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 a price ('$3.00'), which is useful cost information. However, it doesn't disclose critical behavioral traits: whether this is a read-only analysis or has side effects, what permissions are needed, rate limits, processing time, or what happens with incomplete lease terms. The description is insufficient for a mutation-sensitive 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 appropriately concise with three clear sections: purpose statement, args explanation, and returns statement. The price information is efficiently included. However, the 'Args' and 'Returns' labels are redundant since structured fields exist, and the description could be more front-loaded with critical behavioral 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 1 parameter with 0% schema coverage and no annotations, but with an output schema present, the description is moderately complete. The output schema means return values don't need explanation. However, for a tool that analyzes complex lease terms, the description should provide more guidance on input expectations, analysis methodology, and limitations to be 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?

Schema description coverage is 0%, so the description must compensate. It mentions 'lease_terms: Lease details including rent, term, location, size' which provides some semantic context about expected fields. However, with 1 parameter that's a nested object with additionalProperties, this minimal guidance is inadequate - it doesn't specify required vs optional fields, data formats, or validation rules.

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: 'Analyze commercial lease terms and market comparison.' It specifies the verb ('analyze'), resource ('commercial lease terms'), and scope ('market comparison'). However, it doesn't differentiate from sibling tools, which appear to be unrelated financial/crypto tools rather than direct alternatives.

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. The description doesn't mention prerequisites, appropriate contexts, or exclusions. While sibling tools seem unrelated, the description offers no usage context beyond the basic purpose statement.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the tool returns a quote and route but doesn't specify if this is a read-only operation, if it requires authentication, rate limits, or any side effects. The description is minimal and lacks critical behavioral context for a tool that could involve financial transactions.

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 followed by parameter and return details. The 'Price: $0.50' line is slightly extraneous but not wasteful. Overall, it's efficient with minimal 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?

Given the tool's complexity (cross-chain transfers) and lack of annotations, the description is moderately complete but has gaps. It explains parameters and returns, and an output schema exists, so return values needn't be detailed. However, it misses behavioral aspects like safety, permissions, or error handling, which are crucial for such operations.

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 lists all parameters with brief explanations, adding meaning beyond the input schema, which has 0% description coverage. It clarifies that 'recipient' is optional and different from default, and specifies the purpose of each parameter. However, it doesn't provide format details (e.g., chain identifiers, token address formats), leaving some 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 states the tool's purpose with specific verbs ('Get bridge quote and route') and resources ('cross-chain token transfer'), distinguishing it from sibling tools that focus on analysis, trading, or other blockchain operations. It precisely defines what the tool does without restating the name.

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 'build_transaction' or 'get_batch_quote' for similar operations. It lacks context about prerequisites, such as whether the tool is for planning versus execution, or any exclusions for specific 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 full burden. It discloses key behaviors: the tool builds an unsigned transaction with gas estimates, handles native and ERC-20 tokens, and has a cost ('Price: $0.15'). However, it lacks details on permissions, rate limits, error conditions, or what 'ready for signing' entails (e.g., format). It doesn't contradict annotations, but gaps remain for a mutation 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 well-structured and front-loaded with the core purpose. The Args/Returns sections efficiently document parameters and output. The 'Price' line adds necessary context. It's slightly verbose but each sentence earns its place, with no 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 complexity (transaction building with 5 params), no annotations, but an output schema exists (implied by 'Returns'), the description is reasonably complete. It covers purpose, parameters, output, and cost. However, for a mutation tool, it could better explain behavioral aspects like side effects or error handling to fully compensate for missing annotations.

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

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

Schema description coverage is 0%, so the description must compensate. It adds meaningful semantics for all 5 parameters: explaining 'from_address' as sender, 'to_address' as recipient, 'value' in token units/wei, 'chain' as blockchain network, and 'token_address' as optional for ERC-20 vs. native. This clarifies beyond schema titles, though it could specify formats (e.g., hex for addresses).

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: 'Build a transaction object ready for signing.' It specifies the action (build), resource (transaction object), and outcome (ready for signing). However, it doesn't explicitly differentiate from sibling tools like 'bridge_tokens' or 'manage_approvals', which might also involve transaction building in different contexts.

