FlexYield — blockchain RPC gateway

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

With no annotations provided, the description carries the behavioral disclosure burden. It openly states the operation is read-only, that plan modifications are not performed here, and that the card number is never returned. It does not describe error conditions or authentication requirements, but for a zero-parameter read-only status tool this is strong disclosure.

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 dense sentence that front-loads the core purpose and then itemizes the relevant fields without waste. Every clause adds useful information, and it avoids repeating the tool name or schema details.

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 there is no output schema and no annotations, the description provides a thorough inventory of what the tool returns and clarifies its read-only scope. It is sufficiently complete for an agent to invoke the tool correctly, though it could mention response format quirks or error behavior for full 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 tool has no parameters, so the empty input schema fully defines the interface. The description adds value by explaining what the returned state represents, but no parameter-level guidance is needed. Baseline 4 is appropriate for a zero-parameter 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 that the tool returns the billing state of the authenticated account and enumerates the specific data included, such as tier, subscription, card on file, and pricing reservation. It lacks an explicit verb like 'get' or 'retrieve', but the meaning is unambiguous and it distinguishes itself from mutation-oriented billing 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 description makes the read-only nature explicit and notes that plan changes happen in the web console, which tells the agent when not to use this tool. It does not name sibling tools like buy_pack or list_plans as alternatives, but the context is clear enough for selecting this tool for billing status queries.

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 does disclose the success outcome: the key becomes persistent with a 1M units/month public supply. However, it does not mention failure modes, reversibility, or what happens if the wallet already has a bound key.

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-loads the purpose, and includes only necessary details: the step context, the required input, and the success behavior. 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?

For a simple two-parameter tool, the description provides enough context to invoke it correctly: it names the prerequisite step, what to pass, and the success result. The lack of output schema or return-value description is a minor gap given the tool's simplicity.

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%, so the baseline is 3. The description mostly restates what the schema already documents for the signature parameter and adds no new semantics for the address 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?

The description clearly identifies the action (bind) and resource (the capability key used for the call), and explicitly frames this as step 2 of a two-step process. It also references bind_key_start, which distinguishes it from the sibling first-step tool.

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 for when to use the tool: after bind_key_start, with the signature of the message from that step. It does not explicitly state exclusions or alternatives, but the sequential dependency is unambiguous.

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 disclosure burden. It adds meaningful behavioral context: the call returns a SIWE message, bound keys retain identity across sessions, and they receive 1M units/month. It stops short of explicitly stating that this step does not itself mutate the binding or that signing is required next, but 'step 1' and 'returns the exact SIWE message to sign' convey the essential flow.

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 no waste. It front-loads the purpose, then gives the key output and the lasting consequences of binding. Every clause adds useful information for an agent deciding whether and how to invoke this 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?

Given the simple single-parameter schema, no output schema, and no annotations, the description is nearly complete. It explains the purpose, the output, and the consequences. A small gap is that it does not explicitly point to bind_key as the next step, but the 'step 1' language and sibling tool list make that inference straightforward.

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% and the address parameter is already documented as 'The wallet's 0x address (your identity)'. The description does not add further parameter-level detail, but the baseline of 3 applies because the schema handles the parameter meaning sufficiently.

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 action (bind the capability key to a wallet), identifies this as step 1, and states the concrete output: the exact SIWE message to sign. It clearly differentiates from the sibling bind_key tool, which is presumably the later signing/completion step.

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 'step 1' and the stated output indicate this tool should be used first to obtain a message to sign before completing the binding process. It does not explicitly name bind_key as the next step or state when not to use it, but the step/flow context is clear enough for an agent to select it appropriately.

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, and it is unusually rich: a checkout URL is returned, units become available when payment lands, consumption happens after the monthly quota, packs are valid 12 months, and there is a +5% bonus. It also clarifies the purchaser must be the account owner completing on card. This fully discloses the tool's side effects and timing.

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 pack all essential information with no filler; purchase options are front-loaded, followed by the flow, timing, and valid duration. 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 one-parameter, no-output-schema tool, the description covers what the call returns, who can complete it, when units activate, how they are consumed, and validity. Nothing essential is missing for an agent to select and invoke 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?

The schema only says size is s, m, or l; the description adds exact units, prices, and the +5% bonus, making the choice meaningful. Since schema coverage is 100% and only one parameter exists, the description has already done the needed semantic enhancement.

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 starts with a specific verb-resource pair: 'Start the purchase of a prepaid unit pack,' and immediately enumerates the three pack sizes with units and prices. It also distinguishes itself from billing_status by pointing balance reads to that sibling, so an agent can tell which tool handles purchasing vs. reading balances.

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 states clear context for use: buying prepaid units, and gives the alternative for balance reads via 'Read balances with billing_status.' It doesn't explicitly describe when not to use buy_pack beyond the balance-read case, but the purchase context is unambiguous.

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 burden. It discloses that the tool verifies a signature, equips the agent with a key, applies a default budget, and—critically—returns the key exactly once. This is meaningful non-obvious behavior. It does not mention error cases or idempotency beyond 'exactly once,' but the key disclosure is strong.

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 entire description is one efficient, front-loaded sentence. Every clause earns its place: the action, the prerequisite, the default budget, and the one-time return behavior. No filler 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 3-parameter tool with no output schema and no annotations, this description covers purpose, workflow position, signature requirements, default budget, and return behavior. It does not describe error handling or the exact response shape, but the core information an agent needs to invoke it correctly is present.

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 a baseline of 3 applies, and the description adds value beyond the schema: it explains that the signature must be 65-byte and over the exact message from claim_agent_start, and that the default budget is 50000 requests/month. This enriches the address, signature, and monthly_request_cap parameters.

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 ('Complete'), a concrete resource ('an agent claim'), and describes the two core actions: verifying the wallet signature and equipping the agent with a budgeted API key. It also references claim_agent_start, which clearly distinguishes this from the complementary start-step tool and from generic key-creation 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 description clearly situates this tool after claim_agent_start by referencing 'the message from claim_agent_start' and requiring the resulting signature. It does not explicitly name sibling alternatives or state when not to use it, but the prerequisite and workflow context are strong enough for an agent to select it correctly.

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 of behavioral disclosure. It usefully explains that the tool returns the exact SIWE message the wallet must sign, but it does not disclose whether starting a claim has side effects, creates pending state, or has expiration/prerequisite constraints. This is a meaningful but not severe gap.

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, well-structured sentence that front-loads the action and return value, then adds the essential completion pointer. There is no repeated information 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 simple two-parameter tool with no output schema, the description covers the key operational details: what to provide, what is returned, and what to do next. It is slightly incomplete regarding side effects and preconditions, but the core workflow is understandable without further lookup.

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%, so the schema already explains both parameters. The description adds only the framing that the address is the agent's wallet identity and that the claim targets an existing agent, which adds little beyond what the parameter descriptions already state.

