Tenzro LayerZero V2 MCP

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

Discloses that it returns transaction hash on success and describes the expected input format. No annotations provided, but description covers essential behavior without contradictions.

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?

Concise, front-loaded with purpose, then usage steps, then return value. Every sentence adds value with no fluff.

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?

Output schema exists (per context), so description need not detail return values. Workflow is complete, but could mention error handling or RPC dependency. Still adequate.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, and description adds contextual meaning by explaining how to construct signed_tx_hex and listing valid src_chain examples, going beyond 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?

Clearly states it broadcasts a pre-signed Ethereum transaction via eth_sendRawTransaction, specifies source chain, and differentiates from sibling tools that produce calldata.

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?

Explicitly states when to use (canonical broadcast path for calldata from specific tools) and provides step-by-step process including constructing calldata, signing with nativeFee, and submitting RLP-encoded hex.

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?

Describes internal structure (executor worker ID, option type, gas limit, native drop) and output format (hex-encoded bytes). No side effects or auth needed; transparent for a pure encoding function. No annotations provided, so description carries burden adequately.

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 concise sentences, front-loaded with purpose, no wasted words. Efficiently conveys key technical 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 output schema exists, description is complete: explains what tool does, how it relates to other LayerZero functions, and technical format. No gaps for a utility encoding 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 covers 100% of parameters with descriptions. Description adds context like 'on destination' and 'lzReceive execution' but not significantly beyond schema. Baseline of 3 applies.

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?

Explicitly states the tool encodes LayerZero TYPE_3 options bytes for EndpointV2.quote()/send(), specifying version, format, and components. Clearly distinguished from sibling tools like lz_quote_fee or lz_send_message by focusing on encoding.

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?

Mentions use cases (EndpointV2.quote()/send()) but lacks explicit when-not-to-use or alternatives. Usage is implied but not elaborated.

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 explains the tool's behavior (returns a public RPC URL) and its server-side usage, but it does not disclose read-only behavior, authentication requirements, or error scenarios. The description adds some context beyond the name but is not comprehensive.

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 concise sentences. The first sentence clearly states the action, and the second adds relevant usage context. There is no unnecessary information, and it is front-loaded with the essential purpose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple tool with one parameter and an output schema (not described), the description covers the core functionality but lacks details such as the output format, supported chain names, and error handling. Given the schema coverage is high and the output schema is present, the description is adequate but not fully comprehensive.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% for the single parameter, with examples given. The tool description adds the concept of 'public' RPC URLs and their use in eth_call queries, which provides meaning beyond the parameter description. This extra context helps the agent understand the nature of the returned value.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Get the public RPC URL for a supported chain by name.' It distinguishes this from sibling tools like lz_list_chains, which lists chain names but does not return RPC URLs. The verb 'Get' and the specific resource 'public RPC URL' make the action and result unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage context by noting these RPCs are used for eth_call queries against EndpointV2, but it does not explicitly state when to use this tool versus alternatives like lz_list_chains or lz_get_deployments. No exclusions or alternatives are mentioned, leaving the agent to infer from the tool names.

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 must fully disclose behavior. It only mentions data source (LayerZero Metadata API) and returned address types, but fails to state that it is read-only, whether authentication is required, or any rate limits or error conditions. Incomplete for a non-annotated 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?

Two concise sentences with no fluff. Core information is front-loaded. Every sentence adds value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple getter with no parameters and an output schema, the description explains what is returned. However, lacks details about authentication or potential errors, but these are minor given the tool's simplicity. Nearly 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?

Input schema has zero parameters, and schema coverage is 100%. Description adds no parameter info, but since there are none, it doesn't need to. Baseline score of 4 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?

Clearly states verb 'Get', resource 'LayerZero V2 deployment addresses', and scope 'across all supported chains'. Distinguishes from sibling tools like lz_list_chains or lz_get_chain_rpc by specifying it returns specific contract addresses.

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?

Implied usage is for retrieving deployment addresses, but no explicit guidance on when to use versus alternatives (e.g., when needing a single address vs. all) or when not to use. Lacks context for decision-making.

