xrploracle

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 does reveal the scope of data returned (balance, trust lines, offers, escrows, flags), which implies a read-only lookup. However, it does not mention whether it queries the live ledger, if the address must exist, or any error/edge-case behavior, leaving gaps in 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, compact sentence with no unnecessary words. The colon-separated list is efficient and instantly scannable, making it easy for an agent to parse the tool's 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 one-parameter read operation, the description covers the key data categories, but it does not address potential return formats, pagination, or error conditions. Since there is no output schema, the description itself needs to provide enough context for the agent to know what to expect; it is adequate but not fully 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?

The input schema fully describes the single parameter 'address' with 'XRPL classic address (r...)', achieving 100% coverage. The description adds no additional parameter semantics, so it meets the baseline where the schema does the heavy lifting.

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 enumerates the specific account data included (XRP balance, trust lines, open offers, escrows, flags), which distinguishes it from sibling tools that target individual aspects. However, it lacks a strong imperative verb like 'get' or 'retrieve', using the nominal 'intelligence' instead, which leaves the action implied rather than explicit.

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 siblings like xrpl_trust_lines or xrpl_escrow_check. The description implies it provides an aggregate account snapshot, but it does not explicitly state that it should be preferred for a high-level overview or when multiple data types are needed at once, nor does it mention 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 of behavioral disclosure. It indicates the tool supplies pool data, implying a read-only operation, but it does not disclose side effects, permissions, rate limits, or any other behavioral traits. There is no contradiction with annotations, but the description falls short of meaningful 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 no filler, immediately stating the domain and key data points. It is appropriately brief and front-loaded, earning a perfect score for conciseness.

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 that there is no output schema and no annotations, the description should clarify what the response contains and how the optional parameters influence the query. It fails to explain the output structure beyond vague terms like 'intelligence', and it does not connect the parameters to the data returned, leaving the tool under-specified.

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 includes two parameters (asset and asset2) with no descriptions, and the tool description does not explain their role or how they affect the query. Since schema description coverage is 0%, the description should compensate, but it merely lists outputs and leaves the parameters ambiguous.

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 as providing XRPL AMM liquidity pool data, specifying key outputs such as reserves, trading fee, and LP token supply. However, it lacks a definitive action verb and doesn't explicitly differentiate from sibling tools like xrpl_dex_orderbook or xrpl_trust_lines.

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 no guidance on when to use this tool versus alternatives, and it does not mention any prerequisites or exclusion criteria. The only implicit usage is derived from the domain name 'AMM pools' in the title, which is not sufficient 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?

With no annotations provided, the description carries the full burden. It discloses that this is a read operation and specifies the kind of data returned (mesh health, settlement lanes, join instructions). However, it does not provide details on output format, latency, or access requirements, which would be useful for a complete behavioral picture.

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

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

The description is short and front-loaded with the primary action. The final sentence ('The heartbeat of the autonomous agent economy') is metaphorical and not strictly necessary, but it does not detract significantly. Overall, it is concise and readable.

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 having no output schema, the description lists the main types of information returned (mesh health, settlement lanes, join instructions), which is adequate for a simple parameterless read tool. It does not go into deeper interpretation details, but the low complexity and clear purpose make the description sufficiently 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?

The tool has 0 parameters, so the baseline is 4. The description adds no parameter-specific semantics, but none are needed since the input schema is empty and description already clarifies the tool's scope.

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 'Read' and the specific resource 'OracleNet beacon'. It also enumerates what the tool provides (mesh health, settlement lanes, join instructions), making it distinct from sibling tools like xrpl_settlement_status or xrpl_overview.

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

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

The description implies usage by listing what information can be obtained (mesh health, settlement lanes, join instructions), but it does not explicitly state when to prefer this over siblings or mention any alternatives. The context is clear but lacks explicit exclusions or comparisons.

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 full burden. It implies a read-only check but never explicitly states that it does not modify state, nor does it disclose any side effects, input prerequisites, or error behavior. The list of checks provides some context, but important behavioral traits are omitted.

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

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

The description is a single, front-loaded sentence that wastes no words. It lists the key checks efficiently, though it is somewhat telegraphic and could benefit from an explicit verb.

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 and no annotations, the description should explain what the tool returns and potential limitations. It only lists the topics of the check without describing the result format (e.g., booleans, counts) or error cases, leaving the agent to guess.

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 only parameter, 'account', is fully described in the schema with 'XRPL account to check compliance flags,' achieving 100% schema coverage. Under the baseline rule for high coverage, the description doesn't need to add parameter semantics; it adds the specific compliance aspects but those are not parameter-specific.