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 ('Start claiming'), a specific resource ('existing agent'), and the exact return value (the SIWE message). It also names the companion tool claim_agent_complete, so an agent can distinguish this from the completion step without opening schemas.

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 this is the first step of a two-step flow and explicitly points to claim_agent_complete as the required follow-up. It does not state explicit exclusions or alternative conditions, but the workflow guidance is clear enough for correct 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?

No annotations are provided, so the description carries the full burden. It clearly discloses the most important behavioral trait: the plaintext token is returned exactly once and cannot be retrieved again, with a storage warning. It does not cover auth scope or side effects beyond creation, but the one-time disclosure is high-value.

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 no filler. The core action is first, and the critical security caveat is second; every clause 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 two-parameter creation tool with no output schema and no annotations, the description covers the essential non-obvious fact (one-time token) and leaves parameter details to the schema. It could add explicit notes on permissions or key limits, but nothing an agent needs to invoke correctly 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?

Schema description coverage is 100%, so the baseline is 3. The description adds no parameter-level detail, but the schema already documents name and monthly_request_cap with examples and semantics.

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 action ('Create') and resource ('FlexYield API key') and adds the defining one-time-return behavior, which separates it from retrieval tools like get_key and revocation tools like revoke_api_key. No ambiguity about what the tool accomplishes.

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 does not explicitly name sibling alternatives or state when to choose this over get_key, revoke_api_key, or set_key_budget. The use case is implied by 'Create a new,' but there are no exclusions or prerequisites, so an agent gets only implicit routing.

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, and it does well: it discloses the 'add to open one with same symptom' behavior, the automatic call attachment, and the return payload (ticket reference, status, suggested path). It leaves out potential side effects or authorization requirements, but the disclosed behavior is substantive.

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. It front-loads the core action, then adds behavior and return-value details in a compact way. Every phrase contributes to choosing and invoking the tool correctly.

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 annotations and no output schema, the description is unusually complete: it covers the triggering condition, the deduplication behavior, the key parameter integration, and the return shape. Nothing critical is missing for an agent to call this tool 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 description coverage is 100%, so the baseline is 3, but the description adds meaningful cross-parameter guidance: quoting the request_id connects the error body to the exact call and the suggested fix. It also clarifies that request_ids inside the message body are picked up automatically, which the schema alone does not state.

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 opens with a specific verb—'Open a support ticket for this account'—and clearly distinguishes this from sibling tools like get_ticket, list_tickets, and reply_ticket. The added detail about attaching the request_id and the behavior of adding to an existing open ticket makes the 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 clear context for when to use the tool: after a failed call, quote the request_id from the error body. It also explains the deduplication behavior with the same symptom. It does not explicitly name alternative tools like explain_error, but the condition for use is clear enough that an agent can decide correctly.

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 behavioral disclosure burden. It adds meaningful detail: static types are decoded, dynamic types are shown raw and labeled, and decoding depends on a Sourcify-verified ABI. It does not cover failure modes such as missing ABI verification or invalid calldata, but it conveys core behavior honestly.

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 efficient sentence with no filler. It front-loads the action and resource, then specifies output details and type-handling behavior. Every clause contributes useful 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?

The tool is relatively simple and all three parameters are fully documented, and the description does enumerate output components. However, with no output schema and no annotations, the description does not specify the exact return structure or error behavior when the ABI is not verified or calldata is invalid.

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 parameters are already documented with descriptions for chain, address, and data. The description reinforces that 'data' is calldata and clarifies output behavior, but it does not add meaningful parameter-level semantics beyond what the schema provides.

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 and resource: decode transaction calldata against a verified Sourcify ABI, with specific outputs listed (signature, selector, argument values). It is distinct from siblings like get_abi or verify_signature, though it does not explicitly name or contrast 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?

The description offers no explicit guidance on when to use this tool versus alternatives, and no exclusions or preconditions beyond the implicit requirement of a Sourcify-verified ABI. It does not mention related tools like get_abi or explain_error that an agent might consider 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, the description carries the full behavioral disclosure burden. It usefully states that no authentication is required, that replies come by email from the founders, and that the wishlist has a 1000-character limit. This goes well beyond a bare 'submit' 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 a single tightly packed sentence with no filler. The core action is front-loaded, followed by content guidance, delivery expectation, and authentication status. Every clause 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 simple two-parameter submission tool with no output schema and no nested objects, the description covers the purpose, required content, length limit, contact flow, and auth requirement. An agent has enough information to invoke the tool 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 documents both parameters with 100% coverage, so the baseline is 3. The description adds meaningful semantic detail by enumerating example wishlist categories and the max character count, giving the agent a clearer sense of what to put in 'items'.

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 ('Send FlexYield an enterprise wishlist') and specifies the content of the wishlist (chains, SLAs, compliance, features, prices) plus a contact email. It is distinct in purpose from most siblings, though it does not explicitly name alternatives like join_waitlist.

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 explains what to include and that the founders reply by email, but it does not state when to use this tool versus join_waitlist, submit_feedback, or create_ticket. There are no explicit exclusions or alternative routing cues.

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 must carry the safety/behavior burden. It discloses what each mode returns (EIP-55 checksum + validity, 4-byte selector + topic0, keccak256 hash) and implies a pure, side-effect-free utility. It stops short of detailing exact response shapes or invalid-input handling, but no annotation contradictions exist.

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?

One dense sentence with a colon-led list; every clause corresponds to a distinct operation and no filler. The structure front-loads the tool's domain and lets an agent quickly scan the supported modes.

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 four-mode utility with no output schema, the description covers each mode's input and output at a useful level. The main gap is that `to`/`from` are schema-optional but description implies both are required for convert; a short example or explicit requiredness note would remove ambiguity.

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?

Although schema descriptions cover all four parameters, they are generic ('address / value / signature / text'). The description adds op-specific meaning by mapping checksum to addresses, convert to value+from+to units, selector to function signatures, and keccak to text, which is exactly what an agent needs to populate parameters correctly.

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 the resource ('EVM developer utilities') and breaks it into four concrete operations with explicit input/output semantics: checksum, convert, selector, keccak. This level of specificity separates it from sibling EVM tools like decode_calldata and verify_signature, which address different concerns.

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?

Each operation includes its intended input ('input=address', 'input=function signature'), making selection within the tool explicit. It doesn't explicitly rule out alternatives, but the operation-level context is clear enough for an agent to pick the right mode.

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 behavioral disclosure burden. It usefully reveals that no authentication is required and that the result includes meaning and steps, but it does not explicitly state whether the operation is read-only or describe the response format. For a simple informational tool this is adequate but not rich.

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 front-loaded sentence with no filler, and the most important information appears first. The only structural concern is the unexplained 'doorway' term, which introduces a small amount of ambiguity.

