('trip instead of a size'), so an agent can pick it without opening either 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?

The first clause is an explicit selection rule ('Use when the customer describes a trip instead of a size') with the inverse condition implied, and it names quote_route to explain the price relationship so the agent knows which sibling to call for a size-based request.

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?

Beyond the annotations, the description explains the customer-facing handoff: it returns a buy_url, final price, and ready-to-send checkout block; the customer pays on the route-builder page; no account is needed; and eSIM delivery happens on screen and by e-mail after payment. This adds substantial context about what invoking the tool does and does not handle.

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 key usage condition and alternative routing. It is somewhat long, but the extra statements about delivery, account requirements, and exclusions are operationally useful rather than 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?

Given the annotations, full schema coverage, and an output schema, the description covers the decision context, alternative tool, customer handoff behavior, delivery expectations, and exclusions. An agent has enough information to select and invoke it 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 100%, so the schema already documents all six parameters. The description adds only that the input matches quote_route, which is a useful cross-reference but not additional parameter semantics beyond the structured schema.

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 states a specific action and resource: the checkout handoff for one route, returning a buy_url, final price, and checkout block. It explicitly distinguishes this from quote_route, so an agent can tell the two apart 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?

It gives explicit timing and customer intent examples ('I'll take it', 'how do I buy?') and names the alternative quote_route for comparison pricing. It also states exclusions such as no in-chat order tracking and no discount codes.

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