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 prerequisites (e.g., needing wallet access), exclusions, or comparisons to siblings like 'bridge_tokens' for cross-chain transfers or 'manage_approvals' for token approvals. Usage is implied but not explicitly 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 the tool creates a wallet with 'managed keys,' implying a write operation and key management, but lacks details on permissions, security implications, rate limits, or what 'management details' entail. The price mention adds some context but is insufficient for a mutation 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 well-structured and front-loaded with the core purpose, followed by parameter details, return information, and price. Each sentence serves a clear purpose, with no wasted words. However, the inclusion of 'Price: $1.00' as a separate line slightly disrupts flow, though it's still concise.

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 (creating a wallet with managed keys), no annotations, and an output schema (implied by 'Returns'), the description is moderately complete. It covers purpose and parameters but lacks behavioral details like security or operational constraints. The output schema should handle return values, but the description doesn't fully compensate for missing annotation 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 includes an 'Args' section that lists parameters ('agent_name' and 'agent_type') and provides semantic details: 'agent_name' is a 'Name identifier for the agent,' and 'agent_type' includes options ('trading, payment, defi, general'). With 0% schema description coverage, this adds meaningful value beyond the bare schema, though it doesn't fully explain all aspects like default values 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 tool's purpose: 'Create a new wallet for an AI agent with managed keys.' It specifies the verb ('Create'), resource ('wallet'), and target ('AI agent'), distinguishing it from sibling tools like 'create_instant_agent_wallet' by emphasizing 'managed keys.' However, it doesn't explicitly differentiate from that sibling beyond the name, 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 provides no guidance on when to use this tool versus alternatives, such as 'create_instant_agent_wallet' or other wallet-related tools. It mentions a price ('Price: $1.00'), which hints at cost considerations, but offers no explicit context, prerequisites, or exclusions for usage.

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 key behavioral traits: the wallet is 'temporary' with '24-hour validity' and has a 'Price: $0.50', which are crucial for cost and time awareness. However, it doesn't cover permissions, rate limits, or what happens after expiration.

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?

Front-loaded with the core action, followed by structured sections for Args, Returns, and Price. Each sentence earns its place, but the 'Args' section could be integrated more smoothly, and there's minor redundancy in listing options.

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 (1 parameter, no annotations, but with output schema), the description is fairly complete. It explains the purpose, parameter semantics, return value, and cost. The output schema likely covers return details, so no need to elaborate further. However, it lacks error handling or prerequisite info.

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 meaningful semantics: 'purpose' is explained with options 'trading, testing, payment', which clarifies beyond the schema's generic 'Purpose' title and 'general' default. This covers the single parameter well, though it doesn't mention the default value.

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

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

The description clearly states the action ('create a temporary agent wallet') and resource ('wallet'), with the qualifier 'instantly' and 'for quick operations' providing useful context. It distinguishes from the sibling 'create_agent_wallet' by emphasizing speed and temporariness, though it doesn't explicitly contrast them.

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

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

No explicit guidance on when to use this tool versus alternatives like 'create_agent_wallet' or other wallet-related tools. The mention of 'quick operations' and '24-hour validity' implies transient use cases but lacks clear when/when-not directives 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?

No annotations are provided, so the description carries the full burden. It mentions 'AI-powered' and 'Price: $0.50,' which hints at computational cost and potential external API usage, but lacks critical behavioral details like rate limits, authentication requirements, error handling, or whether it's read-only or mutative.

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, with the core purpose stated first. However, the 'Price: $0.50' line, while useful, could be integrated more smoothly, and the structure with separate 'Args' and 'Returns' sections is clear but slightly verbose for such brief content.

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 (AI-powered analysis with nested input objects), lack of annotations, and 0% schema coverage, the description is incomplete. It mentions output ('Fraud score, risk indicators, and recommendations'), which is helpful since an output schema exists, but fails to address input requirements or behavioral constraints adequately.