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 single-parameter, stateless explainer with no output schema, the description covers the trigger, the type of output, and the auth requirement. The main gap is that 'doorway' is not defined, leaving one promised output element unclear.

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 already fully documents the single integer parameter with an example (-32007), and the description repeats the same example without adding new constraints or syntax details. Since schema description coverage is 100%, 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 names a specific verb (Explain), a specific resource (FlexYield error code), and previews the output content (meaning, steps, doorway). It is distinct from the sibling tools, though the cryptic 'doorway' phrase slightly diminishes the clarity.

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 intended use is clearly implied: when a user encounters a FlexYield JSON-RPC error code and wants an explanation and next steps. The statement 'No authentication required' provides a practical precondition, though it does not explicitly name when-not-to-use alternatives.

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 and does well: it discloses the data source, the supported chains, and the unverified-contract behavior (verified:false plus a remediation path). It does not cover invalid inputs or rate limits, but for a simple read tool this is adequate.

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, front-loaded with the core purpose, followed by the supported chains and the unverified behavior. Every sentence adds useful information with no filler or repetition.

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 two-parameter read tool with no output schema and no annotations, the description covers the essential contract: what is returned, where it comes from, which chains are valid, and the failure mode. An agent has enough information to select and invoke 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?

The schema already documents both parameters at 100% coverage. The description adds value by enumerating the exact supported chain slugs, which the schema does not constrain with enums, giving the agent concrete valid values.

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 and resource: retrieving the verified ABI for a contract from Sourcify, and adds extra payload context (name, match level). This clearly distinguishes it from sibling tools like decode_calldata or get_balances, which target different data.

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 intended use is implied by the purpose and the supported chain list, but the description does not explicitly say when to use this tool versus alternatives, nor does it mention any exclusions or prerequisites. It provides context but no direct routing 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?

There are no annotations, so the description carries the behavioral burden. It does disclose a useful caveat: ERC-20 balances are only returned on chains with a data-capable upstream, and it gives concrete chain examples. It does not mention response shape, pagination, or explicit read-only behavior.

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 no filler. The first states the core behavior and scope, while the second gives concrete chain examples. 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?

The description is sufficient for selecting and invoking the tool with two required parameters, and the caveat about ERC-20 support is useful. However, since there is no output schema, the description does not reveal the return shape or how unsupported chains are represented in the result.

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%, so the baseline is 3. The description adds meaningful value by providing several valid chain slugs and conveying that all supported chains are accepted, which is especially useful since chain has no enum in the 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 identifies the resource: native and ERC-20 token balances for an address, so an agent can infer this is about balances rather than prices or history. It does not explicitly name or contrast sibling tools, so it misses the strongest form of differentiation.

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: an agent needing address balances should call this tool. However, the description does not explicitly say when not to use it or point to alternatives like get_token_prices, get_history, or get_gas_prices.

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 must carry behavioral disclosure. It reveals the calculation source (FlexYield multi-provider pool), the recency window (last 20 blocks), the output granularity (slow/standard/fast with max and priority fees in wei/gwei), and the supported chain type. It does not discuss errors or endpoint access limits, but it is much richer than a minimal description.

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 purposeful sentences front-load the output type and units, then give computation source and valid-chain guidance. There is no filler or repetition.

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 one-parameter read-only tool with no output schema, the description covers the main return values (fee tiers, fee components, units), data source, and supported chains. It stops short of describing error conditions or exact response keys, but the tool is simple enough that this is a minor gap.

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 already documents the single chain parameter at 100% coverage, so the baseline is 3. The description adds several concrete valid chain slugs and the EVM-only requirement, giving an agent more useful examples than the schema's single example.

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 and resource: it provides EIP-1559 gas recommendations with fee levels and units. It is clearly distinct from sibling get_token_prices, and the 'EVM chains only' constraint plus examples define the exact scope.

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 for when the tool applies: gas fee recommendations computed over the last 20 blocks, on EVM chains, with valid chain examples. It does not explicitly name alternatives among siblings, but the resource and chain restriction make the intended use unambiguous.

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 reveals that results include both sent and received transfers, are sorted newest-first, and are restricted to EVM chains with a data-capable upstream. It does not mention pagination or result limits, but the disclosed behaviors are meaningful and accurate.

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 concise and front-loaded: it states the core function and sorting order in the first sentence, then adds the EVM restriction in the second. Every word earns its place, with no filler or repetition.

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 only two well-documented parameters and no output schema, the description covers the essential invocation details: what is returned, for whom, and on which chains. The term 'data-capable upstream' is slightly vague, and result pagination or recency bounds are unspecified, but an agent can confidently call the tool with the given inputs.

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%, and both parameters (chain and address) already have clear descriptions with examples. The tool description adds little beyond restating that this is for an address on certain chains, so it does not need to compensate for missing schema documentation.

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 the tool's purpose: retrieving recent asset transfers (sent and received) for an address, with explicit ordering (newest first) and chain scope (EVM only). It is distinctly different from sibling tools like get_balances or get_tx_status, so an agent can tell them 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 gives clear context: use this for transfer history on EVM chains, and it notes the limitation to data-capable upstreams. It does not explicitly name alternative tools or provide when-not-to-use guidance, but the constraints are enough to route the agent correctly in most cases.

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 behavioral burden and meets it: it discloses the one-time-only display of the key ('shown once'), the rate limits, the 'every tool' scope, and the absence of authentication. The 'shown once' caveat is exactly the kind of critical behavioral trait that prevents an agent from assuming the key can be re-fetched later.

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 the purpose and constraints front-loaded in the first sentence and return details in the second; there is no fluff. The 'fences as doorways' / 'other doors' metaphor is evocative but somewhat cryptic, costing a point against an otherwise tight definition.

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 with no annotations and no output schema, the description is remarkably complete: it covers authentication requirements, rate limits, operational scope, what is returned, and the critical one-time key display. Nothing an agent needs to decide whether to call it and what to expect 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, so the baseline is 4 and there is nothing for the description to clarify about arguments. The description instead explains the response contents (key, fences/doorways, upgrade paths, terms digest), which adds value given there is no output 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 opens with a specific verb+resource phrase, 'Get a FlexYield capability key with no signup,' establishing both the action and the key qualifier that separates this tool from create_api_key and bind_key. The 'public supply' wording further distinguishes it as the no-authentication entry point among the key-management siblings.

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 conveys clear usage context: it is the no-signup, public route for obtaining a key, with explicit limits (10,000 weighted units/UTC day, 5 requests/s, every tool). It references the alternative paths—wallet-signature binding for 1M units/month and a claim code for the paid plan—but does not name the sibling tools explicitly or state a when-not-to-use rule, 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 the behavioral disclosure burden. It reveals the default-period behavior, that an agent's own key returns only its own usage, and that periods follow the subscription cycle or calendar months. It does not mention rate limits or errors, but the key scoping and period behavior are meaningful.

