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 behavioral traits such as supporting hex/base64 encoding, fetching on-chain data, and returning detailed insights, but lacks information on error handling, rate limits, or authentication needs, which are important 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 appropriately sized and front-loaded, starting with the core purpose. Every sentence adds value, such as input formats and output details, but it could be slightly more streamlined by avoiding redundant phrases like 'powerful tool'.

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

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

Given the complexity (1 parameter with nested objects, no output schema, and no annotations), the description is somewhat complete but lacks details on return values, error cases, or performance considerations. It covers input semantics well but falls short in fully compensating for the missing structured data.

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 significant meaning beyond the input schema, which has 0% coverage. It explains that 'tx' can be a transaction ID or raw data and clarifies encoding options, effectively compensating for the schema's lack of descriptions. However, it doesn't detail the structure of 'args' or provide examples.

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 specific verbs ('decodes and analyzes') and resource ('Bitcoin SV transactions'), distinguishing it from siblings like price checking or ordinal tools. It specifies the comprehensive insights returned, making the function unambiguous.

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

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

The description implies usage by mentioning it accepts transaction IDs or raw data, but does not explicitly state when to use this tool versus alternatives like bsv_explore or other Bitcoin-related tools. No exclusions or clear alternatives are provided, leaving some ambiguity.

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. The description lists endpoint functionalities but lacks critical behavioral details: it doesn't specify whether operations are read-only or mutative, rate limits, authentication requirements, error handling, or response formats. While it mentions 'API health check' and parameter requirements, it fails to provide comprehensive behavioral context needed for safe and effective tool invocation.

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 well-structured with categorized sections (CHAIN DATA, BLOCK DATA, etc.) and bullet points for each endpoint, making it easy to scan. It is appropriately sized for a tool with 19 endpoints, though some redundancy exists (e.g., repeating 'requires X parameter' could be streamlined). Every sentence adds value by clarifying endpoint purposes and parameter mappings, with no wasted text.

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 (19 endpoints, no annotations, no output schema, and nested input schema), the description is partially complete. It excels in documenting endpoints and parameter mappings but lacks behavioral details (e.g., read/write nature, rate limits) and output information. Without annotations or output schema, the description should ideally cover more behavioral aspects to fully guide the agent, leaving gaps in operational context.

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 significant meaning beyond the input schema, which has 0% schema description coverage. It explicitly maps each endpoint to required parameters (e.g., 'block_by_hash: Complete block data via hash (requires blockHash parameter)'), provides optional parameters with defaults (e.g., 'days parameter, default 7'), and clarifies parameter usage across endpoints. This compensates fully for the schema's lack of descriptions, making parameter semantics clear and actionable.

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: 'Explore Bitcoin SV blockchain data using the WhatsOnChain API. Access multiple data types:' followed by a comprehensive categorization of endpoints (CHAIN DATA, BLOCK DATA, etc.). It specifies the verb 'explore' and resource 'Bitcoin SV blockchain data', distinguishing it from sibling tools like bsv_decodeTransaction (decodes transactions) or bsv_getPrice (gets price 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 provides clear context for when to use this tool: for exploring Bitcoin SV blockchain data via the WhatsOnChain API, with a list of specific endpoint types. It explicitly states 'Use the appropriate parameters for each endpoint type and specify 'main' or 'test' network.' However, it does not explicitly mention when not to use it or name alternatives among sibling tools (e.g., using bsv_decodeTransaction for transaction decoding instead of this tool's tx_by_hash).

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 burden. It discloses the tool fetches 'real-time market data' and mentions the source ('reliable exchange API'), which adds useful context. However, it doesn't mention potential limitations like rate limits, authentication requirements, error conditions, or data freshness guarantees that would be important for a price API 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 efficiently structured with two sentences: the first states the core functionality, and the second provides usage context. Every sentence adds value without redundancy, and it's appropriately front-loaded with the primary 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 price retrieval tool with no annotations and no output schema, the description provides adequate purpose and usage context. However, it lacks details about the return format (e.g., numeric value, timestamp, currency pair), error handling, or data source specifics that would be helpful given the absence of structured output documentation.

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 100% and clearly states 'No parameters required - simply returns the current BSV price in USD'. The description reinforces this by not mentioning any parameters, which is appropriate for a zero-parameter tool. The baseline for 0 parameters is 4.

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

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

The description clearly states the specific action ('Retrieves'), resource ('current price of Bitcoin SV (BSV) in USD'), and data source ('from a reliable exchange API'). It distinguishes itself from siblings by focusing on real-time price data rather than transaction decoding, exploration, or ordinal-related functions.