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 states it retrieves a message, which implies a read operation, but does not disclose any potential side effects, auth requirements, or error behavior. This is adequate for a simple getter but lacks depth.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences, front-loaded with the core purpose, and contains no unnecessary words or 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 getter with one parameter and an output schema, the description is fairly complete. It could mention what happens if the GUID is invalid, but that may be covered by the output schema or error responses.

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 and describes the GUID format. The description adds valuable context about how the GUID is obtained (from EndpointV2.send() or Scan API), which goes 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 clearly states the action ('Get') and the resource ('LayerZero message by its GUID'). It also explains where the GUID comes from, distinguishing it from siblings like lz_get_messages_by_address which retrieves by address.

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 suggests when to use (when you have a GUID) but does not explicitly mention when not to use or name alternatives like lz_get_messages_by_address. It provides context 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?

Discloses that it queries the Scan API and returns messages sent/received, plus the nature of the output (status, chains, timestamps). With no annotations, this provides good 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?

Two sentences with no filler: first states purpose, second provides mechanism and output. Front-loaded and efficient.

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 an output schema existing (per context), the description covers key aspects: input, API queried, and output fields. Lacks mention of the limit param but schema covers it.

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 both parameters have schema descriptions. The description adds no new semantics beyond restating the address parameter; limit is not mentioned.

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?

Describes 'Get LayerZero messages for a specific wallet address' with a clear verb and resource. Distinguishes from siblings like lz_get_message by specifying wallet address as the key parameter.

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?

Explicitly states the context (wallet address) for using this tool, making it clear when to invoke. No explicit exclusions or alternatives mentioned, but the context is sufficient.

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 openly states that the tool lists chains and EIDs, implying a read-only, non-destructive operation. No hidden behaviors or contradictions.

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 with two sentences. It front-loads the core action and purpose, then provides additional context. Every sentence adds value 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?

Given zero parameters, an output schema, and high schema coverage, the description is complete. It explains the tool's output (list of chains with EIDs) and their significance in the broader LayerZero workflow.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters, so the description adds no parameter-specific meaning. Baseline 4 applies because the schema coverage is 100% and the description does not need to compensate for missing schema details.

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 specifies the verb 'List' and the resource 'all 16 chains supported by this LayerZero MCP server with their Endpoint IDs'. It enumerates the chains, distinguishing this tool from sibling tools that deal with transactions, OFTs, or messaging.

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 the usage context by stating that EIDs are used in EndpointV2.quote() and EndpointV2.send(), guiding the agent on when to use this tool. It does not explicitly exclude alternatives, but the purpose is well-defined.

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

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

No annotations are provided, so the description carries the full burden. It discloses that the tool returns DVN names, addresses, supported chains, and configuration details. It does not mention pagination or authorization, but for a zero-parameter list endpoint, this is sufficient.

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 efficiently written sentences. The first states the action and scope, the second adds context and lists return fields. No wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has zero parameters, an output schema exists, and the description covers purpose and return values, it is largely complete. Minor missing details like pagination or rate limits do not significantly detract.

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?

There are no parameters, and schema description coverage is 100%. The description adds meaning by explaining what DVNs are and what data is returned, which goes beyond the empty schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'List' and the specific resource 'all Decentralized Verifier Networks (DVNs)'. It distinguishes from siblings like lz_list_chains by focusing on DVNs and their role in cross-chain message verification.

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 when to use the tool (to list DVNs) but does not provide explicit exclusions or alternatives. However, with many sibling tools having distinct purposes, the context is clear enough for an AI agent.

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. Description indicates a read-only query, but does not explicitly mention being non-destructive or any potential side effects. Adequate but lacks depth.

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?

Single sentence, efficient, and front-loaded with the core action. No extraneous information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a list tool with no parameters and an output schema, the description adequately explains the purpose and return values, making it 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?

No parameters, so schema coverage is 100%. Description adds meaning by explaining what the tool returns, meeting the baseline of 4 for zero-parameter tools.

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?

Description clearly states it lists all available OFT deployments from the LayerZero Metadata API, specifying the returned data types. Distinct from sibling tools that perform specific actions like sending or quoting.

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?

Implied usage for discovering available tokens, but no explicit guidance on when to use this tool versus alternatives or any prerequisites.

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 the description must disclose behavioral traits. It implies a read-only lookup (quote) but does not explicitly state it has no side effects, nor does it mention any restrictions, rate limits, or error conditions.

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?