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 dense sentences with no filler. The core purpose and default behavior are front-loaded, followed by useful grouping and scoping details.

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?

Despite no output schema or annotations, the description explains what the statement contains, how usage is grouped, what the default period is, how periods are defined, and the agent-key scoping rule. The schema's reference to list_statements covers how to discover period keys, so the tool is sufficiently complete for correct invocation.

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% and the period parameter is documented in the schema. The description adds value beyond the schema by stating that the default is the current period and that periods align with the subscription cycle or calendar months.

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 and resource: retrieving this account's statement for a billing period. It also enumerates the contents (invoice facts plus usage grouped by API key/agent, chain, method class), which clearly distinguishes it from sibling tools like list_statements or usage_report.

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: it defaults to the current period, explains period semantics, and notes agent-key scoping. It does not explicitly name alternatives or when-not conditions, but the statement-focused wording makes the intended use clear.

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 of explaining behavior. It does reveal the response contents (thread, evidence, playbooks) and the account scope, but it does not explicitly confirm the operation is read-only, describe error handling for invalid references, or mention any access requirements.

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 concise sentence that front-loads the core purpose and immediately lists what the returned ticket includes. Every word contributes 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?

For a simple single-parameter retrieval tool, the description adequately covers the return contents and scope. The lack of an output schema is partly compensated by listing thread, evidence, and playbooks. Minor gaps like existence/error behavior are not critical for this low-complexity 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?

Schema coverage is 100%, and the parameter description already provides the format example 'FY-1024'. The tool description adds no new semantic detail beyond 'one ticket of this account', 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 returns one ticket of the account in full, enumerating its contents: thread, evidence, and suggested playbooks. The verb is implicit ('get' in the name) but the resource and scope are specific, and it is distinguishable from sibling list_tickets by emphasizing a single full ticket.

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 'One ticket of this account' clearly indicates this is for retrieving a single ticket's full details, implying contrast with list_tickets. However, it does not explicitly name alternatives or state when not to use the tool, so it falls 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 the behavioral burden. It discloses the on-chain data source, the absence of a third-party API, and that each price includes updated_at and a stale flag. This adds meaningful context beyond the schema, though it stops short of describing exact response shape or failure modes.

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. It front-loads the core purpose and source before providing supported symbols and output field details, making it easy for an agent to parse quickly.

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 single-parameter price lookup with no annotations and no output schema, the description covers the source, supported symbols, and key output attributes (updated_at, stale flag). It does not specify the full response structure or error handling, but it provides enough context for an agent to invoke the tool 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 schema already documents the symbols parameter as comma-separated with an example, so the baseline is 3. The description adds value by enumerating supported symbols (eth, btc, link) and indicating that more pairs are available on request, helping the agent construct valid input. It does not cover case sensitivity or invalid-symbol behavior, but coverage is strong overall.

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'), resource ('token prices'), and a distinctive source ('Chainlink aggregator feeds through FlexYield's pool, no third-party price API'). It also lists supported symbols, making the tool's scope concrete and distinguishable from siblings like get_gas_prices.

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 intended use is implied: call this when USD token prices are needed. It provides supported symbols and notes that more pairs are available on request, but it does not explicitly contrast with alternatives such as get_gas_prices or state when not to use this 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?

No annotations provided, so description carries the burden. It fully describes the read operation and its outputs, with no mention of side effects, which is appropriate for a status check.

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 concise sentences convey all necessary information without 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?

Covers the core functionality and output details; though output schema is absent, the description gives enough context for expected results. It doesn't address error cases, but that's not critical for a simple query.

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 already documents both parameters; description adds clarity by providing examples of chain slugs and explaining how output varies by chain type.

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 tool retrieves transaction status, enumerates possible statuses, and specifies additional details returned (confirmations/gas for EVM, slot/commitment for Solana), with concrete chain slug examples.

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?

Description explains what the tool does but doesn't explicitly state when to use it vs. alternatives or any prerequisites. It's self-explanatory for a simple query, but lacks explicit 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 provided, the description carries the behavioral transparency burden. It does disclose a meaningful behavioral fact: 'No authentication required', which is helpful. It also implies the action is a non-destructive waitlist signup, not a purchase or key-binding. However, it does not state what the response returns, whether duplicate signups are handled, whether confirmation emails are sent, or whether the operation is idempotent.

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 succinct sentences with no fluff. The core action is front-loaded, the qualifier constraint is embedded, and the auth requirement is stated at the end. Every clause 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 simple 4-parameter, 2-required waitlist join tool with no output schema and no nested objects, the description covers the essential purpose and the one critical caveat (no auth). The only missing information is the behavioral outcome (e.g., confirmation/duplicate handling), but the schema fully documents all parameters, so completeness is adequate for an agent to invoke 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 description coverage is 100%, so baseline is 3. The description adds the allowed qualifier values ('developer, investor, curious') inline, reinforcing the schema's enum-like description. It also clarifies that authentication is not required, which indirectly explains the absence of auth-related parameters. It adds no meaning beyond this.

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 ('Join') and clearly identifies the resource ('FlexYield early-access waitlist'). It also calls out the required qualifier values and the fact that no authentication is needed, making it easy to distinguish from the many sibling tools that handle billing, keys, tickets, usage, and other concerns.

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 on when this tool is used (joining the early-access waitlist) and states the allowed qualifier values explicitly, which helps an agent decide whether this is the appropriate tool. It does not explicitly name alternatives or say 'use X instead', but the uniqueness of the waitlist purpose among 40+ siblings makes that unnecessary. Slight gap: it does not mention preference-related conditions (e.g., product_updates handling) relative to other 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?

With no annotations, the description carries the behavioral burden. It goes beyond a bare verb by detailing exactly what is returned and noting that the switched-off services are changed by set_key_services, giving useful dependency context. It doesn't explicitly say 'read-only', but the word 'List' strongly implies a 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?

A single dense sentence front-loads the action, then lists the returned fields, and closes with a helpful cross-reference to set_key_services. There is no filler 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 parameterless read-only listing tool with no output schema, the description is largely complete: it names the resource, its account scope, the returned fields, and the related mutating tool. Explicit confirmation of non-mutation or return format would be nice, but 'List' makes the behavior clear enough.

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%, matching the baseline of 4. The description appropriately focuses on response contents rather than parameter syntax, which is unnecessary 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 states a specific action ('List') and resource ('the account's claimed agents') and enumerates the returned attributes: name, address, proof, key id/prefix, budget, and services switched off. This makes it clearly distinct from sibling tools such as list_plans or get_key, even without naming 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?

The context is clear: this tool is for retrieving the account's claimed agents and their key details. It does not explicitly contrast with alternatives like get_key or specify when not to use it, but for a straightforward list operation the intended situation is evident.