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%, with one parameter ('transaction_data') documented only as an object with 'additionalProperties: true.' The description adds minimal semantics by naming it 'Transaction details to analyze' but doesn't specify required fields, formats, or examples, leaving the parameter largely undefined.

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 as 'AI-powered fraud detection for transactions,' which is a specific verb ('detect') + resource ('fraud') combination. However, it doesn't differentiate from sibling tools like 'get_credit_risk_score' or 'run_compliance_check,' which might have overlapping financial risk assessment domains.

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. The description mentions analyzing 'transactions' but doesn't specify context (e.g., payment processing, blockchain transactions) or exclusions, leaving the agent to infer usage from the tool name 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 full burden for behavioral disclosure. It mentions scanning and reporting but lacks critical details: whether this is a real-time or cached scan, execution time, rate limits, authentication needs, data freshness, or potential costs beyond the stated $1.00 price. For a financial tool with zero annotation coverage, this leaves significant 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 efficiently structured with a clear purpose statement followed by Args and Returns sections. Every sentence earns its place, though the 'Price: $1.00' line could be integrated more smoothly. It's appropriately sized for a 2-parameter tool 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 complexity (financial arbitrage scanning), no annotations, 0% schema coverage, but presence of an output schema, the description is minimally adequate. The output schema means return values don't need explanation, but critical behavioral aspects (scan methodology, limitations, cost implications) are missing. For a paid tool with financial implications, more context would be expected.

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 lists both parameters (chains, min_profit_pct) and provides basic semantic context: chains are 'to scan for arbitrage' and min_profit_pct is 'minimum profit percentage to report'. However, it doesn't specify chain format (names, IDs), profit calculation methodology, or whether percentages are absolute or relative. The description adds value but doesn't fully compensate for the schema 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 with a specific verb ('Scan') and resource ('cross-chain arbitrage opportunities'), making it immediately understandable. It distinguishes itself from siblings by focusing on arbitrage detection rather than other financial operations like analysis, bridging, or portfolio management. However, it doesn't explicitly differentiate from potential similar tools (none present in siblings).

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

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, ideal scenarios, or limitations. While siblings include related tools like get_batch_quote or get_trade_signals, there's no explicit comparison or context for choosing this specific arbitrage scanner.

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 states the tool returns 'Prices and metadata' and includes a cost ('Price: $0.25'), which adds useful context. However, it lacks critical behavioral details: whether it's read-only, rate limits, error handling, authentication needs, or what 'metadata' entails. For a financial tool with zero annotation coverage, this is insufficient.

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: the first sentence states the core purpose, followed by structured sections for Args and Returns. The cost note is concise. However, the 'Price: $0.25' line feels tacked on without integration into usage context, slightly reducing efficiency.

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 2 parameters, 0% schema coverage, no annotations, but an output schema exists, the description is moderately complete. It covers purpose and parameters but lacks behavioral transparency (e.g., safety, limits) and detailed usage guidelines. The output schema handles return values, so description needn't explain returns, but gaps in other areas keep it from being fully adequate.

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

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

Schema description coverage is 0%, so the description must compensate. It lists parameters ('tokens', 'chain') and explains 'tokens' as 'List of token addresses to quote' and 'chain' as 'Blockchain network', adding basic semantics. However, it doesn't specify format (e.g., token address standards), chain options beyond the default 'ethereum', or validation rules. With 2 parameters and low schema coverage, this provides marginal value.

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

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

The description clearly states the tool's purpose: 'Get quotes for multiple tokens in a single request.' It specifies the verb ('Get quotes') and resource ('multiple tokens'), and distinguishes it from sibling tools like 'get_token_price' by emphasizing batch capability. However, it doesn't explicitly contrast with 'get_token_price' to fully differentiate usage scenarios.

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 'get_token_price' or other sibling tools. It mentions batch capability but doesn't specify thresholds (e.g., 'use for 2+ tokens') or exclusions. Without explicit when/when-not instructions, the agent lacks clear usage 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 full burden for behavioral disclosure. It mentions the price ('Price: $0.50'), which is useful context about cost implications. However, it doesn't describe rate limits, authentication needs, error conditions, or what happens with invalid inputs. The description states what the tool does but lacks operational details an agent would need.