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

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

The description clearly identifies this as an XRPL compliance check and enumerates specific dimensions (freeze status, clawback capability, auth requirements, transfer restrictions), which distinguishes it from sibling tools like xrpl_token_check or xrpl_account_intel. However, it lacks an explicit verb like 'checks' and doesn't specify the scope of the output, so it's not 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 description provides no guidance on when to use this tool versus other XRPL tools, and there are many siblings with overlapping concerns. The only hint is 'Native MiCA-relevant controls,' which implies a compliance use case, but there are no explicit when-to-use or when-not-to-use instructions.

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 provides minimal behavioral detail: it mentions that bids/asks are returned, but with no annotations, the agent is left unaware of side effects, rate limits, or whether the operation is read-only. The description does not disclose any safety profile or constraints.

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 unnecessary words. It is front-loaded with the tool's identity and scope, making it easy 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 tool with 5 parameters and no schema descriptions or annotations, this description is too sparse. It lacks crucial context about parameter usage, defaults, and return structure, making it incomplete for safe and correct invocation in varying contexts.

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

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

The schema has 5 parameters with 0% description coverage, so the description must compensate. It mentions 'any currency pair' which hints at base/quote currencies, but it does not explain the 'limit' parameter, the role of 'base_issuer'/'quote_issuer', or how currency and issuer parameters relate. This leaves significant ambiguity.

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 as an XRPL native DEX order book providing bids/asks for any currency pair, which distinguishes it from sibling tools like xrpl_nft_offers or xrpl_amm_pools. However, it lacks an explicit verb such as 'retrieves' or 'lists', which slightly reduces precision.

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 no guidance on when to use this tool versus alternatives, nor does it mention any exclusions or preferred contexts. For example, it does not compare itself to xrpl_amm_pools for liquidity pools or xrpl_path_find for payment 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 transparency burden. 'Check' and 'Shows' indicate a read-only operation, and it discloses what data will be returned (locked amounts, conditions, deadlines). It does not explicitly state that no modifications occur, but the wording strongly implies it.

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-loaded with the core action and followed by a clear statement of outputs. Every word earns its place, with no redundant phrasing.

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

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

Given the simple one-parameter schema and no output schema, the description fully explains what the tool does and what it returns. It is sufficient for an agent to select and 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?

Schema description coverage is 100%, so the baseline is 3. The description does not add additional parameter semantics beyond what the schema already provides for 'owner'.

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 the specific verb 'Check' and identifies the resource as 'active XRPL escrows' for an address. It clearly distinguishes from sibling tools like create and monitor by focusing on read-only inspection.

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 use when wanting to view active escrows, but does not explicitly state when to use this tool instead of xrpl_escrow_monitor or other siblings. No alternatives or exclusions are mentioned.

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 mentions locking XRP, setting conditions, and auto-release on fulfillment, which conveys the core mutating action. However, it does not detail side effects, reversibility, prerequisites, or what happens on failure, leaving significant gaps for a state-changing 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 compact, two sentences long, and front-loaded with the key action and resource. Every sentence adds value, explaining the mechanism and the benefit ('no smart contract needed') without redundant 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 create/mutation tool with four parameters and no output schema or annotations, the description provides a general overview but lacks crucial operational details such as the source account, return value, or failure behavior. It is adequate for understanding the high-level purpose but incomplete for safe invocation in complex scenarios.

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 all four parameters with descriptions, so the baseline is 3. The description adds no additional parameter-specific meaning beyond the generic concepts of locking XRP and setting conditions, which do not map explicitly to any 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 states the tool's purpose with a specific verb ('Create') and resource ('XRPL native escrow'). It also provides context ('agent-to-agent deals') and distinguishes it from sibling tools like xrpl_escrow_check and xrpl_escrow_monitor by focusing on creation.

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 creating escrows in agent-to-agent deals, but it does not explicitly state when to use it over alternatives or mention exclusions. There is no comparison to other escrow-related tools, though 'No smart contract needed' hints at a use case advantage.

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 exist, and the description provides no behavioral details—no mention of read-only nature, API calls, potential side effects, or data sources. It's merely a headline.

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 7-word fragment, not a proper sentence. It's concise but under-specifies the tool's purpose and behavior.

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 one parameter and no output schema, the description still leaves the tool's operation and return value entirely unclear. It doesn't convey enough for an agent to select and 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 defines a single 'address' parameter, but the description doesn't mention it or explain what address should be provided. With 0% schema description coverage, the description should compensate but offers no parameter 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?

The description uses the noun phrase 'escrow intelligence' rather than an action verb. It lists output data points but doesn't state what the tool does (e.g., 'retrieve' or 'monitor'). Among siblings (xrpl_escrow_check, xrpl_escrow_create), it doesn't differentiate.

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 vs alternatives. It doesn't mention any context, prerequisites, or when to use it over xrpl_escrow_check or 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?

