Satoshidata Wallet Intel

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the data source ('satoshidata.ai') and what's returned ('current Bitcoin price snapshot and 24 hour change'), but lacks details on rate limits, authentication needs, error handling, or whether it's a read-only operation. For a tool with zero annotation coverage, this leaves significant gaps in understanding its 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, efficient sentence that front-loads the core functionality ('Return the current Bitcoin price snapshot and 24 hour change') and includes the data source. There is no wasted wording, and it's appropriately sized for a simple tool with no parameters.

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 (0 parameters, no annotations, but has an output schema), the description is minimally adequate. It explains what the tool does and the data source, but with no annotations, it should ideally mention more behavioral aspects (e.g., read-only nature, potential rate limits). The presence of an output schema means return values don't need explanation, but other contextual gaps remain.

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

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

The tool has 0 parameters, and schema description coverage is 100%, so no parameter documentation is needed. The description doesn't add parameter semantics (as there are none), but this is appropriate. A baseline of 4 is applied since the schema fully covers the absence of parameters, and the description doesn't need to compensate.

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: 'Return the current Bitcoin price snapshot and 24 hour change from satoshidata.ai.' It specifies the verb ('Return'), resource ('Bitcoin price snapshot'), and data source ('satoshidata.ai'). However, it doesn't explicitly differentiate from sibling tools like 'onchain_stats' or 'mempool_stats' that might also provide price-related data, preventing a perfect score.

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

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools or contexts where other tools might be more appropriate (e.g., using 'onchain_stats' for broader metrics or 'wallet_summary' for wallet-specific data). The only implied usage is for current price data, but no explicit alternatives or exclusions are stated.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states it 'returns' data, implying a read-only operation, but doesn't mention any behavioral traits such as rate limits, data freshness, error handling, or authentication needs. This leaves gaps for an agent to understand operational 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 that front-loads the core purpose with zero waste. It's appropriately sized for a no-parameter tool and doesn't include redundant 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 0 parameters, 100% schema coverage, and an output schema exists, the description is minimally adequate. However, it lacks context about the data source (satoshidata.ai) reliability, update frequency, or how it compares to sibling tools, which could help an agent use it more 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?

The tool has 0 parameters, and schema description coverage is 100%, so there are no parameters to document. The description appropriately doesn't add unnecessary param details, earning a high baseline score for this dimension.

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

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

The description clearly states the action ('Return') and resource ('current recommended Bitcoin fee estimates from satoshidata.ai'), making the tool's purpose immediately understandable. It doesn't explicitly differentiate from siblings like 'mempool_stats' or 'onchain_stats', which might also provide fee-related data, so it doesn't reach the highest score.

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

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

No guidance is provided on when to use this tool versus alternatives like 'mempool_stats' or 'onchain_stats', which might offer overlapping or complementary fee information. The description lacks context about use cases, prerequisites, or exclusions.

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

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

No annotations are provided, so the description carries the full burden. It describes the return data (mempool size, fee floor, congestion summary) but does not disclose behavioral traits like rate limits, authentication needs, or whether it's a read-only operation. It adds some context but lacks detailed behavioral disclosure.

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

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

The description is a single, efficient sentence that front-loads the purpose without any wasted words. Every part of the sentence contributes directly to explaining what the tool does.

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 0 parameters, an output schema exists, and no annotations, the description is reasonably complete for a simple data-fetching tool. It specifies the data returned, though it could benefit from more behavioral context given the lack of annotations.

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

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

The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description does not add parameter semantics, but this is acceptable given the lack of parameters, aligning with the baseline for 0 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 specific action ('Return') and the exact resources ('current Bitcoin mempool size, fee floor, and congestion summary'), distinguishing it from siblings like bitcoin_price or onchain_stats by focusing on mempool metrics rather than price or blockchain data.