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 well-structured with clear sections (purpose, args, returns, price). Each sentence earns its place, though the 'Price: $0.50' could be integrated more smoothly. It's front-loaded with the core purpose, followed by necessary details without redundancy.

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

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

Given 2 parameters with 0% schema coverage and an output schema present, the description does a reasonable job. It explains parameters well and states the return type ('Correlation coefficients between all token pairs.'), though the output schema would provide exact structure. However, as a data analysis tool with no annotations, it should ideally mention data sources, accuracy limitations, or computational constraints for better completeness.

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

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

Schema description coverage is 0%, so the description must compensate. It successfully explains both parameters: 'tokens: List of token addresses or symbols to analyze' and 'timeframe: Analysis period. Options: 1d, 7d, 30d, 90d.' This adds crucial meaning beyond the bare schema, including format details and valid options. The default value for timeframe is mentioned in the schema but not the description, keeping this from a perfect 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 tool's purpose: 'Get correlation matrix between multiple tokens.' It specifies the verb ('Get') and resource ('correlation matrix'), and clarifies it analyzes relationships between tokens. However, it doesn't explicitly differentiate from sibling tools like 'get_risk_metrics' or 'get_trading_signal' that might also involve token analysis.

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 prerequisites, appropriate contexts, or comparisons to sibling tools like 'get_risk_metrics' or 'optimize_portfolio' that might offer overlapping functionality. The price information hints at a paid service but doesn't clarify usage 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?

No annotations are provided, so the description carries the full burden. It mentions 'Price: $2.00', which adds useful context about cost, but doesn't disclose other behavioral traits like rate limits, authentication needs, data sources, or potential side effects. For a tool that likely involves sensitive financial data, 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 and front-loaded with the core purpose. The Args and Returns sections are structured clearly, and the Price note is concise. However, the 'Args' and 'Returns' labels are redundant with the schema and output schema, slightly reducing efficiency.

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 (financial risk assessment), no annotations, and an output schema (implied by 'Returns'), the description is moderately complete. It covers purpose, parameters, returns, and cost, but lacks behavioral details like error handling or data freshness. With an output schema, it doesn't need to explain return values deeply, but more context would help.

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 explaining 'entity_id' as an 'Identifier for the entity (wallet, business ID, etc.)' and 'entity_type' with 'Options: individual, business, dao', which clarifies beyond the bare schema. However, it doesn't detail format constraints or examples, leaving some 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 states the tool's purpose: 'Get credit risk assessment for individuals or businesses.' It specifies the verb ('Get') and resource ('credit risk assessment'), and distinguishes the target entities. However, it doesn't explicitly differentiate from the sibling tool 'get_wallet_risk_score', which might be related, 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. It mentions 'individuals or businesses' but doesn't specify scenarios, prerequisites, or exclusions. Given the sibling tool 'get_wallet_risk_score', there's no clarification on how this differs, leaving usage ambiguous.

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 the tool returns 'Liquidity depth, top pools, and slippage estimates,' which gives some behavioral insight into outputs. However, it lacks critical details like whether this is a read-only operation, potential rate limits, authentication needs, or error conditions. The 'Price: $0.20' hint suggests a paid service but doesn't clarify billing implications.

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 front-loaded with the core purpose, followed by Args and Returns sections. It's concise with no wasted sentences, though the 'Price: $0.20' line could be integrated more smoothly. Overall, it efficiently communicates key information in a compact format.

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 2 parameters, 0% schema coverage, no annotations, but an output schema exists, the description is moderately complete. It covers the purpose, parameters, and return types, but lacks behavioral details (e.g., safety, costs, errors). The output schema likely handles return values, reducing the burden, but gaps remain for a tool with financial implications.

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 explaining 'token_address' as 'The token contract address (0x...)' and 'chain' with options 'ethereum, base, polygon, bsc,' which clarifies beyond the schema's generic titles. However, it doesn't cover all semantic nuances (e.g., format validation for addresses, default behavior for 'chain'). With 2 parameters and partial compensation, a baseline 3 is appropriate.