No annotations are provided, so the description carries the burden. It states what the tool analyzes (obligations, hot wallet balances, compliance) but does not disclose behavioral traits such as whether it is read-only, data refresh characteristics, or any limits. The term 'analysis' implies a read-only operation, but this is not explicit.

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

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

The description is a single sentence that leads with the tool's purpose and lists the key analysis categories. There is no redundant wording or irrelevant information. It earns its place efficiently.

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

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

Given the tool has one parameter, no output schema, and no annotations, the description provides sufficient context by listing the major analysis areas (obligations, hot wallet balances, compliance). It lacks details on return format or interpretation, but for a simple analysis tool, it is 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?

Schema coverage for parameters is 100% (the 'account' field is described). The description does not add additional meaning beyond the schema. Since the schema already documents the parameter adequately, a 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 specifies the tool's function: XRPL gateway/issuer analysis. It enumerates key outputs (total obligations, hot wallet balances, compliance capabilities), which distinguishes it from sibling tools like xrpl_account_intel (general intel) and xrpl_compliance_check (compliance only). The verb 'analysis' is general but the scope is precise.

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: when you need gateway/issuer analysis, use this tool. However, it does not explicitly state when to choose this over alternatives (e.g., xrpl_account_intel or xrpl_compliance_check) or any exclusions. No when-not 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 provided, the description carries the full burden of explaining behavior. It mentions the output is an XML structure and regulatory standards (MiCA/DORA), but does not disclose side effects, return format, or whether it is a read-only operation. This is insufficient for a tool with no annotations.

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 very concise, three short sentences with no wasted words. It briefly states the purpose, target audience, and regulatory readiness. However, it could be more informative without becoming verbose, hence not a 5.

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

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

Given no annotations, no output schema, and only a vague description, the tool is under-specified. It does not clarify what the tool returns (e.g., a static template, a schema, a sample), how to use it, or why it differs from siblings. For a zero-parameter tool, more context about its output and use case is needed.

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 zero parameters, and the schema coverage is vacuously 100%. Per the rubric, a baseline of 4 applies for 0-parameter tools. The description adds no parameter details because none exist, but this 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 indicates the tool provides an ISO 20022 mappable XML structure for RLUSD evidence, but lacks a clear verb (e.g., 'generates', 'returns', 'validates'). It is not a tautology and hints at the resource, but the exact action is vague.

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 on when to use this tool compared to siblings like xrpl_rlusd_integrity or xrpl_compliance_check. The description is purely descriptive and does not state use cases, prerequisites, or 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?

No annotations are provided, so the description must carry the full burden of behavioral disclosure. The word 'scanner' implies a read-only operation, but the description does not state safety, default behavior, return format, pagination, or any limitations. This leaves significant ambiguity.

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. It starts with 'XRPL on-chain object scanner' and immediately enumerates object types. Every word earns its place with no redundancy or filler.

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

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

With no output schema and no annotations, the description should explain return values and default behavior. It does not address what happens when no 'type' is supplied, what the response structure looks like, or whether results are limited. The description is too sparse for a tool that appears to be a general-purpose ledger scanner.

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 'type' parameter with its accepted values, so the baseline is 3. The tool description adds a few synonyms ('MPTs') and groups objects, but does not explain the meaning of omitting the parameter or provide additional semantic 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 clearly identifies the tool as an XRPL on-chain object scanner, listing specific object types (DIDs, AMMs, MPTs, escrows, offers, checks, NFTs) and emphasizing 'native ledger objects.' This distinguishes it as a raw object accessor, though it does not explicitly contrast it with specialized 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?

There is no guidance on when to use this tool versus alternatives like xrpl_amm_pools or xrpl_nft_intel. The description merely states what the tool does, without context, exclusions, or recommended scenarios.

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

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

With no annotations provided, the description carries the burden of behavioral disclosure. It lists the data categories returned (holdings, stats, mutable URIs, transfer fees) and adds a safety note about no smart contract risk. However, it does not explicitly state whether the tool performs read-only operations, the data source or freshness, or any rate limits or authentication 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 extremely concise: one sentence with a colon-separated feature list and a brief second sentence providing a risk note. Every word adds value, and the structure front-loads the main purpose before the optional detail.

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 optional parameter and no output schema, the description provides a comprehensive overview: it states the domain (XRPL NFTs), lists the data categories returned, and offers a comparative benefit. It lacks explicit output format details, but the enumerated features largely substitute for that. It does not explicitly guide selection among sibling tools.

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 of the single optional parameter 'account' with a clear description. The tool description adds context about output categories but does not elaborate on how the account parameter filters results. This meets the baseline expectation when schema coverage is high.