Single sentence that is compact and front-loaded, conveying the essential purpose without any 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?

Description adequately states the function and outputs, but lacks context about typical usage flow (e.g., precede lz_oft_send) or handling of special cases. With an output schema present, return values are covered, but completeness is only moderate.

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?

Input schema covers 100% of parameters with clear descriptions. The description adds no extra meaning beyond the schema, so baseline score of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Quote an OFT transfer') and the resource ('using LayerZero Metadata API'), listing expected outputs (fees, rates, details). However, it does not explicitly differentiate from sibling quote tools like lz_quote_fee or lz_stargate_quote.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool versus alternatives, no prerequisites or conditions mentioned. Given multiple sibling tools for quotes and transfers, the agent lacks decision support.

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 fully handles transparency. It discloses return type (hex-encoded calldata), key parameter nuances (shared decimals, left-padded recipient), and the required msg.value. Could mention the function signature explicitly, but sufficient for tool selection.

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?

Description is concise with two focused paragraphs: first explains purpose and OFT V2 nuance, second outlines workflow. No filler; every sentence adds value. Front-loaded with key 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?

Tool has 7 parameters (5 required), high schema coverage, and output schema exists. Description covers all parameter semantics, workflow, and return value. For a complex cross-chain token operation, this is complete and actionable.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so baseline is 3. Description adds value by explaining amount in shared decimals (uint64), recipient padding, gas_limit default (200000), and min_amount default (90%). This goes beyond the schema's basic 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?

Description clearly states 'Build transaction calldata for an OFT send() call on any OFT contract', specifying a specific verb and resource. It distinguishes from siblings by mentioning prerequisites (lz_quote_fee, lz_oft_quote) and OFT V2 specifics, making 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?

Provides explicit usage guidance: caller must first call lz_quote_fee or lz_oft_quote, then sign and broadcast with msg.value = nativeFee. Also notes OFT V2 uses uint64 amountSD, clarifying when to use this tool versus 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, the description must fully disclose behavior. It reveals that the tool performs an eth_call (read-only) and returns two fee types, and gives contract address and selector. However, it does not discuss edge cases (e.g., chain support, fee variability), failure modes, or any permissions needed. Adequate but not comprehensive.

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 sentences long, front-loading the main purpose and then providing technical specifics. Every sentence adds information without redundancy. Highly efficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has an output schema (not shown), the description covers the essential behavior: estimating fees, return types, and on-chain details. It lacks some context like dependency on RPC health or chain availability, but overall is sufficiently complete for a read-only fee estimation 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 description coverage is 100% (all parameters have descriptions). The tool description adds no additional parameter semantics beyond what the schema already provides, so baseline score of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool estimates cross-chain messaging fees via LayerZero EndpointV2.quote(), and specifies the return values (native fee and LZ token fee), the contract address, and the selector. This distinguishes it from sibling tools like lz_send_message or lz_oft_quote.

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 provide explicit guidance on when to use this tool versus alternative quote tools (e.g., lz_oft_quote, lz_stargate_quote). It only states its function, missing when-not-to-use or context for selection among siblings.

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

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

With no annotations, the description carries the transparency burden. It discloses the tool returns calldata (not broadcasts), requires msg.value from lz_quote_fee, and provides the selector. This is good coverage for a calldata builder.

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 plus a selector line, with no wasted words. Information is front-loaded and efficient.

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 covers the tool's output, workflow dependency on lz_quote_fee, and the need to sign/broadcast. It does not detail output schema or error handling, but an output schema exists (per context signals) and these are acceptable gaps for a calldata builder.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so baseline is 3. The description adds no new parameter details beyond what the schema provides (e.g., receiver padding and options default are already in schema). It does not compensate further.

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 builds calldata for EndpointV2.send() to dispatch cross-chain messages via LayerZero V2, and returns hex-encoded calldata. It distinguishes itself from siblings like lz_broadcast_signed_tx by specifying it does not broadcast.

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 that the caller must sign and broadcast the transaction with msg.value from lz_quote_fee, implying a workflow: first quote, then build calldata, then sign/broadcast. This provides useful usage context, though it does not explicitly compare to 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 discloses key behavioral traits: it is a read-only quote operation, calls a specific contract function, and returns the fee in wei and minimum amount after slippage. It does not mention potential failure modes or rate limits, but adequately covers the expected behavior for a quote 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 concise and well-structured, starting with the main purpose, then explaining the mechanism, return values, and supported assets. Every sentence adds value 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?