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

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

The description implies usage when mempool data is needed, but does not explicitly state when to use this tool versus alternatives like fees_recommended or onchain_stats. It provides basic context 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 provided, so the description carries the full burden of behavioral disclosure. It mentions returning a 'snapshot' but does not specify if this is a read-only operation, requires authentication, has rate limits, or details the freshness of data. For a tool with zero annotation coverage, this is a significant gap in transparency, though it doesn't contradict any 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 a single, clear sentence: 'Return the current satoshidata.ai on-chain market and network snapshot.' It is front-loaded with the core action and resource, with no wasted words or redundant information. This makes it highly efficient and easy for an agent to parse.

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 0 parameters, 100% schema coverage, and an output schema exists, the description is adequate for a simple data-fetching tool. However, it lacks details on behavioral aspects like data freshness or usage context, which could be important for an agent. The presence of an output schema means return values are documented elsewhere, but the description could still benefit from more context about when and why to use this tool.

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

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

The tool has 0 parameters, and the schema description coverage is 100%, so there are no parameters to document. The description does not need to add parameter semantics, but it correctly implies no inputs are required. A baseline of 4 is appropriate as the schema fully covers the lack of parameters, and the description aligns without adding unnecessary details.

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

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

The description clearly states the tool's purpose: 'Return the current satoshidata.ai on-chain market and network snapshot.' It specifies the verb ('Return') and resource ('on-chain market and network snapshot'), making it easy to understand what the tool does. However, it does not explicitly differentiate from sibling tools like 'mempool_stats' or 'bitcoin_price', which might offer overlapping or related data, preventing a perfect score.

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

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

The description provides no guidance on when to use this tool versus alternatives. With sibling tools such as 'mempool_stats', 'bitcoin_price', and 'wallet_summary', there is no indication of when this specific snapshot is preferred or what unique insights it offers. This lack of context leaves the agent to guess based on tool names alone.

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 states what can be submitted but doesn't describe what happens after submission (e.g., confirmation, processing time, side effects), authentication requirements, rate limits, or error conditions. This is a significant gap for a submission 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, efficient sentence that lists all feedback types without unnecessary words. It's appropriately sized and front-loaded with the core purpose.

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

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

Given the complexity (8 parameters, 1 required), no annotations, and 0% schema coverage, the description is incomplete. It doesn't explain parameter usage, behavioral outcomes, or integration with the output schema. For a submission tool with rich parameters, this leaves significant gaps for an AI agent.

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 schema provides no parameter documentation. The description mentions general feedback types but doesn't explain any of the 8 parameters (like 'feedback_type', 'address', 'confidence', etc.) or their relationships. It adds minimal value beyond the parameter names in the schema.

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

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

The description clearly states the action ('submit') and the types of feedback being submitted (label corrections, missing-label suggestions, data-quality reports, or general feedback). It provides a specific verb and resource scope, though it doesn't explicitly differentiate from sibling tools (which appear unrelated to feedback submission).

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, prerequisites, or context for its application. It lists what can be submitted but offers no usage context, timing, or relationship to other tools in the server.

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 states the action ('Submit') but doesn't explain what happens after submission (e.g., confirmation, cost, rate limits, or irreversible effects). This leaves significant gaps in understanding the tool's behavior beyond the basic operation.

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

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

The description is a single, efficient sentence that directly states the tool's purpose without any wasted words. It is appropriately sized and front-loaded, making it easy to grasp quickly.

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

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

Given the tool has an output schema (which handles return values) and no annotations, the description covers the basic purpose adequately. However, as a submission tool with potential irreversible effects and no behavioral details, it lacks completeness in explaining outcomes or constraints, making it minimally viable but with clear gaps.

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

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

The input schema has 1 parameter with 0% description coverage, so the description must compensate. It mentions 'SHA-256 digest' and 'hash_hex' implicitly, adding some meaning beyond the bare schema. However, it doesn't specify format details (e.g., hex string length or validation), leaving room for improvement in clarifying 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 action ('Submit') and the resource ('SHA-256 digest to White Rabbit's Bitcoin timestamping batch'), making the purpose understandable. However, it doesn't explicitly differentiate from sibling tools like 'timestamp_quote' or 'verify_timestamp', which prevents a perfect score.