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 (XRPL NFTs under XLS-20) and lists specific capabilities: collection stats, holdings, mutable URIs, and transfer fees. However, the verb 'intelligence' is vague and does not explicitly say whether it queries, analyzes, or reports; it relies on the feature list to convey purpose. It is broader than xrpl_nft_offers but does not explicitly contrast with it.

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 you need NFT data like holdings and stats) and adds context with 'native ledger NFTs — no smart contract risk', hinting at suitability for native NFT queries. However, it provides no explicit 'use this instead of X' guidance or exclusions, and sibling tools like xrpl_nft_offers are not mentioned.

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 must carry the behavioral disclosure burden. It does state that it shows 'all active marketplace offers,' conveying scope and status filtering, but does not mention read-only nature, error handling, pagination, or output format. Adequate but with 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?

Two short sentences, front-loaded with core function, 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 one-parameter lookup with no output schema, the description covers what the tool does and its input. However, the absence of annotations and output schema leaves some ambiguity about return structure, though the simplicity keeps it near-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?

The schema already describes nft_id fully ('NFTokenID to check offers for'), and the description reinforces the purpose without adding syntax or example formats. Baseline 3 given high schema coverage.

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: showing XRPL NFT buy/sell offers for a specific NFToken. It distinguishes itself from siblings like xrpl_nft_intel by focusing on offers rather than broader NFT intelligence.

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 a specific NFToken' implies the tool requires an NFT ID, but there is no explicit guidance on when to use this versus sibling tools such as xrpl_nft_intel or xrpl_dex_orderbook. Context is clear but alternatives are not mentioned.

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 behavior. It lists the informational content returned (price, stats, reserves, base fee), which is helpful, but it does not state that the operation is read-only, whether data is live or cached, or any side effects. For a no-arg overview tool, this is adequate but not 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 a single, front-loaded sentence that conveys all essential information without filler. Every word contributes to understanding the tool's scope, making it highly concise and well-structured.

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 tool with no output schema, the description is reasonably complete. It specifies the major categories of data returned, which sets expectations for the user. However, it could further clarify whether the overview reflects real-time network state or a cached summary, and it does not mention if it is a read-only operation. Still, given the simplicity, it is a solid description.

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 accepts zero parameters, making parameter ambiguity nonexistent. Per the rubric, a baseline of 4 applies when there are no params, and the description adds no unnecessary detail about parameters since there are none.

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 as an XRPL network overview and lists the four key data categories it covers: XRP price, ledger stats, reserve requirements, and base fee. This distinguishes it from siblings by signaling a broad, aggregate view rather than a specialized function, though it lacks an explicit verb like 'get' or 'retrieve'.

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 on when to use this tool versus its many siblings. Given the tool requires no parameters, it is implied to be a general starting point, but the description does not mention alternatives like xrpl_account_intel or xrpl_ledger_data for more specific needs.

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

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

No annotations are provided, so the description carries the full burden. It mentions 'Atomic cross-currency settlement,' which is ambiguous about whether the tool executes settlements or merely finds routes. It fails to disclose side effects, read-only status, or return behavior, leaving the agent uncertain about the tool's impact.

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 very concise, with two sentences that are to the point. No filler words, but the second sentence adds marginal value and some ambiguity, preventing a perfect score.

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 5 parameters and no output schema, the description is incomplete. It does not describe the return format (e.g., a list of paths), limitations, or how the inputs relate to the output. The tool's complexity (cross-currency path finding) demands more context than provided.

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 each parameter described in the schema. The description adds no additional meaning to the parameters beyond the schema, so the baseline of 3 is appropriate.

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

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

The description clearly states the tool's purpose: 'XRPL cross-currency path finding: discover optimal payment routes using DEX + AMM liquidity.' This is a specific verb+resource (discover routes) and distinguishes it from siblings like order book or payment intel 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 implies the tool is used for finding cross-currency payment routes when DEX and AMM liquidity are involved. It gives clear context but does not explicitly mention when to use alternatives or any exclusions, which would make it 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 burden of behavioral disclosure. It mentions topics but does not state whether the tool is read-only, what it returns, or whether it has side effects. The vague term 'intelligence' does not clarify the actual 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?

The description is a single short sentence, which is concise, but it is under-specified. It provides some context but not enough to be useful; it is not so short as to be a tautology, but it does not maximize the value of its length.

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

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

With three optional parameters and no output schema, the description needs to explain what the tool does with those parameters and what kind of output to expect. It does neither, leaving significant gaps in context for an agent to use the tool effectively.

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 0%, so the description must explain the three parameters (amount_xrp, to_currency, from_currency). It does not mention any of them or how they influence the tool's behavior, leaving the agent without any semantic understanding.