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 must carry the behavioral disclosure burden. 'List' implies a read-only operation and the description indicates what is returned, but it does not mention filtering defaults, pagination, ordering, or the absence of side effects. This is adequate but minimal for a read-only list 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 a single, front-loaded sentence with no filler. It efficiently communicates the account scope, the resource, and the output fields.

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 one-parameter list tool, the description covers the essential return concept ('feedback items with status and our reply') and the schema covers the status filter. Some detail is missing, such as default behavior and potential output shape, but the low complexity makes the description 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?

The schema fully documents the single optional 'status' parameter, including allowed values and the default of 'all'. The description does not add new parameter details, but none are needed since schema coverage is 100%.

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 concrete resource ('feedback items') and scope ('This account's'), and mentions what is included ('status and our reply'). This is not a tautology and distinguishes it from other list_* tools like list_tickets, though it does not explicitly name an alternative.

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 is given for when to use this tool versus related tools such as submit_feedback, reply_ticket, or list_tickets. There is no when-not-to-use condition or alternative-selection hint beyond the implied account scope.

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 behavioral disclosure burden. It does this well by specifying that no authentication is required and by detailing the returned data shape and units. While it does not discuss pagination or edge cases like an empty plan list, those are minor for a simple public listing 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 entire description is one efficient sentence with the verb and resource front-loaded, followed by a compact enumeration of return attributes. It contains no filler, repetition, or irrelevant context, and every clause adds useful information for invoking and interpreting 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?

For a zero-parameter, no-output-schema, no-annotation tool, this description is complete: it identifies the resource, the public scope, the exact return fields, the units, and the authentication requirement. An agent has all the information needed to decide to call it and to interpret its result 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 tool has zero parameters, and the schema confirms no required or optional properties. According to the calibration baseline for zero-parameter tools, the description needs no additional parameter explanation. The description's focus on return fields is appropriate given there is nothing to document 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 uses a specific verb ('List') with a clear resource ('FlexYield's public subscription plans'), making it immediately obvious what the tool does. It further enumerates the exact fields returned, including prices in integer USD cents, billing interval, quota, and burst limits, which strongly distinguishes it from other list_* siblings. No ambiguity remains about the tool's 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 makes clear this is a public, read-only listing operation requiring no authentication, which provides solid context for when an agent should invoke it. It does not explicitly name alternative tools or state when not to use it, but for a parameterless public plan-listing tool the use case is clear and there are no obvious competing 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 provided, the description must carry the behavioral disclosure burden. It does disclose meaningful behavior: results are ordered newest first, scoped to the account, and contain statement keys for use with get_statement. However, it does not explicitly state that this is a read-only operation or describe any response shape or edge cases, leaving some behavior implicit.

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 concise clause that packs in the key facts: scope, ordering, returned content, and the downstream relationship to get_statement. Every word earns its place, with no repetition of the tool name or schema details.

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 optional-parameter list tool with no output schema and no nested objects, the description covers the essential context: what is returned, in what order, and why it matters. It could explicitly say 'use the returned key as the statement identifier argument to get_statement', but the current phrasing is sufficient for a low-complexity 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 input schema already documents the lone parameter 'limit' with a description and default of 12, so schema coverage is 100%. The tool description adds no additional parameter meaning beyond that, which matches the baseline of 3.

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 defines the resource as the account's billing periods with their statement keys and notes the newest-first ordering. It also references get_statement, distinguishing this listing operation from that retrieval sibling. The main verb is only implied by the tool name rather than stated explicitly, so it stops just short of a 5.

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 get_statement' indicates that this tool is used to obtain statement keys that are then passed to get_statement, giving clear context for when to use it. It does not explicitly state alternatives or when not to use it, but the intended workflow is reasonably clear.

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 present, so the description carries the burden of behavioral disclosure. It does well by revealing the default filter behavior (unresolved only), the fact that status filters results, and the fields returned. It omits pagination details, but for a simple read-only list tool these are the key behaviors.

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?

One compact sentence delivers the action, scope, returned fields, filter behavior, and default. There is no filler or redundancy, and every clause 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?

Given a single optional parameter, no output schema, and a simple listing operation, the description is complete enough for correct invocation. It explains what will be returned and the default filter behavior, covering the main information an agent needs.

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% for the single status parameter, listing all accepted values. The description adds meaningful semantics beyond the schema by stating that status filters results and that the default is unresolved only, which is not encoded in the 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 states a specific verb ('List'), a clear resource ('this account's support tickets'), and enumerates the returned fields (reference, subject, status, last activity). This clearly distinguishes it from sibling tools like get_ticket (single ticket) and create_ticket/reply_ticket (mutations).

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 usage context: use this tool to list the current account's support tickets, with an explicit default of unresolved only. It does not name alternatives or state when not to use it, but the listing scope is unambiguous.

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 or output schema are provided, so the description carries the transparency burden. It discloses useful behavioral traits: data comes from the tool's own probes rather than hearsay, no authentication is required, and optional restrictions exist. It does not state whether the result is a single top chain or a ranked list, nor what happens when no chain qualifies.

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 compact sentences with no filler: the purpose and data source are front-loaded, optional filters follow immediately, and the auth note is a useful closing detail. 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?

The tool is simple and all three optional parameters are fully documented in the schema. However, with no output schema, the description should ideally clarify the result shape—whether it returns one chain slug, a ranked list, or additional metadata—which is currently 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?

Schema description coverage is 100%, so the parameters are already well documented. The description restates the family and candidate-list restrictions without adding much semantic value beyond the schema, and the default ranking behavior is already captured in the prefer parameter's schema description.

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 with a specific verb and resource: 'Recommend a chain from measured data' based on status, uptime, and p50 latency. It is unambiguous about what the tool does, but it does not explicitly differentiate itself from the sibling pick_route, so it stops short of the strongest sibling-distinction score.

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 when to use the tool—when a chain should be chosen from measured data—and mentions optional filtering by family or candidate list. However, it gives no explicit guidance about when not to use it and does not mention alternatives such as pick_route, leaving the decision largely to inference.

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 usefully states that authentication is not required and describes the data sources (probes, costs), which indicates a non-mutating recommendation. It does not, however, disclose return shape, failure behavior, or whether any state changes occur beyond the recommendation.

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 main purpose is front-loaded in the first clause, and the rest is a compact list of the data inputs that justifies the recommendation. The separate 'No authentication required' sentence is useful and not redundant. No filler or repetition.

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 recommendation tool, the description covers purpose, key inputs, decision basis, and auth requirements well enough for an agent to invoke it. It could be slightly more complete by stating the output object shape, but 'recommend a route tier' already signals the primary return value.

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 baseline is 3. The description adds some context by naming the measured inputs (method weight, p50 on public/premium supply, costs) and matching the 'need' values, but it does not add invocation-level detail beyond the schema for chain, method, or need.