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

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

The description provides no guidance on when to use this tool versus alternatives like 'timestamp_quote' or 'verify_timestamp'. It mentions the context ('Bitcoin timestamping batch') but lacks explicit when-to-use or when-not-to-use instructions, leaving usage unclear relative to siblings.

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

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

With no annotations provided, the description carries the full burden. It discloses that this is a read operation ('Return') and specifies the output content (fee details), which helps the agent understand it's a query tool. However, it doesn't mention potential rate limits, authentication needs, or error conditions, leaving some behavioral gaps.

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

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

The description is a single, well-structured sentence that efficiently conveys the tool's purpose and output details without unnecessary words. It is front-loaded with the main action and resource, making it easy to parse.

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 low complexity (0 parameters) and the presence of an output schema (which handles return values), the description is mostly complete. It clearly states what the tool does and what information it returns. However, it could be slightly more complete by mentioning any prerequisites or typical use cases, though this is minor.

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 with 100% schema description coverage, so the schema fully documents the lack of inputs. The description adds value by confirming no parameters are needed and clarifying the tool's purpose, but doesn't need to compensate for any gaps. Baseline for 0 params is 4, as it appropriately addresses the parameter-less nature.

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 specific action ('Return') and resource ('current Bitcoin timestamping preflight quote'), including what information it provides ('fixed service fee and estimated anchor-fee share'). It distinguishes from siblings like 'timestamp_hash' (which presumably hashes data) and 'verify_timestamp' (which verifies timestamps).

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 a quote for timestamping is needed, but does not explicitly state when to use this tool versus alternatives like 'timestamp_hash' or 'verify_timestamp'. It provides some context (preflight quote) but lacks explicit guidance on exclusions or prerequisites.

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

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

No annotations are provided, so the description carries full burden. It mentions the tool returns a 'narrow' state check but doesn't disclose behavioral traits like error handling, rate limits, authentication needs, or what 'narrow' specifically entails (e.g., limited data vs. quick check). This leaves significant gaps for a tool with no annotation coverage.

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 that front-loads the core purpose ('Return a narrow Bitcoin transaction state check') and specifies the possible states. There is no wasted verbiage, 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?

Given the tool's low complexity (one parameter) and the presence of an output schema (which likely covers return values), the description is reasonably complete for its purpose. However, it lacks details on behavioral aspects and parameter semantics, which slightly reduces completeness for a tool with no annotations.

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

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

The schema description coverage is 0%, but the description adds no parameter information beyond what the schema provides (a single 'txid' parameter). It doesn't explain the format, constraints, or meaning of 'txid'. With low coverage, the description fails to compensate, resulting in a baseline score.

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 specific action ('Return') and resource ('Bitcoin transaction state check') with explicit enumeration of possible return states ('unknown, mempool, conflicted, or confirmed'). It distinguishes from siblings like 'tx_verify' or 'verify_timestamp' by focusing on transaction status rather than verification or timestamping.

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 like 'tx_verify' or 'verify_timestamp', nor does it mention prerequisites or exclusions. It simply states what the tool does without contextual usage information.

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 mentions the verification action but doesn't cover critical aspects like error handling, rate limits, authentication needs, or what happens if verification fails (e.g., returns false, throws error). This leaves significant gaps in understanding the tool's 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, efficient sentence that front-loads the core purpose without any wasted words. It directly communicates what the tool does, making it highly concise and well-structured for quick understanding.

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

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

Given the tool's complexity (verification with 4 parameters) and the presence of an output schema (which likely handles return values), the description is minimally adequate. However, with no annotations and low schema coverage, it should provide more behavioral and usage context to be fully complete for safe agent operation.

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 description adds meaningful context beyond the input schema, which has 0% schema description coverage. It explains that parameters relate to verifying payment amount and confirmations, clarifying the purpose of 'min_amount_sats' and 'min_confirmations'. However, it doesn't detail parameter formats (e.g., 'txid' as hex string) or constraints, so it doesn't fully compensate for the schema gap.