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 identifies the tool's domain (XRPL cross-border payments) and lists key topics (routing, ODL, settlement speed, cost), but it lacks a specific verb or explicit action like 'analyze' or 'evaluate'. This makes it hard to distinguish from similar tools like xrpl_path_find, which likely handles routing.

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 no indication of when to use this tool versus alternatives. It does not mention any exclusions or comparisons to sibling tools, leaving the agent without decision-making 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 must carry the burden of behavioral disclosure. It fails to do so: it does not mention what actually happens when joining (e.g., account creation, side effects, reversibility, costs, or what 'Trust Passport' means). The marketing-style language ('1,229 compliance tools', 'gateway to autonomous agent economy') does not provide concrete behavioral details.

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

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

The description is short but not functional conciseness. The second sentence and parts of the first are promotional and do not contribute useful information for an agent. Phrases like 'instant Trust Passport' and 'gateway to the autonomous agent economy' are vague and waste words that could have been used for behavioral or procedural 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 the tool's simplicity (2 params, no output schema), the description is still incomplete because it omits what happens after calling the tool, potential side effects, or expected results. The description focuses on selling the outcome rather than explaining the tool's behavior, leaving the agent without enough context to anticipate consequences.

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% (both parameters are described in the schema). The description adds no extra meaning to the parameters beyond saying 'xrpl_address' is the wallet address. It aligns with the baseline for high schema coverage, providing no additional semantic benefit.

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

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

The description clearly states the tool's purpose: to join OracleNet using an XRPL wallet. It uses a specific verb ('Join') and identifies a distinct resource, differentiating it from sibling tools that are mostly informational or transactional. However, it does not define what 'OracleNet' is, leaving some ambiguity.

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 the use case (joining OracleNet) and does not suggest alternatives, but it lacks explicit guidance on when to use this tool versus others, especially since siblings exist. No exclusions or prerequisites are mentioned, so the usage context is only hinted at.

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 disclosing behavior. It only lists topics and does not indicate whether the tool is read-only, what data it accesses, whether it returns a score, or any side effects. This is a significant gap for a tool with zero annotation support.

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 very short, but it is a sentence fragment rather than a complete, well-structured description. It is not verbose, but it lacks a clear subject-verb structure and feels like a label rather than a functional explanation.

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 absence of output schema and annotations, the description should provide more context about what the tool returns or how to interpret its results. It only lists topic areas, leaving the agent without enough information to understand the tool's functionality or output. The low complexity (0 params) slightly reduces the need, but the vagueness still makes it incomplete.

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 schema provides no parameter details. The description indirectly clarifies the tool's subject matter (RLUSD compliance data), which is the only relevant semantic context. This aligns with the baseline of 4 for tools with no 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 states the tool is about 'RLUSD stablecoin compliance and risk intelligence' and lists specific focus areas (peg health, supply, NYDFS compliance). However, it lacks a clear action verb such as 'retrieve' or 'analyze', making it a noun phrase rather than a specific operation. It does provide some differentiation from siblings like xrpl_rlusd_supply, but the purpose remains vague.

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 no guidance on when to use this tool versus alternatives. It does not mention any specific scenarios, exclusions, or alternative tools, leaving the agent without direction for tool selection.

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 reveals the mechanism (SHA-256 hash anchoring) and scale (86+ transactions) but does not explain what the tool returns when invoked or whether it performs verification. The 'unfalsifiable' claim adds some integrity 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 two sentences with no redundancy. It front-loads the purpose and key differentiator effectively.

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 zero-parameter schema and no output schema, the description covers the essential purpose and mechanism. It could mention return format or interpretation of the audit trail, but overall it is adequate for a read-only informational tool.

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

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

The tool has zero parameters, so parameter semantics are inherently satisfied. The description adds context about the tool's operation but is not required to explain any 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 clearly states the tool anchors SHA-256 hashes of attestation data on the XRPL through 86+ transactions, creating an audit trail. This specific verb and resource context distinguish it from sibling RLUSD 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 implies the tool is for audit trail verification but does not explicitly state when to use it over alternatives like xrpl_rlusd_integrity or xrpl_rlusd_cci. No exclusions or prerequisites are mentioned.

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

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

No annotations are provided, so the description carries the burden. It discloses the composite formula weights (40%/35%/25%) and grade range (A-F), which adds useful behavioral transparency about how the score is derived. However, it does not mention data sources, update frequency, or any limitations of the proprietary score.

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 extremely concise: two sentences, no fluff. It front-loads the purpose and then details the composition and grade, with every sentence providing substantive 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?

Given the tool has no parameters and no output schema, the description adequately explains the purpose and output nature. It covers the composite score weights and grade. A minor gap is not explaining the exact return format (e.g., numeric score versus grade string), but for a no-parameter tool, the description is fairly 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?

