Hive DePIN

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

No annotations are provided, so the description carries full burden. It does not disclose side effects (e.g., whether the listing goes live immediately), required permissions, rate limits, or any post-creation behavior. Only mentions metadata fields and fee.

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 short (two sentences), but the first sentence front-loads examples rather than stating the core purpose. It could be restructured to immediately clarify 'Creates a listing for physical infrastructure capacity'.

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 creation tool with no output schema, the description should explain what the tool returns (e.g., listing ID, confirmation). It also lacks guidance on parameter usage across different provider categories. The 22 metadata fields are mentioned but not detailed, leaving gaps.

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% but the tool description adds minimal semantic enrichment beyond listing examples. It does not explain parameter relationships (e.g., which parameters apply to which provider category) or constraints, leaving the agent to rely solely on schema descriptions.

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 conveys that the tool lists physical infrastructure capacity with examples, but uses the verb 'List' which could be misinterpreted as querying rather than creating, despite the tool name 'create_listing'. The purpose is clear enough but the verb choice is slightly ambiguous.

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 guidance on when to use this tool versus siblings like 'depin_list_providers' or 'depin_get_match_fee'. The description mentions a match fee but no context about prerequisites, alternatives, or typical scenarios.

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 mentions the current fee value (0.15%) and that it returns currencies and chains, but does not disclose authentication requirements, rate limits, or whether the call is idempotent. The behavior is partially transparent but lacks important context.

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 a single sentence that is front-loaded with the key action and result. No unnecessary words or redundancy.

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 tool, the description covers the core purpose and return context. However, it lacks details like why the fee matters, how to interpret the returned data, or any caching behavior. A bit more context would improve completeness.

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 no parameters and is fully covered. The description adds meaning by stating the return includes 'settlement currencies and chains', which clarifies the tool's output beyond the empty schema.

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 verb 'Get' and the resource 'DePIN marketplace match fee', with a specific value and additional return context. It is distinct from sibling tools like depin_create_listing or hive_earn_register.

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 guidance on when to use this tool versus alternatives. There is no mention of prerequisites, context, or exclusions. The description only states what the tool does, not when it should be used.

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 provided, so description carries the burden. It states 'No auth required' (positive), but does not disclose other behaviors like read-only nature, pagination, or rate limits. The 'list' verb implies a read operation, but more detail would be beneficial.

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, front-loaded with purpose. However, the inclusion of 'capacity' is a distraction and reduces conciseness by introducing incorrect information.

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 simple list tool with optional params and no output schema, the description covers purpose, filters, and auth. However, it omits response format or default behavior (e.g., returns all providers if no filters). It is adequate but not comprehensive.

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 baseline is 3, but the description introduces 'capacity' as a filter, which is not a parameter in the schema. This misalignment can mislead the agent. The description adds minimal value beyond the schema due to the inaccuracy.

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 'List DePIN provider listings', identifies the resource, and distinguishes it from sibling tools (none of which are list operations). The filtering options are also mentioned.

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 guidance on when to use this tool vs alternatives, but since there is no other list tool, usage is implied. However, it lacks context such as prerequisites or when not to use.

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?

The description discloses that it makes a GET call and gracefully returns 'rails not yet live' on upstream failure. With no annotations, it covers the main behavioral traits, though additional details like rate limiting are omitted.

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 with key information front-loaded: purpose, then URL and error handling. No redundant words.

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 simple tool with one parameter and no output schema, the description covers purpose, mechanism, and error state. It could mention return shape but is adequate.

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 parameter is already well-documented. The description only references the parameter in the URL without adding new semantics, meeting the baseline.

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 that the tool returns top earning agents by attribution payout in USDC, distinguishing it from sibling tools like hive_earn_me (self) and hive_earn_register (registration). The verb 'top earning agents' and resource 'leaderboard' are specific.

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 implicitly indicates use for viewing top earners but lacks explicit when-not or alternative guidance. However, the context is clear enough for an agent to infer usage versus other hive_earn tools.

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?

Discloses the exact GET endpoint, uses real data, and handles the undeplyed upstream case gracefully. No annotation provided, so description carries full burden and does well.

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 sentences with no fluff. Front-loads the main purpose and includes key behavioral details 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?

For a simple 1-param tool with no output schema, the description covers return fields and exceptional behavior. Could be slightly more complete about error handling but generally sufficient.

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?

With 100% schema coverage, the description adds 'caller agent's' context but essentially restates the schema. Baseline score 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 looks up the caller agent's earn profile with specific fields (lifetime + pending USDC balance, last payout tx hash, next-payout ETA), distinguishes from siblings like hive_earn_leaderboard and hive_earn_register.

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 implied for checking one's own earn profile, but no explicit when-to-use or when-not-to-use guidance or alternatives among siblings.

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 burden. It discloses that the tool makes a POST request on behalf of the caller and handles upstream cold-start with a structured error response. This adequately informs the agent of the tool's behavior and 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?

The description is four sentences long, front-loaded with the core purpose, and every sentence adds unique value (purpose, settlement details, API endpoint, error resilience). No unnecessary information.

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 registration tool with 3 simple parameters and no output schema, the description covers purpose, usage context, endpoint, and error handling. It does not specify the success response format, but this is a minor gap that does not significantly impair completeness.

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 100% description coverage for all three parameters. The description does not add semantic information beyond what the schema provides, so a baseline 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 tool's purpose: registering an agent for the Hive Civilization attribution payout program. It specifies the verb 'register' and the resource 'agent for the payout program', and differentiates from siblings like hive_earn_leaderboard and hive_earn_me.

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 for when to use the tool (to register for the attribution payout program) and mentions that it calls a specific API endpoint on behalf of the caller. It does not explicitly state when not to use it or list alternatives among siblings, but the context is sufficient for an agent to decide.

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