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: 'Verify that a Bitcoin transaction paid enough sats to the expected address with enough confirmations.' It specifies the verb (verify) and the resource (Bitcoin transaction), and while it doesn't explicitly differentiate from siblings like 'tx_status' or 'verify_timestamp', the focus on payment verification is distinct enough for clarity.

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

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'tx_status' (which might check transaction status without verification) or 'verify_timestamp' (which could involve timestamp verification), leaving the agent without context 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 of behavioral disclosure. It states the action ('verify') but doesn't describe what verification entails (e.g., checks for blockchain inclusion, returns verification status, or handles errors). It lacks details on permissions, rate limits, or response behavior, which are critical for a verification tool with no annotation coverage.

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 that is front-loaded with the core purpose. There is no wasted wording, and it directly communicates the tool's function without unnecessary elaboration.

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 moderate complexity (verification against blockchain), no annotations, and an output schema (which likely covers return values), the description is minimally adequate. It states what the tool does but lacks details on behavioral aspects and parameter semantics, leaving gaps in understanding how to use it 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?

The description doesn't add meaning beyond the input schema, which has 0% coverage (no parameter descriptions). It mentions 'detached OpenTimestamps proof' but doesn't explain the proof_base64 parameter's format or requirements. With one parameter and low schema coverage, the baseline is 3, as the description doesn't compensate for the lack of schema details.

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

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

The description clearly states the tool's purpose with a specific verb ('verify') and resource ('detached OpenTimestamps proof against the Bitcoin blockchain'). It distinguishes this from siblings like timestamp_hash or timestamp_quote, which likely create timestamps rather than verify them. However, it doesn't explicitly contrast with tx_verify, which might verify Bitcoin transactions rather than timestamp proofs.

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 (verifying timestamp proofs), but provides no explicit guidance on when to use this tool versus alternatives like tx_verify or other timestamp-related tools. It doesn't mention prerequisites, such as needing a pre-existing proof, or exclusions for invalid proof formats.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool returns data, implying a read-only operation, but does not specify aspects like rate limits, authentication needs, error handling, or data freshness. This is a significant gap for a tool with no annotation coverage.

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, clear sentence that directly states the tool's purpose without unnecessary words. It is front-loaded and efficiently conveys the core functionality, making it easy to parse.

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

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

Given the tool has an output schema, the description does not need to explain return values. However, with no annotations and low schema coverage, it lacks details on behavioral traits and parameter semantics. The description is minimal but adequate for a simple query tool, though it could be more 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 description mentions 'a single Bitcoin address,' which aligns with the 'address' parameter in the schema. However, with 0% schema description coverage, the description does not add details like address format or validation rules. It provides basic context but does not fully compensate for the lack of schema documentation.

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

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

The description clearly states the action ('Return') and the resource ('White Rabbit contributor depth and category distribution for a single Bitcoin address'), making the purpose evident. However, it does not explicitly differentiate this tool from sibling tools like 'wallet_detail' or 'wallet_summary', which might also provide wallet-related information, preventing a perfect score.

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

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

The description provides no guidance on when to use this tool versus alternatives. It does not mention any prerequisites, exclusions, or comparisons to sibling tools such as 'wallet_detail' or 'wallet_summary', leaving the agent without context 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 of behavioral disclosure. It states the tool returns data, implying a read-only operation, but lacks details on permissions, rate limits, error handling, or what 'grouped' and 'evidence' entail. For a tool with no annotations, this is insufficient to inform safe and effective use.

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 efficiently conveys the core purpose without redundancy. It's front-loaded with the key action and resource, making it easy to parse, and every word contributes to understanding the tool's function.

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 moderate complexity (address analysis with evidence grouping), no annotations, and an output schema present, the description is minimally adequate. It covers the basic purpose but lacks behavioral details and usage context. The output schema may handle return values, but the description doesn't fully address operational nuances for a tool with no annotation support.