The tool has zero parameters, and schema coverage is 100% (empty schema). With no params, the description is not required to explain parameter semantics. The description adds value by explaining what the score measures and how it's composed, which is more than baseline for a parameterless tool.

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

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

The description clearly states it computes a Compliance Confidence Index for RLUSD using a weighted composite score and grades A-F. It identifies a specific resource (RLUSD) and a specific output (composite score/grade), distinguishing it from sibling tools like xrpl_rlusd_integrity or xrpl_rlusd_anchor by its composite proprietary scoring nature.

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 the tool is used to obtain a compliance/confidence score relevant to MiCA, but it does not explicitly state when to use this over alternatives like xrpl_compliance_check or xrpl_rlusd_integrity. The MiCA-relevant note gives some context, but exclusions and alternatives are absent.

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 full responsibility for behavioral disclosure. It hints that the tool returns data (via 'data: ...') but does not disclose whether it is read-only, requires special permissions, or how it behaves in terms of rate limits or response structure. The listed attributes (freshness scoring, confidence levels) are more about data content than behavioral 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?

The description is concise, only two sentences, and front-loads the main idea. It lists several attributes efficiently without unnecessary fluff. However, some terms feel buzzword-like, slightly reducing clarity.

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 and no annotations, the description must be more comprehensive to stand alone. It fails to explain what the agent will receive, how the data is structured, or the meaning of key terms like 'freshness scoring' and 'confidence levels'. For a supposedly enterprise-grade tool, the description is insufficiently informative.

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 input schema is empty with 100% coverage. According to the rubric, a baseline of 4 applies for 0-parameter tools. The description does not need to add parameter semantics since there are none to document.

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 indicates the tool provides RLUSD enterprise-grade data, mentioning several features like freshness scoring and compliance flags. However, it lacks a specific verb (e.g., 'get', 'list', 'query') and doesn't clearly distinguish itself from closely related siblings like xrpl_rlusd_integrity or xrpl_rlusd_anchor. The purpose is clear in a general sense but vague in execution.

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 'Built for regulated institutions' gives a target audience but does not specify when to use this tool versus the many RLUSD-related siblings. There is no mention of alternatives or exclusions, leaving the agent without clear guidance on tool selection.

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 must carry the burden of behavioral disclosure. It mentions 'scanned directly from XRPL trust lines,' which gives some insight into the data source, but it does not state whether the operation is read-only, whether any authentication is needed, what the return format is, or any potential rate limits. This is a significant gap for a tool that performs analysis.

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 key purpose and outputs. Every phrase adds value, and there is no redundancy or unnecessary detail.

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 no parameters and no output schema, the description covers the core purpose and expected results. It could mention whether the analysis is current or historical, and clarify that it is a read-only operation, but for a zero-parameter tool it 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?

The tool has zero parameters, so the baseline is 4. The description adds context about the type of analysis and outputs, which is sufficient. No parameter-specific semantics are needed.

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

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

The description clearly states the tool's function: 'RLUSD holder distribution analysis' with specific outputs (whale concentration, top 10/50 holders, concentration risk score). It also mentions the data source (XRPL trust lines), distinguishing it from sibling tools focused on supply, anchors, or other aspects.

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 analyzing RLUSD holder distribution, but provides no explicit guidance on when to use this tool versus siblings like xrpl_rlusd_supply or xrpl_trust_lines. No exclusions or alternatives are mentioned, leaving the agent to infer context from the tool name.

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. It discloses that the tool auto-flags deviations and mismatches, indicating it's a read-only analysis tool that produces flags. It doesn't describe output format or potential side effects, but as a non-mutating integrity check, this is adequate. Could be more detailed about return values.

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 tool's purpose ('RLUSD multi-source integrity check'), followed by specific sources and outputs. Every word earns its place with no redundancy or 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?

For a zero-parameter tool with no output schema, the description is fairly complete: it explains the input sources, the comparison, and the auto-flagging behavior. It could mention what the agent receives as a result (e.g., a report, a status), but this is a minor gap given the tool's straightforward nature.

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 needs no parameter details. The baseline for 0 params is 4, and the description appropriately focuses on functionality rather than 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 clearly identifies the tool as an RLUSD multi-source integrity check, specifying exactly what it cross-references (DeFiLlama price, XRPL on-chain supply, XRPL DEX liquidity) and what it auto-flags (peg deviations and supply mismatches). This distinguishes it from sibling RLUSD tools like supply or anchor 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 implies usage context: it's a cross-referencing integrity check for detecting mismatches across multiple sources. It gives clear context but doesn't explicitly mention alternatives or exclusion criteria, though the multi-source nature inherently sets it apart from single-source siblings.

