apix402

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

With no annotations, the description carries the behavioral transparency burden. It discloses the payment mechanism (x402 over HTTP), the lack of API key/account requirements, and that a wallet serves as identity. It does not explicitly state that the tool is read-only, but the verb 'List' strongly implies 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 sentences with no filler. The first sentence front-loads the core function and output fields; the second adds essential payment/auth context. Every word earns 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?

For a zero-parameter catalog tool with no output schema, the description is complete: it lists what the tool returns (route, price, question, preview), how to use it (start here), and the payment/auth model. No critical context 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 tool has zero parameters, and the schema coverage is 100% trivially. The baseline for zero-parameter tools is 4, and the description reinforces that no filters are needed by stating it lists every check.

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 lists all apix402 checks available for purchase, including route, price, question, and free preview. The verb 'List' and specific resource make the purpose unambiguous, distinguishing it from the sibling sample-check tools.

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 'Start here' explicitly instructs users to invoke this tool first when browsing available checks. It does not name alternatives, but the context of sibling tools being individual checks implies this is the discovery entry point.

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 burden. It discloses that the tool is a 'live sample' with a fixed DAO set, requires no arguments, and returns a count of disagreements. It also notes what is not included (which DAO disagrees and how) referring to the paid endpoint, giving a clear behavioral scope.

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, each providing distinct value: identifying it as a live sample, describing the data and scope, and clarifying the free vs paid distinction. No redundant content, though slightly denser than the minimal two-sentence example.

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 no output schema and no annotations, the description adequately covers what the tool returns (count of disagreements), its scope (fixed DAOs), and how to obtain deeper details (paid endpoint). It leaves out interpretation of the count but is otherwise complete for a zero-parameter sample 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 has 0 parameters, so the baseline is 4. The description reinforces 'no arguments', aligning with the empty input schema, though it doesn't add further parameter-level detail since none exist.

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 is a live sample that shows DAO governance proposals closest to their deadline with a count of disagreements between off-chain and on-chain data. It uses specific verbs and resources, and its focus on DAO governance distinguishes it from sibling samples like 'oracle_staleness_sample' or 'lending_depeg_sample'.

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 gives context on when to use the tool: it's a free sample with a fixed set of tracked DAOs and no arguments. It also references the paid GET /dao-proposals endpoint as an alternative for more detailed mapping, providing a clear usage boundary, though it doesn't explicitly compare to sibling sample 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?

No annotations are provided, so the description carries the burden. It discloses the sample nature and the specific position, but doesn't explicitly state whether it is read-only, if it makes network calls, or what output format to expect.

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 'Live sample', and the second sentence adds valuable context about the paid endpoint. No waste, every sentence earns 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?

For a zero-parameter sample tool, the description covers the purpose, the specific data shown, and the paid alternative. It lacks explicit mention of response structure, but the sample nature is clear and no output schema exists.

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 description adds context about the fixed position rather than parameter syntax. A baseline of 4 is appropriate since no parameter documentation is needed.

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 identifies this as a live sample for a specific Aave V3 position, showing stETH depeg exposure and wstETH collateral. It distinguishes itself from sibling sample tools by naming the specific lending depeg product.

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 the sample is for a fixed position and mentions the paid endpoint for any borrower, giving a clear alternative. However, it doesn't explicitly state when to use the sample versus the paid tool.

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 of behavioral disclosure. It clearly states that this is a 'live sample' returning 'Boolean verdicts only', which informs the agent that it will get immediate true/false responses without additional details. It also points to the paid endpoint for richer data. While it does not explicitly say it is read-only, the nature of a 'sample' implies a safe, non-mutating 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 a single sentence with a semicolon and a dash, efficiently conveying the key points without redundant wording. It front-loads 'Live sample' and immediately explains the output. The structure is slightly dense but remains clear and acceptable for its length.

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 tool with no parameters and no output schema, the description is quite complete. It explains the tool's purpose, return type ('Boolean verdicts only'), and explicitly lists what is not included, while referencing the paid endpoint for those missing details. This covers the essential context an agent would need to decide whether to use this 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 tool has 0 parameters, so the baseline is 4. The description adds extra meaning by explaining that the price feed set is 'fixed', which justifies why no parameters are available. This goes beyond the empty schema and clarifies the tool's behavior for the agent.

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 ('sample') and clearly defines the scope: checking a fixed set of price feeds for rejection by a guard based on measured cadence. It distinguishes itself from sibling sample tools by explicitly stating 'Boolean verdicts only' and referencing the paid GET for additional details, making its unique 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 implies that this is a lightweight, free sample for quick boolean checks and that the paid GET /oracle-staleness should be used when ages, thresholds, spread, or revert selector are needed. However, it does not explicitly name alternative tools or provide a clear 'use this when' statement, leaving the usage context somewhat implied rather than directly 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?

With no annotations, the description carries the full burden. It discloses key behavior: recursive expansion, the module-governance nuance (1-of-1 appearing but actually 2-of-8 via module), and that it is a live sample. It does not explicitly state read-only status, but the 'sample' context implies safety, and the added nuance provides value beyond what annotations would.

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 purpose, and includes a valuable comparison to the paid alternative. Every clause serves a purpose; no redundancy or filler.

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 sample tool with no output schema, the description is remarkably complete. It covers the fixed scope, recursive expansion, a critical nuance, and even points to the paid tool for expanded needs. No significant gaps remain.

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 description need not explain any. The baseline for 0 params is 4, and the description adds no unnecessary parameter details, allowing the score to stand.

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: to show who can actually move funds from a fixed Gnosis Safe, including owners, threshold, and modules expanded recursively. This distinguishes it from sibling tools by focusing on Safe governance and from the paid tool by framing it as a sample.

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 usage context by contrasting with the paid GET /safe-signer-drift: this sample covers one fixed Safe, while the paid tool accepts any Safe and adds change details. It does not explicitly compare to sibling sample tools, but their different domains make this omission acceptable.

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 burden of behavioral disclosure. It reveals the tool performs a live read directly from the contract, implying current data and possible chain interaction, and notes the limitation of being fixed to one plan. However, it does not describe the response format, potential errors, or whether any side effects occur, so transparency is partial.

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, highly concise, and front-loaded with the key concept 'Live sample.' The second sentence contrasts with the paid alternative, adding value without redundancy. Every sentence earns its place; no wasted 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?

Given the tool's simplicity (no parameters, no output schema, no annotations), the description is largely complete: it explains the source (contract read), the scope (one fixed plan), and the alternative (paid endpoint). The only missing part is the exact structure of the returned state, but for a sample tool this is a minor gap, so a 4 is appropriate.

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 is empty, so there are no parameters. The description says 'one fixed vesting plan,' clarifying that no parameters are needed because the plan is predetermined. This adds meaning beyond the schema by explaining why there are zero parameters, justifying the baseline 4 for a parameterless tool.

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 provides a live sample of the current state of one fixed vesting plan read from the contract. This defines a specific resource and action ('read state of a fixed vesting plan'), and it distinguishes itself from the paid GET /vesting-status that accepts any plan or stream. However, it does not explicitly differentiate from sibling sample tools, though the 'vesting' naming helps.

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 implies usage by contrasting with the paid endpoint: use this free sample for one fixed plan, use the paid GET for arbitrary Hedgey plans or Sablier streams. This gives clear context and an explicit alternative, though it does not discuss when to choose among sibling sample tools.

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