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 description adds meaningful context for the single parameter by specifying it's 'for a single Bitcoin address', clarifying that 'address' refers to a Bitcoin address. With 0% schema description coverage and only one parameter, this adequately compensates, though it doesn't detail format (e.g., address type) or constraints.

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

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

The description clearly states the action ('Return') and the resource ('grouped White Rabbit label evidence and detail for a single Bitcoin address'), making the purpose understandable. It distinguishes from siblings like 'wallet_summary' by specifying 'detail' and 'evidence', but doesn't explicitly contrast with 'wallet_contributors' or 'wallet_trust_safety', which may offer related information.

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 minimal guidance by specifying 'for a single Bitcoin address', implying it's for individual address analysis. However, it offers no explicit when-to-use rules, alternatives (e.g., vs. 'wallet_summary'), prerequisites, or exclusions, leaving the agent to infer usage from context alone.

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 mentions 'premium' and 'chain intelligence summary', hinting at specialized or enhanced data, but fails to clarify key traits like rate limits, authentication needs, data freshness, or whether this is a read-only operation. This leaves significant gaps in understanding the tool's 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, efficient sentence that front-loads the core functionality without any wasted words. It's appropriately sized for the tool's apparent simplicity, 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?

Given the tool has an output schema, the description doesn't need to explain return values, which helps. However, with no annotations and low schema coverage, it lacks details on behavioral traits and parameter nuances. For a tool with siblings like 'wallet_detail', more context on differentiation would improve completeness, but it's minimally adequate.

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

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

The input schema has 0% description coverage, so the description must compensate. It specifies that the tool returns a summary 'for a single Bitcoin address', implying the 'address' parameter is a Bitcoin address, but doesn't add details like format requirements or validation rules. This provides minimal semantic value beyond the schema's structure.

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 ('Return') and resource ('premium White Rabbit chain intelligence summary for a single Bitcoin address'), making it easy to understand what it does. However, it doesn't explicitly differentiate from sibling tools like 'wallet_detail' or 'wallet_contributors', which might offer overlapping or related functionality.

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, such as 'wallet_detail' or 'wallet_contributors', nor does it mention any prerequisites or exclusions. This lack of context could lead to confusion in tool selection among similar 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'return' (implying a read operation) and specifies 'teaser' (suggesting limited or promotional information), but doesn't cover critical aspects like rate limits, authentication needs, error conditions, or what 'teaser' entails (e.g., partial vs. full data). For a tool with zero annotation coverage, this leaves significant gaps in understanding its 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, efficient sentence with zero wasted words. It's front-loaded with the core purpose and includes all essential elements (action, resource, scope) without redundancy. Every word earns its place, 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?

Given the tool's low complexity (one parameter, no nested objects) and the presence of an output schema (which handles return values), the description is minimally adequate. However, with no annotations and incomplete behavioral transparency, it lacks context on operational aspects like rate limits or error handling. It meets basic needs but has clear gaps for safe and effective use.

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 description adds meaningful context for the single parameter by specifying it's for 'a single address,' clarifying that the 'address' input should be a Bitcoin wallet address. With 0% schema description coverage and only one parameter, this compensates well—though it doesn't detail format requirements (e.g., address validation), a baseline of 4 is appropriate given the low parameter count and clear semantic addition.

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

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

The description clearly states the action ('Return'), the resource ('White Rabbit's free Bitcoin wallet trust and safety teaser'), and the scope ('for a single address'). It distinguishes this from sibling tools like wallet_detail or wallet_summary by focusing specifically on trust/safety information rather than general details or summaries. However, it doesn't explicitly contrast with all siblings, so it's not a perfect 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 alternatives like wallet_detail or wallet_summary. It doesn't mention prerequisites, limitations, or specific contexts where this tool is preferred. The agent must infer usage from the purpose alone, which is insufficient for optimal tool selection.

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