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

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

The description clearly states the tool's purpose: 'Get DEX liquidity analysis for a token across major exchanges.' It specifies the action ('Get'), resource ('DEX liquidity analysis'), and scope ('across major exchanges'). However, it doesn't explicitly differentiate from sibling tools like 'get_token_metadata' or 'get_token_price', which reduces it from 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. It doesn't mention any prerequisites, exclusions, or comparisons to sibling tools (e.g., 'get_token_price' for price data instead of liquidity analysis). The only implicit context is the token address and chain parameters, but no explicit usage rules are given.

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 return structure and price ('$0.40'), which adds some context. However, it lacks critical details such as rate limits, authentication requirements, error handling, or whether the analysis is real-time or cached. For a paid tool with no annotations, this leaves significant gaps in understanding its operational 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 well-structured and concise. It starts with a clear purpose statement, lists parameters with brief explanations, specifies the return format, and ends with pricing information. Every sentence adds value without redundancy, and the information is front-loaded 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 complexity (AI-powered analysis with multiple factors), no annotations, and an output schema (implied by 'Returns'), the description is fairly complete. It covers parameters thoroughly and outlines the return structure. However, it lacks details on behavioral aspects like cost implications or usage limits, which are important for a paid tool, preventing a perfect score.

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 fully compensate. It does so effectively: it explains all four parameters with clear semantics—'pair' as the currency pair with examples, and the three boolean flags specifying what to include in the analysis. This adds substantial meaning beyond the bare schema, making the parameters well-understood.

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

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

The description clearly states the tool's purpose: 'Get AI-powered forex currency pair sentiment analysis.' It specifies the verb ('Get') and resource ('forex currency pair sentiment analysis'), making the function unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'get_sentiment_analysis' or 'get_stock_sentiment,' which is why it doesn't achieve 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 like 'get_sentiment_analysis' or 'get_stock_sentiment,' nor does it specify prerequisites, exclusions, or contextual triggers for its use. The only implicit guidance is the parameter descriptions, which are insufficient for usage decisions.

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

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

No annotations are provided, so the description carries the full burden. It discloses that the tool provides 'real-time' data and mentions pricing ('Price: $0.10') and a promotional offer ('FIRST CALL FREE'), which are useful behavioral traits. However, it lacks details on rate limits, error handling, data freshness, 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 well-structured with clear sections (purpose, args, returns, price) and uses bullet-like formatting. It's appropriately sized, though the promotional pricing note could be considered slightly extraneous. Every sentence adds value, with no wasted words.

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

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

Given the tool's moderate complexity (single parameter, real-time data query), the description is reasonably complete. It explains the parameter semantics thoroughly, and since an output schema exists, it doesn't need to detail return values. However, it could better address behavioral aspects like rate limits or data sources for a fully complete picture.

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 fully documents the single parameter 'chains' by listing all options (ethereum, base, polygon, bsc, arbitrum, optimism) and specifying the default behavior ('Defaults to all supported chains'), adding clear meaning beyond the bare 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 tool's purpose with a specific verb ('Get') and resource ('real-time gas prices across multiple blockchain networks'). It distinguishes itself from siblings like get_token_price or get_multi_chain_balance by focusing specifically on gas prices rather than token prices, balances, or other metrics.

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. While it's clear what the tool does, there's no mention of when it's appropriate (e.g., before submitting transactions) or when other tools might be better suited (e.g., get_batch_quote for quotes, build_transaction for transaction building).

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 queries balances across networks and includes a price ('Price: $0.50'), which adds some context. However, it lacks critical behavioral details such as rate limits, authentication requirements, error handling, or whether this is a read-only operation (implied but not stated). The description is minimal beyond the basic functionality.