Given the tool's complexity, the description covers the essential aspects: purpose, mechanism, return values, and supported token/chain combinations. It omits potential error cases or edge cases, but for a quoting tool, this is sufficient. The presence of an output schema reduces the need to describe return format in detail.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% coverage, but the description adds meaningful context beyond schema descriptions. It clarifies the amount unit (base units, specifying 'wei for ETH, micro-units for USDC/USDT') and lists supported tokens and chains, which helps agents use the 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 clearly states the tool's purpose: quoting a Stargate V2 native bridge transfer fee by calling quoteSend(). It specifies the supported tokens and chains, making the purpose specific. However, it does not explicitly differentiate from sibling tools like lz_oft_quote or lz_transfer_quote, which also quote fees for different protocols.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for getting Stargate bridge fees but provides no explicit guidance on when to use this tool versus alternatives. It does not state when not to use it or mention any prerequisites or scenarios where another tool would be more appropriate.

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

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

Discloses key behaviors: returns unsigned calldata, requires separate broadcast, describes msg.value composition, and token-specific approval needs. Could mention error handling or limitations, but covers main traits.

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?

Four sentences: purpose and returns, caller action, ETH case, ERC-20 case, supported tokens/chains. Front-loaded, no redundancy, each sentence adds distinct 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?

Covers input, usage steps, token-specific behavior, and supported chains. Output schema exists (not shown), so return values are documented elsewhere. Could mention prerequisites like token balance or pool approval.

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 describes all parameters (100% coverage). Description adds value by explaining amount units (wei vs micro-units), msg.value logic, and token-chain support details.

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?

Description clearly states it builds calldata for Stargate V2 sendToken(), specifies return values (calldata, target address, msg.value), and distinguishes from quoting tools like lz_stargate_quote.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides explicit guidance: caller must sign and broadcast, approves for ERC-20, different msg.value for ETH vs ERC-20. Lacks explicit instructions on when to choose this tool over siblings like lz_transfer_build.

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

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

The description discloses that it queries the LayerZero Scan API and lists return statuses, but it does not state that it is a read-only operation, any rate limits, or authentication requirements. Since no annotations are provided, the description carries the full burden and leaves some gaps.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences, front-loaded with the core action, and contains no fluff. Every sentence provides necessary information about input, API, outputs, and statuses.

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 presence of an output schema (not shown but indicated), the description appropriately does not detail return fields. It covers the input, the API, and possible statuses. Minor omission: no mention of error handling or prerequisites, but overall sufficient for a simple query tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema already covers 100% of the single parameter with a description. The tool description adds context by calling it the 'source transaction hash' and ties it to the API, reinforcing its purpose beyond the schema's basic definition.

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 tracks a cross-chain LayerZero message via source transaction hash, specifies the API and possible statuses (INFLIGHT, CONFIRMING, etc.), and distinguishes it from siblings like lz_get_message (which likely takes a different identifier) by emphasizing the input is a transaction hash.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for tracking messages by tx_hash but does not explicitly mention when to avoid this tool or suggest alternatives. Siblings like lz_get_message or lz_get_messages_by_address exist, but no comparative guidance is provided.

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

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

With no annotations, the description carries full burden. It discloses key behavioral traits: automatic handling of approval and bridge steps, and that output is calldata for signing/broadcasting. Does not mention potential failure modes or auth requirements, but is adequate for a build 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?

Three concise sentences with no filler. First sentence states purpose, second details input/output, third adds behavioral note. Efficient and front-loaded.

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 one parameter, existing output schema, and clear sibling connections (lz_transfer_quote, lz_broadcast_signed_tx), the description covers all essential aspects: purpose, input, output, and key behavior. Complete for the tool's complexity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so baseline is 3. The description reiterates the schema's description for quote_id without adding new meaning, so no extra value beyond schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Build signable transaction steps'), the resource ('from a Value Transfer API quote'), and the output ('pre-built transaction calldata'). It also distinguishes from siblings by explicitly referencing the prerequisite tool lz_transfer_quote.

