Japan National Exam Pass Results

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

Annotations already declare readOnlyHint=true, so safety is covered. The description adds the content categories returned (prices, licensing, limits, freshness), which is useful context, but an output schema exists and would surface the same structure, so the incremental disclosure is modest.

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 front-loaded sentence with no filler; every clause enumerates distinct payload content, so nothing is wasted.

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 parameters, a read-only annotation, and an output schema present, the description need not explain return values or safety. It is nearly complete for this simple tool; only a hint about when to reach for it 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?

The tool takes zero parameters, so there is nothing for the description to disambiguate. Baseline 4 applies under the '0 params' rule.

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?

Clear verb ("List") plus resource ("the tools of this server") and an enumeration of the payload contents (prices, data sources, licensing, daily limits, freshness). It is plainly distinguishable from siblings like get_receipt or drone_flight_check, though it does not explicitly name or contrast 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?

No explicit when-to-use or when-not-to-use guidance is given; usage is only implied by the discovery framing ("the tools of this server"). An agent can infer this is the entry point for learning available tools and pricing, but nothing states that intent directly.

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 readOnlyHint=true and openWorldHint=true, so safety and external-source traits are covered. The description adds genuinely new context beyond that: rows come back in page order, each row carries session, announcement date, consistency check, page URL and retrieved_at, and status is 'unknown' when a page was not or could not be read. The only gap is that it does not state pagination behavior beyond the limit cap.

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 front-loaded with the core question the tool answers and the alternative-tool routing comes last. It is efficient, though enumerating the returned column names overlaps with the existing output schema and could be trimmed.

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 an output schema covering return values and annotations covering the read-only, open-world profile, the description only needs scope and routing, both of which it supplies, plus the useful 'unknown status' caveat. It stops short of explaining list size or refresh cadence, which leaves a small gap for a listing tool.

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, limit, and the schema already documents it fully (1-100, default 50) at 100% coverage. The description adds no meaning about how the limit interacts with page order or whether exceeding available exams truncates silently, so the 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 states a specific verb and resource (list national exams on MHLW's current pass announcement list) plus the payload (examinees, passers, pass rate, all candidates) and the row granularity (one row per exam in page order). It also names the sibling exam_results_lookup as the tool for a different scope, so an agent can distinguish the two 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?

It explicitly routes the agent: use this tool for the current announcement list, and use exam_results_lookup for new graduates, revisions and earlier sessions. That is both a when-to-use and a when-not-to-use statement naming the alternative.

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 readOnly/openWorld annotations, the description discloses return constituents (consistency check, revisions, source URL, retrieved_at, page SHA-256) and the three status values including the important not_found_in_checked_records case, which tells the agent that absence is scoped to checked records rather than proof of nonexistence. It also explains the session default ('omit for every session this service has read'). It stops short of describing coverage limits or freshness beyond retrieved_at.

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 core question and inputs are front-loaded, and the sentence listing return fields is compact. It is dense but nearly every clause carries information; 'Check the official page' is the only near-boilerplate line, though it usefully signals authority for the numbers.

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?

An output schema exists, annotations cover safety, and all parameters are documented, so the description only needs to add framing — which it does by explaining status semantics, provenance fields, and the session default. Nothing an agent needs to call this correctly appears to be 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 coverage is 100%, so both parameters are already documented with accepted id/name forms and the dai N kai session convention. The description restates the exam forms (nurse/physician, Japanese or English) without adding syntax or disambiguation rules the schema lacks, 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 opens with a specific question form that states the resource precisely: applicant/examinee/passer counts and pass rates for Japanese national exams as published by MHLW. A verb+resource is clearly implied and the scope (all candidates and new graduates) is named, though it never distinguishes this lookup from the sibling exam_results_list.

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 only implied: supply an exam identifier and optionally a session to get that exam's published results. There is no statement about when to prefer this over exam_results_list (which presumably enumerates available exams) or catalog, and no prerequisites beyond 'Check the official page.'

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 readOnlyHint=true, the description discloses pricing ('Free'), error behavior for unknown/unsettled ids (RECEIPT_NOT_FOUND), and a retention window (30 days after settlement). These are substantive operational facts an agent cannot get from the annotations or 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?

Three short sentences, front-loaded with the purpose, followed by cost, error case, and retention. No sentence is redundant and nothing is buried.

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 an output schema present, return values need no explanation, and the annotations cover safety. The description still covers cost, failure mode, and data lifetime, leaving no material gap for an agent calling this single-param read tool.

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% and the schema already documents the 'rcpt_' + 64 hex format, so the baseline is 3. The description adds semantic constraint by implying the id must belong to a settled paid call, which goes slightly beyond the schema's format-only documentation.

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 opens with a specific verb+resource: 'Re-fetch the stored result of a settled paid call by its receipt_id.' This is unambiguous and an agent can immediately tell what the tool returns and what it operates on, even though the sibling tools are unrelated.

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 states the triggering condition clearly ('for when the response was lost after payment'), which is exactly the scenario that should select this tool. It also implicitly scopes usage to settled calls via the RECEIPT_NOT_FOUND note, though it names no alternative tools for other recovery paths.

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