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 action ('Recommend a route tier'), the exact value space (cheap / balanced / fast), and the scope (one JSON-RPC call). This makes it clearly distinct from sibling tools like pick_chain, which chooses a chain rather than a tier.

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 tool is for choosing a route tier for a single JSON-RPC call using measured data, and notes that no auth is needed. However, it never explicitly states when to use pick_route instead of pick_chain or when not to use it, so the usage guidance is only implied rather than explicit.

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 states 'No authentication required,' which is a behavioral trait. It implies this is a read-only quote operation, but does not explicitly state that no state change occurs or mention rate limits or other side effects. Since no annotations are provided, the description carries the burden but lacks full transparency.

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 concise sentences, providing essential information without unnecessary verbosity. It efficiently conveys the tool's purpose and output type.

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?

The description gives a good overview of the output (weighted units cost and USD per 1M units per lane). It lacks details on response structure, error handling, or edge cases, but for a simple quote tool it is reasonably complete. No output schema exists, so the description carries the burden and does a decent job.

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% with all three parameters (tier, chain, method) described. The description adds context that tier corresponds to 'cheap/balanced/fast' lanes, but this is already present in the schema. No additional semantic meaning is provided beyond the schema definitions.

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: quoting a JSON-RPC call by providing weighted unit costs and USD per 1M units for each lane. It uses a specific verb ('Quote') and specifies the resource ('JSON-RPC call'), distinguishing it from billing or gas price 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 'before making it' gives some usage context, indicating this is a pre-execution check. However, it does not explicitly mention when to use this tool over alternatives like 'get_gas_prices' or 'buy_pack', nor does it describe conditions that would make this tool inappropriate.

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 burden and does disclose the state-changing behaviors: adding a message, resolving a ticket, and reopening a ticket. However, it does not mention permissions, reversibility, or what happens when both resolve and reopen are provided.

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 one tight, front-loaded sentence that uses inline code for boolean flags and avoids redundancy. 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 simple scalar-parameter tool with a fully described schema, the description plus schema give an agent enough to invoke it correctly. It lacks explicit output/response details and combined-flag behavior, but those are not required by the schema or annotations.

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%, so the schema already documents every parameter. The description reinforces the resolve/reopen semantics but adds no new parameter-level detail beyond the 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 states a specific action ('Add a message') and a clear resource ('one of this account's tickets'), then adds the two operational modes: resolve and reopen. This clearly distinguishes reply_ticket from sibling tools like create_ticket or get_ticket.

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 context is clear: this tool is for interacting with an existing ticket in the current account, not for creating or listing tickets. It does not explicitly name alternatives or provide when-not-to-use guidance, 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 provided, the description carries the full behavioral disclosure burden. It states that resolution happens on-chain via FlexYield's pool and warns that reverse records are self-declared and should be forward-verified, which is material trust context. It does not mention failure modes or network requirements, but the read-only 'get' semantics are clear.

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 compact sentences front-load the operation and immediately give an example of each accepted input. Every clause adds value, and the trust warning is placed after the main rules without bloat.

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 single-parameter read-style tool, the description covers the two invocation modes, the network, and a key trust caveat, and it implies the return type for each mode. It lacks explicit no-record/error behavior and does not clarify address formatting, but these are minor for this scope.

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% and the query parameter is already described as an ENS name or 0x-address. The description adds concrete examples, clarifies the return direction for each input form, and attaches a security caveat, so it contributes meaning beyond the schema's one-line description.

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 operation (ENS resolution on Ethereum mainnet), the exact input forms (a name or an address), and the two expected outputs (address or reverse-record name). It clearly distinguishes this tool from the many other sibling tools by stating the network and the on-chain mechanism.

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 conditions for use: pass a name to get an address, or pass an address to get a reverse-record name, and it adds a forward-verification warning for reverse records. It does not explicitly name alternative tools, but no sibling appears to cover ENS resolution, so the usage context is clear with no exclusions.

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 behavioral burden and discloses the key consequence: requests using the key stop working immediately. It also adds idempotence, telling agents repeated calls are safe. It doesn't detail response or error behavior, but the core risk is covered.

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 front-load the action and then add only high-value behavior: immediate effect and idempotence. No filler or repetition of the schema.

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 single-parameter destructive action, the description covers what is revoked, when it takes effect, and repeated-call safety. It omits output or error semantics, but the tool is simple enough that an agent can invoke it correctly from this text.

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 fully describes api_key_id with 100% coverage, so the baseline applies. The description adds a small ownership constraint—the key must belong to the authenticated account—but otherwise contributes no additional parameter detail.

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 opening verb 'Revoke' with the object 'API keys' states the exact operation, and 'authenticated account's' scopes it to the caller's own keys. This clearly distinguishes it from sibling create/bind/get/set key tools even without naming 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?

No explicit when-to-use guidance or alternatives are given; it never says to use create_api_key for issuing a key or contrasts with set_key_budget/bind_key. The only implied context is that revocation is for invalidating an existing key, which an agent must infer.

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 full responsibility for revealing behavior. It covers the read/write distinction, the effect of reaching a cap (-32014), and the behavior of disabled services (-32012). This is substantial behavioral disclosure beyond the basic operation, especially the error-code semantics.

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 three dense sentences with no filler. The primary purpose is front-loaded, the read mode is stated succinctly, and the error behaviors are presented in an efficient final sentence. 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?

The description is quite complete for a tool with no annotations and no output schema: it states the supported services, the read/change modes, and the relevant error codes. Minor gaps remain around the exact response shape for a normal read and how caps, enabled, and window parameters interact when combined, which leaves a little room for agent uncertainty.

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 baseline is 3. The description adds real value by enumerating the valid service keys, which the schema does not provide as an enum, and by explaining the monthly unit cap behavior and disabled-service error. This goes beyond the schema's parameter 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 opens with a specific verb-resource pair: 'Read or change the authenticated account's service settings.' It then enumerates the exact services (rpc, data, gas, tx_status, ens, prices, contracts, utils) and the two setting aspects (enabled state, monthly unit cap), making the tool's purpose unambiguous and distinguishable from siblings like set_key_services.

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 distinguishes the two modes: reading with no arguments versus changing caps or enabled services with arguments. It does not explicitly name alternatives or exclusions, but the 'authenticated account's' scope implicitly separates it from key-level service tools, so context is clear even without an explicit when-not-to-use statement.

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 of disclosing mutation behavior. It does reveal the null/0 clearing behavior, but it does not disclose side effects, authorization requirements, reversibility, or what happens after the cap is set. This goes only slightly beyond the title.

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 short sentences front-load the operation and the critical edge case (null/0 removes the cap) with no filler. 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 simple two-parameter setter with a complete schema, the description is mostly sufficient. However, there is no output schema and no mention of what the call returns or whether setting the cap affects already-consumed requests, which would help an agent fully anticipate the result.