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 indicates the tool should be used after obtaining a quote from lz_transfer_quote, providing clear context. However, it does not specify when not to use it or mention alternatives among siblings.

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

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

With no annotations, the description fully bears the burden of transparency. It discloses the return size (130+ chains), includes specific examples (Solana, EVM L1s and L2s), and mentions chain keys, adequately informing the agent of what to expect.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two concise sentences front-load the core action and add specific details without any 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 zero-parameter tool with an output schema, the description provides sufficient context about the returned chains and their relevance to a sibling tool. No obvious 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?

No parameters exist, so the baseline is 4. The description adds meaning beyond the schema by explaining the tool's purpose and output, contextualizing the empty schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'List' and the resource 'all chains supported by the LayerZero Value Transfer API'. It further distinguishes its output for use in a specific sibling tool (lz_transfer_quote), providing clear 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 implies usage context by noting the chains are for use in lz_transfer_quote, but does not explicitly state when not to use it or list alternatives. Clear context but 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 discloses that the tool returns quotes with fees, estimated times, and a quote ID. It also makes clear it is a read-only quoting operation. However, it omits details like error handling, rate limits, or default behavior for missing parameters. The information provided is sufficient for basic usage but could be more thorough.

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 plus a note about native ETH address. It is front-loaded with the core purpose and includes essential details without unnecessary words. Every sentence 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?

Given the tool's complexity (7 required parameters, cross-chain transfer), the schema covers all parameters, and an output schema exists. The description explains the API context, supported chains, and the return include of a quote ID. No additional details are needed for an agent to invoke correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so baseline is 3. The description adds value by explaining the use of 0xEeeeeEeeeEeEeeEeEeEeeEEEeeeeEeeeeeeeEEeE for native ETH, and provides example chain keys. This clarifies token address semantics beyond 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 clearly states the tool retrieves a cross-chain transfer quote from the LayerZero Value Transfer API, specifies it replaces the deprecated Stargate API, supports 130+ chains including Solana, and returns key outputs (fees, estimated times, quote ID). This distinguishes it from sibling quote tools like lz_stargate_quote.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly mentions this is the newest API replacing the deprecated Stargate REST API, giving clear context. However, it does not explicitly compare to other sibling tools like lz_oft_quote or lz_quote_fee, or state when not to use this tool. The hint that the quote ID is for building transaction steps (linking to lz_transfer_build) provides some alternative context.

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 correctly indicates a read-only operation ('Check the status'), but does not disclose potential side effects, authentication needs, rate limits, or error behavior (e.g., invalid quote_id). This is adequate but could be more informative.

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 is front-loaded with the main action and key details. No filler words; every part serves a purpose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has one required parameter and an output schema, the description covers the essential information: what it does, what identifier is needed, and what is returned. It does not need to explain return values further. Slightly more context about error handling could push it to a 5.

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 one parameter described. The description adds 'or transfer ID' to the parameter meaning, but the schema already states 'Quote ID or transfer ID'. Since schema description coverage is high, baseline is 3; the description adds minimal extra value.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'Check' and the resource 'Value Transfer API transfer', specifies the identifier 'quote ID', and lists what is returned (status, hashes, progress). This distinguishes it from sibling tools like lz_quote_fee or lz_transfer_quote.

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 (to check transfer status) but does not explicitly state when not to use it or provide alternatives. Given the tool name and context, the usage is clear, but explicit exclusions would improve it.

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 fully informs the agent that this is a read-only listing operation. It describes the returned data (addresses, symbols, decimals, chain availability), providing sufficient 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 concise with two sentences, front-loading the main purpose and then adding optional filtering. No wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has one optional parameter and an output schema exists, the description provides all necessary information for an agent to use it correctly. It covers purpose, filtering, and return contents.

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 single parameter 'chain' is fully explained in the description with an example ('e.g. 'optimism', 'solana''), adding meaningful context beyond the schema's type and 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 it lists tokens for cross-chain transfer via LayerZero Value Transfer API, with optional chain filtering. It distinguishes itself from siblings like lz_oft_list and lz_transfer_quote by focusing on token availability.

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 indicates when to use the tool (to list available tokens) and mentions optional filtering by chain. However, it does not explicitly state when not to use this tool versus alternatives, though the context of sibling tools makes the purpose clear.

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