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. The 'Args' and 'Returns' sections are structured clearly, and the 'Price' note is concise. There's minimal waste, though the formatting could be slightly more polished (e.g., bullet points). Overall, it's efficient and 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 moderate complexity (3 parameters, no annotations, but with an output schema), the description is somewhat complete. It covers the purpose, parameters, returns, and price, but lacks behavioral context like permissions or limitations. The output schema exists, so the description doesn't need to detail return values, but it could benefit from more operational guidance to fully inform the 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 description must compensate. It adds meaning by explaining 'wallet_address' as 'The wallet address to check (0x...)', 'chains' as 'List of chains to query. Defaults to all supported chains.', and 'include_tokens' as 'Whether to include ERC-20 token balances.' This clarifies parameter purposes beyond the schema's titles. However, it doesn't specify chain identifiers or token details, leaving gaps in parameter 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 clearly states the tool's purpose: 'Get multi-chain wallet balance across 7+ EVM networks.' It specifies the verb ('Get'), resource ('wallet balance'), and scope ('across 7+ EVM networks'), which is specific and actionable. However, it doesn't explicitly differentiate from sibling tools like 'get_wallet_risk_score' or 'track_portfolio', which might also involve wallet 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 no guidance on when to use this tool versus alternatives. It mentions 'Defaults to all supported chains' for the 'chains' parameter, but this is parameter-specific and doesn't address tool-level usage. There are no explicit when/when-not instructions or references to sibling tools, leaving the agent to infer usage based on the purpose 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. It discloses that it returns 'active' events with 'current odds', which adds useful behavioral context. However, it lacks details on rate limits, authentication needs, or error handling, leaving gaps for a tool with potential API costs.

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 structured sections for Args and Returns, and ends with price information. Every sentence earns its place with no wasted words, making it highly efficient and 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 (so return values are documented elsewhere) and no annotations, the description provides good context on purpose, parameters, and returns. It includes price information, which is valuable. However, it could better address behavioral aspects like rate limits or error cases for a paid tool.

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

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

Schema description coverage is 0%, so the description must compensate. It adds meaningful semantics by explaining 'category' as an optional filter with examples (politics, crypto, sports) and 'limit' as the number of events to return, which clarifies beyond the schema's basic titles. This effectively covers both 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's purpose with specific verbs ('Get active Polymarket prediction market events') and distinguishes it from siblings like 'get_polymarket_odds' and 'search_polymarket' by focusing on active events rather than odds or search 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 implies usage context by specifying 'active' events and listing categories, but does not explicitly state when to use this tool versus alternatives like 'get_polymarket_odds' or 'search_polymarket'. It provides clear filtering options but lacks explicit comparison guidance.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool retrieves data ('Get'), implying a read-only operation, but doesn't mention potential costs, rate limits, authentication needs, or error conditions. The inclusion of 'Price: $0.15' hints at a cost, but this isn't integrated into behavioral context. More details on what 'current' means (e.g., real-time vs. cached) would improve 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 well-structured and concise, using a clear purpose statement, an 'Args' section for parameters, a 'Returns' section for outputs, and a 'Price' note. Each sentence serves a purpose without redundancy. However, the 'Price' line feels slightly disconnected from the main flow, 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?

Given the tool's moderate complexity (one parameter, no annotations, but with an output schema), the description is somewhat complete. It covers purpose, parameters, and returns, but lacks usage guidelines and detailed behavioral context. The output schema likely handles return values, so the description doesn't need to elaborate on 'odds, volume, and price history.' Overall, it meets minimum viability but has 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 description adds minimal semantics beyond the input schema. It explains that 'event_id' is 'The Polymarket event ID,' which clarifies the parameter's purpose but doesn't provide format examples, constraints, or how to obtain valid IDs. With schema description coverage at 0% and only one parameter, this is adequate but not comprehensive, aligning with the baseline for moderate 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 purpose: 'Get current odds for a specific Polymarket event.' It specifies the verb ('Get'), resource ('odds'), and scope ('specific Polymarket event'), making it easy to understand. However, it doesn't explicitly differentiate from its sibling tool 'get_prediction_market_odds' or 'search_polymarket,' 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 a specific event ID but doesn't explain prerequisites, such as how to obtain event IDs, or contrast it with related tools like 'get_polymarket_events' for listing events or 'get_prediction_market_odds' for other markets. This lack of contextual guidance leaves gaps for an AI agent.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions that odds are 'aggregated from multiple sources' and includes a price ('Price: $0.50'), which adds some context. However, it doesn't disclose critical behavioral traits such as rate limits, authentication requirements, error conditions, or whether this is a read-only operation. For a tool with no annotations, 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 appropriately sized and well-structured with clear sections: purpose statement, Args, Returns, and Price. Each sentence earns its place, and there's no redundant information. However, the 'Price: $0.50' line could be integrated more smoothly, and the structure is functional but not exceptionally polished.