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 documents both parameters with 100% coverage, including the meaning of null/0. The description restates that convention and adds budget context, but it does not provide meaning beyond what the schema already supplies, so baseline 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 states a specific verb ('Set or clear') and a precise resource ('monthly request budget of one of the account's API keys'), and it explicitly covers the remove-cap behavior. This distinguishes it from sibling key-management tools like revoke_api_key or set_key_services.

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 the key usage instruction: pass null or 0 to remove the cap, so the agent knows how to invoke it. However, it does not explicitly say when to prefer this tool over related key tools or mention alternatives such as usage_report for inspecting budgets, leaving when-to-use guidance implied.

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 behavioral burden and does so well. It discloses exact error behavior (-32012 with blocked_by: key, -32014 with scope: key), the clearing semantics of empty values, and the hard constraint that a key can never exceed account-level settings. This is substantive context beyond the schema.

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 organized, with the main purpose front-loaded and backtick formatting making parameter semantics scannable. Every sentence adds value: scope, error behavior, constraint, and read-vs-write distinction. 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?

The description is largely complete for a read/update tool: it covers the main parameters, error semantics, scoping, and constraints. The main gap is that `window` is not mentioned in the description and no output schema is present, leaving the read-report behavior slightly underspecified. Still, this is a minor gap given the schema covers `window`.

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 baseline is 3. The description adds meaning by clarifying that `enabled` is the FULL list to keep on, `caps` applies per key alone, an empty value clears, and id-only means read. However, the `window` parameter is not integrated into the tool description, even though the schema explains it.

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 pair, 'Read or change', and identifies the exact resource: which gateway services one API key may use and its per-service monthly unit caps. It clearly distinguishes this from account-level siblings by emphasizing 'ONE of the account's API keys' and listing the service types.

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 usage context: 'No arguments besides id = read' tells the agent how to perform a read, while the descriptions of `enabled` and `caps` imply how to perform changes. It does not explicitly name alternative tools or state when not to use this tool, 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It clearly states the mutation and scope, but it does not clarify whether omitted parameters are left unchanged or reset to defaults—a significant ambiguity given that all four parameters are optional. It also omits any auth, persistence, or side-effect 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?

One sentence that front-loads the action and resource, then compactly lists all relevant settings. Every phrase earns its place; there is no fluff or redundant restatement of the tool name.

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 scalar-only setter, the description plus the 100% schema coverage handles the core invocation details. The main gap is the missing partial-update semantics: because no parameters are required, an agent needs to know whether providing only one preference preserves or resets the others.

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 already documents each parameter, but the description adds useful meaning beyond the schema: it ties the booleans to the 80% and 100% monthly-quota thresholds and specifies that the timezone is for the console and must be an ActiveSupport/IANA name. This enriches the otherwise minimal 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 uses a specific verb ('Set') and names a precise resource: the account owner's notification preferences. It further enumerates the exact preferences—80% and 100% usage alerts, incident notices, and the console timezone—making it clearly distinguishable from sibling 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 intended use is inferable: an agent should call this when modifying notification preferences. However, there is no explicit guidance about when to prefer this over nearby settings-related siblings such as service_settings or update_account_insights, and no exclusions or alternatives are named.

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 behavioral burden. It does add useful context by noting that feedback is "Private to the account" and that the answer and status later appear in list_feedback, implying an asynchronous or record-producing operation. It does not disclose mutation side effects, permissions, or rate limits, though 'Send' implies a write 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 main action is front-loaded, and the second sentence adds important privacy and follow-up behavior without wasting 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 four-parameter tool with no annotations and no output schema, the description covers purpose, scope, privacy, and where results will appear. It does not describe the immediate return value or any prerequisites, but the schema covers required inputs and list_feedback provides the visible outcome, so the definition is reasonably 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?

Schema description coverage is 100%, so the baseline is 3 and the schema already documents all four parameters. The description adds some contextual mapping by listing "feature wish, chain request, praise or complaint," which helps clarify the kind and chain parameters, but it does not add substantial detail beyond the 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 states a specific verb and resource: "Send product feedback for this account," and enumerates the accepted types: feature wish, chain request, praise, or complaint. It points to list_feedback for follow-up but does not explicitly differentiate this from sibling tools like create_ticket or enterprise_wishlist.

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 is for product feedback scoped to the account, and hints at the workflow via "the answer and status show up in list_feedback." However, it does not explicitly state when to prefer this tool over alternatives such as create_ticket or enterprise_wishlist, nor does it give any when-not-to-use 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 provided, the description carries the full burden of behavioral disclosure. It says the data is optional and lists allowed values, but it does not reveal whether existing insights are overwritten or merged, whether account-level permissions are required, or what confirmation or response the agent should expect. The update semantics are only implied by the tool name.

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 purpose and field list are front-loaded in a single opening sentence, and the allowed values are packed into a compact pipe-delimited list. It is efficient, though the dense formatting could be slightly easier to parse if grouped per field.

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 9-parameter tool with no output schema and no annotations, the description covers the core input data and the optional nature of the call. It is not fully complete because it lacks behavioral details such as overwrite/merge behavior, authorization requirements, and expected return value.

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 only 33%, so the description compensates by providing explicit allowed-value enumerations for use_case, team_size, volume, region, previous_provider, referral_source, and wish_chains, plus clarifying that chains are live chain slugs. It omits wish_chain_other from the description, but the schema already documents that parameter, making the gap minor.

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 action ('Tell FlexYield about the account's setup') and enumerates the exact data fields involved, so the tool's purpose is immediately clear. It also reads distinctly from sibling tools: this is about recording optional account segmentation, not retrieving usage stats or managing billing.

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 labels the data as 'optional segmentation data' and lists no required parameters, so an agent can infer when it might be useful. However, it does not explicitly say when not to use it, nor does it name alternative sibling tools for similar data-collection or setup tasks.

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 must carry the behavioral burden. It usefully states the authenticated-account scope and the exact metric breakdown, and 'Report' strongly implies a read-only operation. It does not disclose potential delays, output structure, rate limits, or whether any billing-related side effects occur.

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 states the subject and then uses a colon to present a dense but organized list of delivered metrics. No filler or redundancy; every clause adds 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?

The description and schema together cover what the tool returns and how to call it, but there is no output schema and no guidance to disambiguate from the closely named usage_stats and usage_volume siblings. For a report tool with no annotations, the lack of a statement about response format or non-mutating behavior leaves minor but real 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?

The input schema covers 100% of the two optional parameters with descriptions, including a default value for hours, so the schema already does the heavy lifting. The tool description adds no parameter-specific detail beyond mentioning per-chain counts, which maps loosely to the chain 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?

The description clearly identifies a specific resource ('the authenticated account's RPC gateway usage') and enumerates the concrete metrics returned, which goes beyond the tool name. It doesn't explicitly contrast with similarly named siblings like usage_stats and usage_volume, so it stops short of full differentiation.