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

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

With no annotations, the description carries the full burden. It states that reports are 'parsed and structured,' but does not disclose read-only status, side effects, permissions, or any operational behavior such as data freshness or external calls.

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 front-loaded with the main topic, followed by a list of key contents and a brief processing note. There is no waste.

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 no-parameter tool with no output schema, the description provides the key fields and data source, which is sufficient for a basic understanding. However, it does not specify the return format/structure beyond 'parsed and structured,' and could be more explicit about what the output looks like.

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 there is no need for parameter-level explanation. The baseline of 4 applies since no parameter information is needed.

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

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

The description clearly indicates the tool provides RLUSD transparency reports with specific contents (reserve ratios, outstanding units, reserve values) from Standard Custody. It is explicit about the resource and data scope, but lacks an explicit verb (e.g., 'returns') and does not differentiate from sibling RLUSD 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 implies usage when CPA-attested transparency report data is needed, but it does not provide explicit when-to-use/when-not-to-use guidance or mention alternatives, especially given the many RLUSD-specific sibling tools.

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

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

No annotations are provided, so the description carries the full burden. It discloses the data source (gateway_balances) and tracked metrics (mint/burn, supply changes), but does not explicitly state it is read-only or mention any limitations, rate limits, or whether data is cached. For a query 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 first sentence is information-dense and front-loaded. The second sentence ('The deepest RLUSD supply data available.') is marketing fluff that doesn't add functional value, making it partially wasted. Still, the overall length is appropriate.

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 0-parameter tool with no output schema, the description covers the core capabilities: data source, metrics, and time ranges. It lacks detail on return format or specific use cases, but given the simplicity, it is sufficiently 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?

The tool has 0 parameters and schema coverage is 100% (empty object). Per rubric, 0 parameters baseline is 4. The description adds context about what the tool returns, which is sufficient since there are no parameters to explain.

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 with a specific verb and resource: 'RLUSD live supply intelligence' with concrete metrics (circulating supply, mint/burn tracking, supply changes). It distinguishes from sibling RLUSD tools by emphasizing 'deepest RLUSD supply data available.'

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 supply-related queries (live supply, supply changes) but does not explicitly state when to use this vs alternatives or provide exclusions. No mention of when not to use 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 carries the full burden. It discloses meaningful behavioral traits: HMAC-SHA256 signing, exponential backoff retry, and dead letter queue handling. This goes beyond a generic statement, though it doesn't cover all aspects like authentication prerequisites or return formats.

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 a clear front-loading of the tool's name/domain followed by key features. No wasted words, and the structure is easy to scan.

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 being concise, the functional purpose is incomplete: it doesn't explain what action the agent should perform when invoking the tool (e.g., subscribe, check status, deliver alerts) or what the expected output is. Given no output schema and no parameters, the description needs to be more explicit about the tool's role, which it is not.

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 per the rubric. The description adds no parameter-specific details, but none are needed since there are no inputs to document.

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 identifies a webhook system for RLUSD with specific alert types (depeg, supply mismatch, etc.), which distinguishes it from siblings. However, it lacks a clear verb; it's not explicit whether the tool registers webhooks, sends them, or monitors their status, so the purpose is somewhat vague.

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

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

No explicit guidance on when to use this tool versus the many RLUSD-related siblings (e.g., xrpl_rlusd_anchor, xrpl_rlusd_enterprise). The description implies an enterprise webhook use case but never states when to choose this tool or mentions 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?

No annotations are provided, so the description must carry full behavioral disclosure. It fails to state whether the tool is read-only, whether scores are static or derived from live data, or what limitations exist. The description simply outputs numbers without context.

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

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

The description is a single sentence that front-loads the purpose and provides the key scoring data efficiently. However, the phrase 'The definitive XRPL assessment' is promotional and adds no functional value, preventing a perfect score.

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 output schema, the description explicitly provides the expected output (category scores and overall grade), making it fairly complete. It lacks context on whether the scores are real-time or static, but the core result is clear.

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?

This tool has zero parameters, and the schema is empty, so there is nothing to clarify. According to the rubric, a baseline of 4 is appropriate for 0-parameter tools. The description does not need to add parameter 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?

The description clearly states the tool provides XRPL RWA ecosystem scoring, listing specific category scores and an overall grade. This gives a specific verb+resource and distinguishes it from generic tools. However, it does not explicitly name or differentiate from sibling tools like xrpl_overview or xrpl_compliance_check, so it falls 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?

There is no explicit guidance on when to use this tool versus alternatives. No use cases, exclusions, or prerequisites are mentioned. The phrase 'definitive XRPL assessment' implies authority but provides no actionable direction for the 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 are provided, so the description must carry the full burden of behavioral disclosure. It only lists data categories ('Shows...') without stating whether the tool is read-only, live, or has any side effects, network dependencies, or rate limits. This is a significant gap for a tool with zero annotation support.