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's an output schema (which covers return values), no annotations, and low schema coverage (0%), the description does an adequate job. It explains the purpose, parameters, and returns at a high level, and the output schema will handle return details. However, for a tool with no annotations and sibling tools in similar domains, it lacks sufficient context about behavioral traits and usage differentiation.

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 descriptions. The description includes an 'Args' section that briefly explains 'event_id' and 'query', adding some semantic meaning beyond the schema. However, it doesn't provide details on format, constraints, or how these parameters interact (e.g., whether both can be used together). With 0% schema coverage, the description compensates partially but not fully.

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

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

The description clearly states the tool's purpose: 'Get prediction market odds (aggregated from multiple sources).' It specifies the verb ('Get'), resource ('prediction market odds'), and key characteristic ('aggregated from multiple sources'). However, it doesn't explicitly distinguish this tool from sibling tools like 'get_polymarket_odds' or 'search_polymarket', which appear related to similar domains.

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 two optional parameters (event_id and query) but doesn't explain when to use one over the other or when to use this tool compared to sibling tools like 'get_polymarket_odds' or 'search_polymarket'. There are no explicit when/when-not statements 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 for behavioral disclosure. It mentions the tool is 'AI-powered' and has a price ('$5.00'), which adds useful context. However, it doesn't disclose critical behavioral traits like whether this is a read-only operation, what happens with invalid inputs, rate limits, or authentication requirements for a paid service.

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 clear sections (purpose, args, returns, price) and uses minimal sentences. Every sentence adds value: the first states the core function, the args section explains parameters, returns describes output, and price discloses cost. No wasted words, though slightly more front-loading could improve it.

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 (so returns are documented elsewhere) and 2 parameters with 0% schema coverage, the description does an adequate job. It covers purpose, parameters, returns, and cost. However, for a paid tool with no annotations, it should more explicitly state behavioral expectations like error handling or usage limits to be 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?

Schema description coverage is 0%, so the description must compensate. It provides meaningful semantics for both parameters: 'address: Property street address' and 'property_id: Or property ID if known.' The 'Or' clarifies these are alternatives, which is valuable information not in the schema. However, it doesn't specify format requirements 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 tool's purpose: 'Get AI-powered property valuation estimate.' It specifies the verb ('Get') and resource ('property valuation estimate'), and the 'AI-powered' qualifier adds useful context. However, it doesn't explicitly differentiate from sibling tools, which appear unrelated to property valuation.

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 prerequisites, constraints, or relationships with sibling tools. The only implicit usage hint is that it's for property valuation, but no explicit when/when-not instructions are given.

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 a price ('Price: $0.40'), which is useful context about cost, but fails to describe other critical behaviors such as rate limits, authentication needs, error handling, or whether the operation is read-only or has side effects. For a tool with no annotation coverage, this leaves significant gaps in understanding how it behaves.

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, followed by args, returns, and price in a structured format. Each sentence adds value without redundancy. The only minor issue is the inclusion of 'Price: $0.40' as a separate line, which could be integrated more smoothly, but overall it's efficient and well-organized.

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's an output schema (which handles return values), no annotations, and low schema coverage, the description does an adequate job. It covers the purpose, parameters, returns, and cost, but lacks details on behavioral traits and usage context. For a tool with two parameters and no annotations, it's minimally complete but could be more informative about when and 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?