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 is given about when to choose usage_report over sibling tools such as usage_stats or usage_volume, and there are no exclusions or alternative conditions. The only implied usage is to report usage, which essentially restates the tool's purpose.

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 at all, the description carries the full burden, and it delivers meaningful behavioral facts: spend has 'no metered overage exists; Builder has no ceiling,' units_saved is explained as the nominal weight cache hits would have cost, and money_saved_cents is tied to rate_basis ('plan or pro_reference'). The only gap is that read-only/auth behavior is implied rather than stated outright.

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 front-loaded, opening with the core purpose before diving into report specifics. Every clause earns its place, though the four report modes are packed into one semicolon-heavy paragraph where bullets would have improved scannability.

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 does the necessary work of explaining return content for all four report types, including edge semantics like quota-exhaustion risk and the no-ceiling behavior. Minor gaps remain: authentication requirements, error behavior for invalid report values, and how window interacts with each report beyond 'ignored for spend' are not addressed.

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 baseline is 3, but the description adds substantial meaning beyond the schema's terse 'One of: latency, errors, spend, cache' by specifying exactly what each report value returns (e.g., 'per-chain p50/p95 per bucket + summary'). It also reinforces a schema fact, that window is ignored for spend, which helps agents pick the right arguments.

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 opens with a clear statement of what the tool does: 'Windowed statistics for the authenticated account,' anchored to 'the console's Statistics pages,' and enumerates four report modes (latency, errors, spend, cache) with concrete metrics. It is clearly a statistics retrieval tool, but it never explicitly differentiates itself from the closely named siblings usage_report and usage_volume, so an agent must infer the distinction.

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 context is implied through the detailed report-mode breakdown: an agent can tell that this tool serves latency/error/spend/cache statistics needs. However, there is no explicit when-to-use or when-not-to-use guidance, and no mention of alternatives like usage_report, usage_volume, or billing_status, which overlap in the usage/billing domain.

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 behavioral disclosure burden. It reveals key implementation details: buckets are zero-filled, a bucket is marked partial when the window starts inside it or it is still filling, and the data matches the dashboard/CSV export. These are non-obvious behaviors an agent needs to interpret the response correctly.

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 consists of two very specific sentences, the first stating the purpose and the window options, the second adding behavioral details and data source consistency. All details are actionable and not redundant — every sentence delivers a relevant fact.

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 two-parameter tool with no output schema and no annotations, the description is quite complete: it explains the kind of data returned, the bucket semantics, the supported windows, and the data source. It could explicitly list the response fields, but the description gives an agent enough to call the tool and interpret the result.

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%: the schema documents both 'chain' and 'window' with examples and valid values. The description adds little beyond restating the window list and implying how the parameters shape the time buckets; it does not elaborate on parameter semantics beyond the schema. A baseline of 3 applies when the schema already carries that information.

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 indicates a specific resource ('Requests over time for the authenticated account') and a specific data representation (zero-filled time buckets), which makes the tool's purpose obvious. It does not explicitly differentiate it from similar siblings such as 'usage_report' or 'usage_stats', but the resource and behavior are described well enough to infer a distinct 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 provides context for when to use the tool ('Same data as the dashboard chart and CSV export') but does not explicitly state when to use this tool versus alternative siblings like 'usage_report' or 'usage_stats'. The various window options give usage context, but there is no direct WANT claim about alternatives or exclusions.

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 burden of behavioral disclosure. It reveals a key security posture ('FlexYield never holds keys'), explains what operations are performed (parses fields, checks signature and expiry), and notes the boundary that domain/nonce policy is left to the caller. It does not describe error or invalid-signature behavior, which would strengthen it further, but it provides meaningful behavioral 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 dense but well-organized sentence. It groups related information in parentheses and separates the two modes clearly. It is not bloated, though breaking it into two sentences would slightly improve scannability for an agent parsing it quickly.

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 there is no output schema, the description needs to convey the verification result contract. It explains what inputs are checked and the security policy, but it does not tell the agent what the tool returns on success versus failure (e.g., boolean, parsed fields, or error). That missing piece prevents the description from being fully self-sufficient for correct invocation and interpretation.

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 already provides 100% coverage with descriptions for all four parameters, so the baseline is 3. The description adds valuable mode-specific semantics: it ties 'message' and 'signature' to their exact formats in each mode, clarifies 'address' as an optional expected signer for personal mode, and explains that SIWE mode parses embedded fields from the message text. This goes beyond the bare schema hints.

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 opens with a specific verb ('Verify') and identifies two concrete resource types (EIP-191 personal_sign and SIWE/EIP-4361). It clearly distinguishes the two modes ('personal' vs 'siwe') and what each validates, making it immediately identifiable among the large sibling tool list that contains no other verification tool.

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 states the exact conditions for each mode: personal mode with message + 65-byte signature and optional address, siwe mode with exact message text and signature. The closing 'Recovery only' clarifies when verification is appropriate. It does not name alternative tools explicitly, but the mode breakdown serves as practical usage 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 burden. It does make the behavioral trait 'Read-only' explicit, which is useful and prevents the agent from assuming mutation. It also lists the categories of information returned (door/tier, budgets, fences, volume, break-even, account features, other doors), giving an idea of the response scope. However, it does not disclose whether results are formatted as JSON, whether authentication or a specific API key context is required, or any side effects beyond read-only. For a non-mutating overview tool this is moderate transparency.

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 long list; it is not overly verbose but it is not well-structured or front-loaded. The most important insight, 'read-only', appears at the end. The many comma-separated items are cryptic and could be clarified with definitions. It earns a place but could be more concise and clearer in ordering.

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 zero params, no output schema, and no annotations, the description should carry full context. It tells us roughly what the tool reports, but leaves the agent guessing what terms like 'door', 'fence', 'lane', and 'break-even sentence' actually mean in API key context. There's no indication of the response structure (e.g., plain text vs. JSON) or how to interpret the output. For a tool that appears to be a general status overview, the description lacks the explanatory depth needed for a new agent to confidently reason about what it will receive.

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 with no properties, so there are no parameters to explain. The description adds value by implying that the tool operates on the current API key's context, which is a reasonable baseline for a zero-parameter tool. No schema coverage issue exists, and the baseline score for 0 params is 4.

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 an identifiable purpose: it reports the current status and capabilities of an API key (door and tier, budgets, permissions, volume pricing, break-even, account features). This distinguishes it from more focused siblings like get_key, billing_status, or usage_report by framing it as an overview tool. However, the heavy use of domain jargon (door, fence, lane, break-even sentence) makes the intended purpose less immediately accessible, though not a tautology.

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 explicit guidance about when to use this tool versus alternative siblings. The description does not say 'use for a high-level overview', nor does it direct the agent to specific tools for detailed data. The only guidance is 'Read-only', which sets expectation but does not help with tool selection. No when-not or alternative is mentioned.

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