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 clear context for when to use this tool ('calculating transaction values, monitoring market conditions, or converting between BSV and fiat currencies'). However, it doesn't explicitly state when not to use it or name specific alternatives among the sibling tools for similar price data 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It describes the return data ('complete inscription data including content type, file information, inscription origin, and current status'), which is helpful. However, it lacks details on error handling, rate limits, authentication needs, or performance characteristics, leaving gaps for a mutation-free but data-rich 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 front-loaded with the core purpose, followed by return details and usage context in two efficient sentences. Every sentence adds value without redundancy, making it appropriately sized 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 (data retrieval with detailed output), no annotations, and no output schema, the description is moderately complete. It outlines the purpose and return data but lacks specifics on output structure, error cases, or operational constraints, which are important for a tool with rich data returns.

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 compensate. It adds meaning by specifying the parameter as 'outpoint' and implying its critical role in identifying the inscription, though it does not detail the format beyond what the schema provides ('Outpoint in format 'txid_vout''). For a single parameter tool, this provides adequate context, but not exhaustive detail.

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

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

The description clearly states the specific action ('retrieves detailed information') and resource ('about a specific ordinal inscription by its outpoint'), distinguishing it from siblings like ordinals_searchInscriptions (searching) or ordinals_getTokenByIdOrTicker (tokens). It provides a precise verb+resource combination that leaves no ambiguity about the tool's function.

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

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

The description explicitly states when to use this tool ('useful for verifying NFT authenticity or retrieving metadata about digital artifacts'), providing clear context. However, it does not specify when NOT to use it or name alternatives (e.g., ordinals_searchInscriptions for broader searches), which prevents a perfect score.

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 the tool retrieves detailed information and returns complete token data, which implies a read-only operation, but doesn't explicitly state whether it's safe, requires authentication, has rate limits, or what happens on errors. For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior and 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 appropriately sized with two sentences: the first states the purpose and parameters, and the second provides usage context. It's front-loaded with the core functionality, and every sentence adds value without redundancy. However, it could be slightly more structured by explicitly listing return fields or constraints.

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 (1 parameter with nested objects, no output schema, no annotations), the description is moderately complete. It covers the purpose, parameters, and usage context but lacks details on return values, error handling, or behavioral traits. Without an output schema, it should ideally explain what 'complete token data' includes, but it doesn't. It's adequate for basic use but has clear gaps for full agent understanding.

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 meaning by specifying that the tool retrieves information 'by its ID or ticker symbol,' which aligns with the two properties in the input schema (id and tick). However, with 0% schema description coverage, the schema provides no descriptions for these parameters. The description compensates somewhat by indicating what the parameters represent, but it doesn't detail formats (e.g., ID as outpoint) or usage rules (e.g., exclusive OR). Baseline is 3 as it adds some value but doesn't fully compensate for the coverage 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: retrieving detailed information about a specific BSV-20 token by ID or ticker symbol. It specifies the resource (BSV-20 token) and action (retrieving detailed information), and distinguishes it from siblings like ordinals_getInscription or ordinals_marketListings by focusing on token data rather than inscriptions or market listings. However, it doesn't explicitly differentiate from all siblings (e.g., bsv_explore might also retrieve 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 context by stating it's 'useful for verifying token authenticity or checking supply metrics,' which suggests when to use it. However, it doesn't provide explicit guidance on when to use this tool versus alternatives like bsv_explore or ordinals_searchInscriptions, nor does it specify prerequisites or exclusions. The guidance is present but not comprehensive.

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 that the tool 'retrieves' listings and includes details like prices and seller info, but fails to describe critical behaviors such as pagination handling (implied by 'offset' and 'limit' parameters), rate limits, authentication requirements, error conditions, or the structure of returned results. For a tool with 14 parameters and no output schema, this is a significant gap.

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

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

The description is appropriately sized at three sentences, front-loaded with the core purpose. Each sentence adds value: the first states the action and scope, the second details asset types, and the third specifies result contents. There's no redundant information, and it's structured for quick comprehension.

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 (14 parameters, nested objects, no annotations, no output schema), the description is incomplete. It covers the purpose and result types but lacks essential context such as behavioral traits (e.g., pagination, errors), detailed parameter guidance, and differentiation from siblings. Without an output schema, the description should ideally explain return values, but it only mentions them superficially ('listing prices, details about the assets, and seller information').

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%, meaning all 14 parameters lack descriptions in the schema. The description compensates partially by mentioning 'flexible filtering' and listing the types of results included (prices, asset details, seller information), which hints at parameters like 'minPrice', 'maxPrice', and 'tokenType'. However, it doesn't explain the semantics of most parameters (e.g., 'id', 'origin', 'pending'), leaving many undocumented. Baseline is 3 due to some compensation but incomplete 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 purpose: 'Retrieves current marketplace listings for Bitcoin SV ordinals with flexible filtering.' It specifies the resource (marketplace listings) and the action (retrieves), and mentions support for multiple asset types. However, it doesn't explicitly differentiate from sibling tools like 'ordinals_marketSales' or 'ordinals_searchInscriptions', 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. It mentions 'flexible filtering' but doesn't specify scenarios where this tool is preferred over siblings like 'ordinals_marketSales' (which might retrieve sales history) or 'ordinals_searchInscriptions' (which might search inscriptions without marketplace context). No explicit when/when-not instructions or named alternatives are 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 full burden for behavioral disclosure. It mentions the tool 'retrieves recent sales data' and 'provides insights into market activity,' which implies a read-only operation, but doesn't explicitly state this is a query tool with no side effects. It also doesn't disclose rate limits, authentication requirements, data freshness, or pagination behavior (though pagination parameters exist in the schema). The description adds some behavioral context about what data is returned but leaves significant 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 appropriately sized with three sentences that each add value: first states core purpose, second explains what insights are provided, third describes filtering capabilities and use cases. It's front-loaded with the main purpose and avoids unnecessary repetition. Some minor wordiness exists ('to help analyze market trends and track specific token sales' could be tighter).