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 short sentences, front-loaded with the core purpose ('XRPL network deep state') and efficiently list the relevant network features without any extraneous wording. 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?

Given there is no output schema and no annotations, the description provides a meaningful enumeration of expected data (validators, amendments, fees, load, uptime, native features). It is adequate for a no-parameter tool, though it could mention the output format or that it reflects current network state.

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 schema already fully defines the input structure. The baseline for 0 params is 4, and there is no need for additional parameter explanation in the 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 explicitly states 'XRPL network deep state' and enumerates specific data categories (validators, amendments, fees, load, uptime) plus native features, making it clear what the tool does. This distinguishes it from broader tools like xrpl_overview by focusing on deep state details.

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 use for fetching deep network state but does not explicitly specify when to use it vs alternatives such as xrpl_overview or xrpl_ledger_data, nor does it mention any exclusion criteria. Usage guidance is only implicit through the described data 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?

With no annotations, the description carries the full burden of behavioral disclosure, but it provides none: no return format, data source, update cadence, or operational details. The phrase 'Why XRPL is the fastest settlement' is promotional rather than informative about tool 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?

The description is short and front-loaded with topical keywords, but the second sentence ('Why XRPL is the fastest...') adds no functional value and reads as marketing fluff, so not every sentence earns its place.

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

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

For a zero-parameter, no-output-schema tool, the description is the sole source of context, yet it fails to explain what 'settlement status' concretely returns or how to interpret the mentioned metrics. The listed topics are broad and without specifics, leaving significant 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 tool has zero parameters, so the baseline is 4. There are no parameter semantics to describe, and the description does not need to add parameter-level context.

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 identifies the tool's domain (XRPL settlement lane) and lists topics like fees, speed, RLUSD supply, and liquidity, but lacks a specific verb or operation. It reads more like a product pitch than a tool purpose statement, and does not clearly distinguish it from similar sibling tools such as xrpl_overview or xrpl_rlusd_supply.

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 provided on when to use this tool versus siblings. It implies a general settlement overview use case but never states explicit conditions, exclusions, or alternatives, leaving the agent to infer appropriateness.

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 lists risk factors checked but does not disclose whether the tool is read-only, what data it queries, its output format, or any limitations. The read-only nature is only inferred from '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?

The description is a single, compact sentence that front-loads the purpose and lists key risk categories efficiently. 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?

Despite the simple parameter set, the description omits return value and usage context. An agent would not know what the check returns or when to prefer this over xrpl_compliance_check, leaving the description incomplete for reliable selection and 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?

The schema has two parameters with 0% description coverage, and the description does not explain 'issuer' or 'currency' in terms of format or expected values. While the parameter names are self-evident, the description fails to compensate for the missing schema-level 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 specifies the tool as an XRPL issued currency risk check and lists concrete risk dimensions (issuer trust, supply, freeze capability, compliance), which helps differentiate it from generic account or transaction tools. However, it does not explicitly contrast with sibling tools like xrpl_compliance_check or xrpl_rwa_scoring.

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 guidance on when to use this tool versus alternatives. The phrase 'risk check' implies usage but the description lacks prerequisites, exclusions, or comparison to sibling 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?

There are no annotations to fall back on, so the description carries the full burden. It only mentions the output ('Shows balances, issuers, compliance status'), but does not disclose behavioral traits such as whether it performs a read-only query, any rate limits, or how compliance status is derived. This is a gap for an analysis 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, well-structured sentence that packs in the resource, scope, and output summary. Every word earns its place, with no redundancy or filler.

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

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

For a simple tool with one parameter and no output schema, the description covers the core: what it analyzes (trust lines), the scope (all issued currencies), and what it returns (balances, issuers, compliance status). It could optionally mention that it reads live ledger data or how to interpret compliance status, but it is adequate for basic selection and 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?

The input schema has one parameter 'account' with a generic description, but the tool description adds the meaning that the account is the holder of the trust lines ('an account holds'). This enriches the parameter semantics beyond the schema, even though 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 clearly states the tool performs trust line analysis on XRPL, specifically listing 'all issued currencies an account holds'. It distinguishes from siblings like xrpl_gateway_balances by focusing on the account's trust lines, not gateway balances. The verb 'analysis' and resource 'trust lines' are explicit.

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 when wanting a comprehensive view of an account's issued currencies, but it does not provide explicit when-to-use guidance or exclude alternatives. It does not mention any related tools like xrpl_token_check or xrpl_compliance_check, leaving the agent to infer appropriate use from context.

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