esimdata: travel eSIM comparison

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

Annotations already declare this as a safe, idempotent read operation. The description adds useful behavioral context beyond annotations by identifying the data source as the manufacturer's published list, noting regional exceptions such as mainland China models, and indicating that a source link is returned.

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 front-loaded sentence with no wasted material. The parenthetical regional-exception note is relevant and compactly presented.

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 one-parameter, read-only lookup tool with full annotation coverage, the description supplies the key missing context: data provenance, regional caveats, and the fact that a source link is included. Nothing essential for correct invocation is absent.

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. The description adds meaning by clarifying that the model parameter covers phones, tablets, and watches, whereas the schema examples only mention phone models.

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: checking whether a phone, tablet, or watch model supports eSIM. It also distinguishes the tool from sibling plan/provider tools by focusing on device compatibility and naming the authoritative source.

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 context is clear: use this when verifying eSIM support for a specific device model. It does not explicitly state when not to use it or name alternatives, but no sibling tool serves the same purpose, so the routing gap is minimal.

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, closed-world, so safety is covered. The description adds real behavioral detail beyond them: results are aligned on the same fields and returned in the caller's input order, which matters for reliable comparison 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?

A single sentence with zero filler; the count constraint, the id source, the ordering rule, and the purpose are all packed in without redundancy.

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 one-parameter read tool with no output schema, the description is nearly sufficient: it conveys input source, cardinality, ordering, and that results are field-aligned. It does not tell the agent which fields are compared or what happens with an invalid/duplicate id, but those are minor.

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 0%, so the description must carry the param semantics — and it does: it identifies plan_ids as ids sourced from search_plans, states the 2–10 range (matching minItems/maxItems), and specifies that array order is preserved in the output.

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 verb ('put side by side') and resource ('plans'), with explicit bounds (2 to 10) and an ordering guarantee. It is clearly distinct from get_plan (single plan) and search_plans implicitly, though it never names the single-plan alternative 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?

'ids from search_plans' names the upstream tool that supplies inputs, and 'to help a traveller choose' gives the decision-making context for using it. It stops short of stating when NOT to use it (e.g., for a single plan, use get_plan).

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 the description doesn't need to cover safety. It adds meaningful context by detailing the aggregate return contents (counts, cheapest plan, per-GB price, networks) — valuable since no output schema exists — though it doesn't mention what happens for an unknown country.

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?

One sentence with no wasted words, and the overview framing is front-loaded ahead of the field list. It is slightly dense but every clause maps to real output content.

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 and full annotation coverage, the description's enumeration of return fields fills the main gap an agent would have. Only minor omissions remain, such as behavior for unsupported countries or output structure.

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?

There is a single parameter with 100% schema description coverage, including accepted formats (English name, ISO code, alias). The description adds nothing about the parameter, so the schema does all the work — the baseline 3 for high-coverage single-param tools 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 (eSIM market for a country) and enumerates exactly what the response contains: plan/provider counts, cheapest plan, cheapest per GB, and network lists. This lets an agent distinguish it from plan-level siblings like get_plan or search_plans, though it never explicitly contrasts with them.

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?

"A destination at a glance" implies the overview use case, so an agent can infer this is the right first stop for a country-level summary. However, there is no explicit when-to-use vs. the sibling tools (compare_plans, search_plans, list_providers) and no stated prerequisites or exclusions.

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/closed-world, and the description goes beyond them by enumerating exactly what comes back: countries covered, networks, policies, provider page, buy link, and price history. It doesn't mention rate limits, error behavior for stale ids, or depth of the price history, so it's strong but not exhaustive.

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?

One front-loaded sentence with no filler — the purpose comes first and the return-contents list follows. The list of fields is dense and unprioritized, but every clause carries 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?

Since there is no output schema, enumerating returned fields (coverage, networks, policies, buy link, price history) is exactly the missing information and it's supplied here. Remaining gaps — unknown-id behavior and how much price history is returned — are minor for a simple read-only lookup.

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?

With one parameter at 100% schema coverage, the schema already carries type and example format; the description adds the meaningful semantic that the id comes from a prior search_plans call, telling the agent how to obtain a valid value rather than guessing.

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 and scope: 'everything esimdata knows about one plan' keyed by an id, and explicitly attributes that id to search_plans, which separates it from the sibling list/search tools. A slight gap is that the retrieval verb itself is implicit rather than stated.

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 parenthetical '(by the id search_plans returned)' implies the chained workflow — call search_plans first, then fetch with this tool — which is real, actionable guidance. However, it never states when NOT to use it (e.g., use compare_plans or country_overview instead) or what happens with an unknown id.

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 this as a safe, read-only, idempotent, non-destructive operation. The description adds useful context beyond annotations: it discloses that the response includes each provider's website and whether esimdata earns a commission, and it explicitly states that ranking never depends on commission.

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 a single well-formed sentence with no wasted words. It front-loads the core purpose and packs the two key details (website and commission status) plus the ranking caveat efficiently.

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 zero-parameter, read-only list tool with no output schema, the description is complete enough: it says what is listed and what fields each entry carries. An agent can invoke it correctly without further information.

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?

The tool takes zero parameters, so there is no parameter semantics to explain. The baseline for a parameterless tool is 4, and the description does not need to compensate for any schema gaps.

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 clearly states that this tool lists every eSIM provider tracked by esimdata and indicates what each entry includes (website and commission status). This is a specific verb+resource definition, though it does not explicitly differentiate itself from siblings like compare_plans or search_plans.

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?

Usage is implied: call this when you need a directory of providers and their commercial relationship with esimdata. However, there is no explicit guidance on when to prefer this over siblings such as search_plans or compare_plans, nor any stated exclusions or 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 the safety profile is covered. The description adds genuinely new behavioral context: results are ranked neutrally rather than by sponsorship, each result carries a buy_url and a price-check timestamp. It does not state what happens on an unrecognized country or how truncation by limit is signaled.

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?

Three sentences, all load-bearing: scope and ranking first, filter dimensions second, return-value shape last. No repetition of the title and no 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?

With 10 parameters and no output schema, the description usefully discloses the key return fields (buy_url, last-checked time) and the ranking model. Remaining gaps are minor but real: default result count, behavior on an unknown destination, and empty-result semantics are left to the schema or unspecified.

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 every parameter's meaning is already documented. The description only restates the filter categories and sort options at a high level, adding no syntax, default, or edge-case detail beyond the schema. Baseline 3 is appropriate when the schema carries the full load.

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 verb and resource (find travel eSIM data plans), the scope (every provider esimdata tracks), and the ranking model (neutral, price / price-per-GB / validity). This makes it clearly distinguishable from siblings like compare_plans, country_overview and get_plan, which operate on a narrower or already-selected set.

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 description gives a clear picture of when this tool fits: destination-based discovery with filtering by trip length, data, unlimited, needs and budget. However, it never explicitly contrasts with compare_plans or country_overview, so an agent must infer which sibling to pick for a comparison or an overview.

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