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 (8 parameters in a nested structure, no output schema, no annotations), the description provides basic purpose and filtering context but is incomplete. It doesn't explain the return format, pagination behavior, default tokenType, or what 'recent' means temporally. For a sales data retrieval tool with rich filtering options, more contextual information would be helpful despite the lack of output schema.

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 filtering 'by token ID, ticker symbol, or seller address' which maps to three of the eight parameters (id, tick, address). However, with 0% schema description coverage, the description doesn't compensate for the undocumented parameters (dir, limit, offset, pending, tokenType). The description adds some semantic value for three parameters but leaves five completely undocumented beyond the schema 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 'retrieves recent sales data for BSV-20 and BSV-21 tokens on the ordinals marketplace' with specific verbs ('retrieves', 'provides insights') and resources ('sales data', 'BSV-20 and BSV-21 tokens'). It distinguishes from siblings like ordinals_marketListings (which likely shows current listings rather than completed sales) and ordinals_getTokenByIdOrTicker (which retrieves token metadata rather than sales data), though the differentiation could be more 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 context by stating it 'helps analyze market trends and track specific token sales' and mentions filtering capabilities, but doesn't explicitly state when to use this tool versus alternatives like ordinals_marketListings or bsv_getPrice. It provides some guidance through the filtering mention but lacks explicit when/when-not instructions or named 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 full burden but offers minimal behavioral disclosure. It mentions 'results include detailed information' but doesn't specify what that includes, format, or any limitations. No information about rate limits, authentication needs, error conditions, or pagination behavior beyond what's implied in the schema.

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

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

Three sentences with zero waste - first states purpose, second enumerates capabilities, third provides usage context. Well-structured and appropriately sized for a search tool with multiple parameters. Could be slightly more front-loaded with explicit sibling differentiation.

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 complex search tool with 9 nested parameters, 0% schema coverage, no annotations, and no output schema, the description is inadequate. It doesn't explain return format, error handling, performance characteristics, or provide examples. The 'detailed information' claim is too vague for an agent to understand what to expect.

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%, but the description compensates by listing supported filter criteria: 'address, inscription content, MIME type, MAP fields, and other parameters.' This provides meaningful context about what the args object contains, though it doesn't explain individual parameter purposes or relationships. The description adds value beyond the bare schema but doesn't fully document all 9 nested 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 'searches for Bitcoin SV ordinal inscriptions using flexible criteria' with specific verb+resource. It distinguishes from siblings like ordinals_getInscription (specific retrieval) and ordinals_marketListings (market-focused), though not explicitly named. However, it doesn't fully differentiate from potential general search tools like bsv_explore.

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 ('ideal for discovering NFTs and exploring the ordinals ecosystem') but doesn't explicitly state when to use this tool versus alternatives. It mentions 'powerful search tool' but provides no guidance on when to choose it over other search or retrieval tools in the sibling list.

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 effectively describes key behaviors: all parameters are required, returns converted data as a string, and explains binary representation. It doesn't mention error handling, performance characteristics, or side effects, but covers essential operational 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 well-structured and appropriately sized. It starts with a clear purpose statement, provides usage context, documents parameters with examples, and adds important notes. Every sentence adds value, and the information is front-loaded with the most important details first.

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 data conversion tool with no annotations and no output schema, the description does an excellent job covering purpose, parameters, and basic behavior. The examples are particularly helpful. It could be more complete by mentioning error cases or performance considerations, but it provides sufficient context for 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 schema description coverage is 0% (no parameter descriptions in schema), so the description fully compensates. It clearly documents all three parameters, their required status, valid values for 'from' and 'to' (utf8, hex, base64, binary), and provides multiple examples showing exactly how to use them together.

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 ('Converts') and resource ('data between different encodings'), and distinguishes it from sibling tools by focusing on data format transformation rather than blockchain or ordinal operations. The examples further clarify the exact 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 clear context about when to use the tool ('useful for transforming data formats when working with blockchain data, encryption, or file processing'), but doesn't explicitly state when NOT to use it or name specific alternatives among sibling tools. The guidance is helpful but not exhaustive.

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