KGLD Reserve Attestation

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

No annotations are provided, so the description carries the burden. It discloses that the tool returns a public PDF URL, hash, custody amount, auditor name, reply domain, contract addresses, and independent verification steps. It also explicitly frames the tool as a way to verify without trusting the server, which is a meaningful behavioral trait. It doesn't mention potential network calls or failure modes, but for a read-only info tool this is reasonably transparent.

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 well-structured, front-loading the core purpose and then listing contents and verification steps. The bilingual repetition (English and Korean) doubles the length, but both versions are concise and the Korean adds accessibility. It earns its place by covering purpose, contents, and usage in a compact form.

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, no-output-schema tool, the description is quite complete: it names the resource, the data fields, and the verification workflow. It doesn't specify the exact response format or whether the PDF URL is directly accessible, but the description gives enough for an agent to call it and interpret the result. The sibling tools are not explicitly differentiated, but the 'start here' guidance mitigates that.

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 has zero parameters, so the schema is trivially complete. The description adds value by explaining what the returned data contains and how to use it, which is more than the empty schema provides. Baseline 4 for zero params 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 clearly states the tool returns an independent auditor's proof-of-reserve report for KGLD, listing specific contents: PDF URL, SHA-256, as-of date, attested custody, auditor name, reply domain, token contract addresses, and verification steps. It also explicitly says to start here for any 'is KGLD really backed' question, which distinguishes it from siblings like get_reserve.

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 provides clear context: use this tool for any question about whether KGLD is really backed, and it explains how to verify without trusting the server. It doesn't explicitly contrast with get_reserve or request_verification, but the 'start here' phrasing gives strong usage guidance. A slight gap is not naming when to use get_reserve instead.

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 provided, the description carries the full burden. It discloses data provenance (issuer's own tally), units, the assurance limitation, and directs verification to a sibling tool. It does not discuss auth, rate limits, or exact output shape, but these are less critical for a zero-parameter read-only tool.

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 compact, front-loaded with the tool's core purpose, and every sentence adds value. The Korean duplicate is quick and relevant for the stated locale, and the important caveat about auditor assurance appears early rather than 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?

This is a zero-parameter, read-only tool with no output schema, and the description covers its result contents, units, provenance, limitations, and verification path. There is nothing an agent needs to call it correctly that 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?

The input schema has zero parameters, so the baseline for this dimension is 4. The description still adds semantic context by listing the fields an agent should expect in the result, which is more useful than an empty schema alone.

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 ('get') and resource ('reserve'), then enumerates exactly what is returned: custody gold weight in grams and troy ounces, on-chain total supply, and mintable allowance. It also distinguishes this tool from get_attestation by noting this is the issuer's own tally, so an agent can tell the two apart.

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 explicitly marks this as the issuer's own KorDA tally and advises verifying supply on-chain via get_attestation.contracts, and it warns that auditor assurance only extends to get_attestation.asOf. This gives clear when-to-use and when-to-alternative guidance.

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 full burden and excels: it discloses that the auditor replies directly to the requester's email (not through this server), that the reply cannot be fabricated by the issuer, that the response returns verificationCode and expectedSenderDomain, and that it may take business days or not be answered. This is rich behavioral context for an asynchronous, externally dependent operation.

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 moderately long but front-loaded with the core action and every sentence adds functional detail (flow, verification steps, caveats). The Korean translation adds redundancy but serves a bilingual audience; overall it is structured logically and 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?

With no output schema, the description explains the return values (verificationCode, expectedSenderDomain) and how to use them for verification against get_attestation. It also covers time expectations and the 'call once per report' constraint. For a single-parameter tool, this is fully complete.

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 schema covers ownerEmail with a Korean description, but the tool description adds meaningful context: it clarifies the email is the requester's address and that the auditor replies directly to it, explaining the trust model beyond the schema's format. This adds value beyond the schema's baseline coverage.

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 the tool's action: 'ask the independent auditor to confirm the reserve report by email' with a specific verb and resource. It distinguishes itself from siblings (get_attestation, get_reserve) by being a request for human verification rather than a retrieval, making its purpose unambiguous.

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 explicit usage guidance: ask the user for their email before calling, call once per report, and warns that the operation may take business days or go unanswered. It references get_attestation for verification steps, implying when this tool is relevant, though it does not explicitly state when not to use it or contrast it directly with siblings.

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