RegBase Japan Corporate Registry Diff

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

No annotations are supplied, so the description carries the full burden. It does disclose provenance (RegBase jp-diff-feed actor) and cadence (daily diff), which implies a read-only, periodically refreshed dataset, but it says nothing about freshness lag, ordering, result volume, or whether credentials are needed.

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 front-loaded sentences with no filler; the resource and scope come first and provenance last. The 'RegBase jp-diff-feed actor' clause is somewhat internal jargon, which keeps it from a 5.

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 should say more about the shape of returned records (fields per company, pagination behavior). It adequately conveys scope and optional filters for a simple three-parameter read tool, but leaves the return contract underspecified.

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 all three parameters are already documented, including the change-type enum values. The description's enumeration of change categories loosely mirrors the change_types filter but adds no syntax or format detail beyond the schema; 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 verb and resource: latest changes in Japan's National Tax Agency corporate registry, enumerating the four change categories (new, changed, closed, revived). An agent knows what it returns, but nothing distinguishes it from siblings like lookup_company or get_snapshot_info.

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?

There is no when-to-use guidance and no alternative named. The phrase 'daily diff' implies it is for recent-change monitoring rather than single-company lookup, but the agent must infer this and receives no signal about when lookup_company or get_snapshot_info would be the better choice.

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?

No annotations are supplied, so the description carries the full burden and does little beyond saying what is returned. It does not state that the call is read-only and side-effect free, whether it hits a bundled/static resource or a live service, expected cost, or the shape of the response, all of which matter for a tool with zero annotation coverage.

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 a colon-delimited list of returned fields and no filler. Every word contributes to identifying the resource and its output.

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 and no output schema, the description correctly compensates by enumerating what the call reports, so an agent knows what it gets back. The remaining gap is behavioral (static vs. live, cost, read-only nature) rather than structural.

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 no parameters, so there is no argument semantics to explain; the baseline for a zero-parameter tool applies. Nothing in the description misleads about 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?

The description pairs a specific verb ("Describe") with a specific resource ("bundled registry snapshot") and enumerates the returned fields (record counts, as-of date, source). It is clearly not the diff, company-lookup, or signature-verification sibling, though it never names them 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?

Usage is only implied: an agent can infer this is a metadata/status call to check snapshot provenance or freshness, but the description never states when to call it versus get_latest_diff or what condition warrants it. No exclusions or prerequisites are given.

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?

No annotations are supplied, so the description carries the full burden, yet it discloses almost no behavior: nothing about the result format, whether matching is case-sensitive or partial-prefix, how many records come back, or what happens when zero companies match. The only behavioral hint is provenance ("Mirrors the RegBase jp-company-lookup actor"), which implies an external data source but adds no operational detail.

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 tight sentences, with the lookup key and its two modes front-loaded before the provenance note. Nothing is redundant and no sentence 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 an external-lookup tool with no annotations and no output schema, the description does not say what the response looks like, whether results are paginated or capped, or how failures/no-match cases surface. An agent knows how to call it but not what to expect back.

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 description adds real meaning for "query" beyond the schema's generic "Corporate number or company name substring": the 13-digit exactness constraint and the Japanese-or-English language support. However, with only 50% schema coverage, "max_results" is undocumented in both places (no unit, no ceiling, no behavior description), which the description does not compensate for.

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 a specific verb and resource ("look up a Japanese company") and states the two accepted input forms with enough precision that an agent can distinguish it from the sibling tools (diff, snapshot info, signature verification), which deal with entirely different objects.

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 implies when each query mode applies (exact 13-digit number vs. name substring, in Japanese or English), which is useful routing guidance, but there is no explicit statement of when to prefer this tool over alternatives or of any prerequisites. The sibling tools are unrelated, so the practical ambiguity is low.

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?

With no annotations, the description carries the full disclosure burden. It usefully discloses the signature scheme (Ed25519), the key source (published T3 public key, key_id derived at runtime), the offline mode, and the upstream actor it mirrors — genuine value. But it says nothing about outcome semantics: what is returned on a valid vs. invalid signature, whether failure raises an error, or whether the call has any side effects.

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 tight sentences with the core action front-loaded and supporting detail (key source, actor parity) following. No filler, though the actor-mirroring clause is only marginally useful to an agent selecting the tool.

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 is the only place a verification result could be explained — and it omits that entirely. For a verification tool, knowing whether the return is a boolean, a report object, or an exception is central to invoking 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 coverage is 100%, so the single 'record' parameter is documented, giving a baseline of 3. However, the schema's own description is bare ('The signed record object to verify') and the description adds no information about the nested structure the record must carry (payload, signature, key_id), which matters for a nested-object parameter.

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?

Names a specific verb ('Verify') and a specific resource ('RegBase Ed25519-signed company evidence record') with crypto-level detail. The operation is clearly distinct from the sibling read tools (get_latest_diff, get_snapshot_info, lookup_company), though the description never explicitly contrasts itself 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?

Usage is only implied: an agent infers it should call this when it holds a signed record and needs offline authenticity checking. There is no explicit when-to-use, no statement of prerequisites, and no mention of when not to use it or what to do instead.

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