Hive Oracle

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It explicitly reveals that the response includes a price, timestamp, and oracle signature, and importantly discloses that the backend is pending (Q3 2026), which is a significant availability caveat. It does not address authentication, rate limits, or read-only nature explicitly, but the disclosed information is substantive and goes beyond a simple action statement.

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 two sentences, front-loaded with the main action, and includes only essential details: what is fetched, what the response contains, and a crucial availability note. No filler or redundant phrasing. Every sentence adds value.

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?

Given the low complexity (single parameter, no output schema), the description adequately covers what the tool does, what the response looks like, and the current backend status. It does not explain how the signature might be used with the verify_signature sibling, but that is not necessary for basic comprehension. Minor omissions like potential failure modes or authentication are acceptable for a quote-fetching 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?

The schema covers the single 'symbol' parameter fully with examples and a description. The tool description adds no additional parameter-level detail beyond 'for a given symbol,' which is redundant with the schema. Per the high schema coverage baseline, a score of 3 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 action ('Fetch') and the resource ('a cryptographically signed price quote'), and specifies the input ('for a given symbol'). It distinguishes from siblings like list_feeds and verify_signature by focusing on quote retrieval rather than enumeration or verification. The subsequent sentence about response contents reinforces the purpose.

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 phrase 'for on-chain verification' implies a use case, and siblings like verify_signature hint at a related workflow, but the description does not explicitly state when to use this tool versus alternatives, nor does it mention exclusions or preconditions. Usage context is implied rather than clearly guided.

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 behavioral disclosure burden. It explicitly states the tool is backend pending (Q3 2026), which is critical availability information, and describes the return catalog contents. It could mention whether the operation is read-only or requires authentication, but 'List' inherently signals a non-destructive 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 two tight sentences. The first sentence states the action and scope; the second specifies the return fields and adds a crucial timeline note. There is no redundant or filler 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?

For a parameterless list tool with no output schema, the description is complete: it states what will be listed, what the return catalog contains, and the current backend status. The sibling tools and lack of parameters make this sufficiently contextualized.

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 input schema provides no semantics to clarify. The description correctly omits parameter details, and the 0-param baseline of 4 applies. No additional value is needed here.

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 uses a specific verb ('List') with a clear resource ('all available oracle data feeds') and enumerates feed types (price, off-chain event, index), making its purpose unmistakable. It also distinguishes itself from siblings like get_price or subscribe by focusing on catalog listing rather than retrieval or subscription.

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 clearly implies when to use this tool: when you need an overview of all available feeds and their metadata. It does not explicitly mention alternatives or exclusions, but the catalog-oriented phrasing and sibling context provide sufficient 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?

No annotations are provided, so the description carries the full burden. It discloses key behavioral traits: settlement via USDC/x402 on specific chains, the return of a subscription_id, and a significant caveat: 'Backend pending (Q3 2026).' This addresses operational status and limitations, though it does not cover authentication or delivery mechanism details.

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 and front-loaded with the core action ('Subscribe to threshold-triggered oracle notifications'). It includes essential context (chains, settlement, return value, backend status) in just two sentences, with every detail earning its place.

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?

Given the tool's simplicity (2 parameters, no output schema, no annotations), the description provides sufficient context: it explains what the tool does, what to expect as a return value, and even flags backend unavailability. This is complete for an agent to decide and invoke 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?

The input schema already provides full descriptions for both parameters (symbol and threshold) with 100% coverage. The description does not add additional semantics beyond what the schema states, so the baseline of 3 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's function: 'Subscribe to threshold-triggered oracle notifications for a symbol.' This specific verb+resource phrasing distinguishes it from sibling tools like get_price and list_feeds by focusing on the notification subscription action. It also mentions the return value and supported chains, reinforcing the purpose.

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 clear context that this tool is for setting up threshold-based notifications, which implies when to use it (when you need alerting on price thresholds) versus siblings that fetch prices or list feeds. However, it does not explicitly state alternatives or exclusions, so it stops short of a 5.

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 discloses the boolean return type and a critical backend pending status (Q3 2026), which is essential for an agent to set expectations. It does not mention error handling or side effects, but for a verification tool, these are likely implied.

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, each with clear value: purpose, return type/use case, and backend status. No redundant phrasing.

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?

Given the simple verification nature and full schema coverage, the description covers purpose, return behavior, and a major limitation. It could benefit from stating error behavior, but the backend pending note adds significant context.

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 already describes both parameters (sig and quote) with complete coverage, so the description adds little beyond naming the target of verification. It correctly maps the purpose to the parameters, but no additional format or constraint details are provided.

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?

Clearly states the action ('Verify the cryptographic signature') and the resource ('oracle quote'), distinguishing from sibling tools like get_price, list_feeds, subscribe which focus on data retrieval. The return type is also specified.

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?

Provides context that it is used to confirm data provenance in smart contracts and agent workflows, implying when it should be invoked. However, it does not explicitly contrast with sibling tools or mention when not to use it, so a clear exclusion is missing.

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