Japan Drone Rule Pre-check (partial coverage)

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 and openWorldHint, so safety is covered; the description adds genuine behavioral context by describing the four-valued verdict per check (applies / does_not_apply / possible_check_required / unknown), the I/II/III category, permission_needed, and a per-check receipt. The 'Reference only' caveat and DIPS escalation rule set expectations about reliability, which is valuable for an agent acting on the 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?

Front-loaded as a single interrogative sentence that frames the tool's purpose, followed by the return shape and two short caveats. The parenthetical check list is dense but each item carries information about coverage; 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?

For a 17-parameter, open-world lookup with a full output schema and read-only annotations, the description supplies what the structured fields cannot: the enumerated rule checks, the four verdict values, the category/permission outputs, and the advisory-only limitation. An agent has enough to call it correctly and interpret the response.

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 17 parameters (including defaults such as 'Omitted = reported unknown' and the JST offset convention) are already documented in the schema. The description only gestures at the inputs via 'this point, time and height' and the check list, adding little beyond the structured fields; 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?

States a specific question the tool answers — which Japanese drone rules apply at a given point, time and height — and enumerates the concrete checks returned (DID 2020, 150 m, night, airport screening, Small UAS Act facilities, MLIT emergency airspace, flight methods, 25 kg). This is clearly distinguishable from siblings like drone_rule_table (static table) and get_receipt (receipt lookup).

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?

Gives explicit framing ('Reference only') and a fallback for uncertainty ('uncertain = check DIPS'), plus a negative scope ('no applications prepared'), which tells the agent this is advisory, not a filing tool. It does not, however, name the sibling drone_rule_table or state when to prefer that over this one.

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=false, so the safety profile is covered. The description goes further by describing the substance of the returned data, including that Art. 132-85/86 triggers can be waived with certificates and that screening radii come with a documented basis and version — useful behavioral context beyond 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?

Two sentences: a front-loaded question that anchors the tool to its consumer, then a dense enumeration of contents. Every clause carries information and the qualifying 'Reference only' lands at the end where it is easy to scan.

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-value documentation is already handled, yet the description adds the domain framing (statute articles, waiver certificates, guideline version and sources) an agent needs to interpret the table. Zero parameters plus read-only annotations mean nothing is left uncovered.

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 the baseline is 4; there is nothing parameter-related the description needs to compensate for. The description correctly spends its words on return content instead of nonexistent inputs.

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 ('Returns the rule table') and immediately frames it as the data behind the sibling drone_flight_check, so an agent can separate the reference tool from the checking tool. It also enumerates the table's contents (triggers, category definitions, screening radii, guideline version), leaving no ambiguity about what comes back.

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 'Reference only' signals this is consultative data rather than an action, which implicitly steers the agent to drone_flight_check for actual checks. However, there is no explicit when-to-use/when-not statement or named alternative for performing a check, so the guidance remains implied rather than stated.

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.