Schema description coverage is 0%, so the description must compensate. It adds meaning by explaining that 'token_address' is a 'token contract address (0x...)' and 'chain' is a 'Blockchain network,' which clarifies the semantics beyond the bare schema. However, it doesn't provide examples, format details, or constraints for these parameters, leaving some ambiguity. With two parameters and low schema coverage, this is a baseline adequate effort.

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

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

The description clearly states the tool's purpose: 'Get comprehensive risk metrics for a token.' It specifies the verb ('Get') and resource ('risk metrics for a token'), making it easy to understand what the tool does. However, it doesn't explicitly differentiate from sibling tools like 'get_wallet_risk_score' or 'get_credit_risk_score', 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 doesn't mention sibling tools like 'get_wallet_risk_score' or 'get_credit_risk_score' that might handle related risk assessments, nor does it specify prerequisites or exclusions. The only implicit context is the mention of 'token' and 'blockchain network,' but this is insufficient for clear usage guidelines.

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 'Price: $0.30' which is useful cost context, but lacks other behavioral details like rate limits, authentication needs, data freshness, or error handling. The description doesn't contradict annotations (none exist), but it's insufficient for a mutation-like tool (though sentiment analysis is likely read-only).

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 clear sections (Args, Returns, Price) and uses bullet-like formatting. It's relatively concise at 5 lines, though the 'Price' line could be integrated more smoothly. Most sentences earn their place by adding value beyond the tool name.

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

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

Given no annotations, 0% schema coverage, but an output schema exists (implied by 'Has output schema: true'), the description is moderately complete. It covers basic purpose, parameters, returns, and cost, but lacks behavioral context and usage guidance. The output schema reduces need to explain return values, but more operational details would help.

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 descriptions. The description adds some semantics: it explains 'query' as 'Topic to analyze (token name, project, or keyword)' and 'sources' as 'List of sources. Options: twitter, reddit, news, telegram'. This clarifies purpose and options, but doesn't fully compensate for the coverage gap (e.g., no details on source combinations or query formatting).

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

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

The description clearly states the tool's purpose: 'Get AI-powered sentiment analysis for crypto topics.' It specifies the action (get sentiment analysis) and resource (crypto topics). However, it doesn't explicitly differentiate from sibling tools like 'get_token_sentiment' or 'get_stock_sentiment' beyond mentioning 'crypto topics'.

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 'get_token_sentiment' or 'get_stock_sentiment' that might be related, nor does it specify prerequisites, constraints, or typical use cases beyond the basic function.

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 the tool is 'AI-powered' and includes a 'Price: $0.40', hinting at a paid service, but doesn't disclose critical behavioral traits like rate limits, authentication needs, data sources, or error handling. For a tool with no annotations, this leaves significant gaps in understanding its 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 well-structured and appropriately sized. It starts with a clear purpose, lists parameters with brief explanations, specifies returns, and ends with price info. Every sentence adds value, though the 'Price' line could be integrated more smoothly. It's front-loaded and avoids redundancy.

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

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

Given the tool's moderate complexity (4 params, no annotations, output schema exists), the description is partially complete. It covers parameters and return values, but lacks behavioral context (e.g., costs, limitations). The output schema handles return structure, so the description doesn't need to detail that, but it should address usage and operational aspects more fully.

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 effectively adds meaning by explaining each parameter: 'symbol' as 'Stock ticker symbol', and the boolean flags as controlling inclusion of news, technicals, and institutional analysis. This clarifies beyond the bare schema, though it doesn't detail format constraints (e.g., symbol validation).

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

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

The description clearly states the tool's purpose: 'Get AI-powered stock market sentiment analysis.' It specifies the action ('Get') and resource ('stock market sentiment analysis'), and distinguishes it from siblings like 'get_forex_sentiment' and 'get_token_sentiment' by focusing on stocks. However, it doesn't explicitly differentiate from 'get_sentiment_analysis' (a sibling), which might be more general.

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 siblings like 'get_forex_sentiment' for forex or 'get_token_sentiment' for tokens, nor does it specify prerequisites or exclusions. The only implicit context is the stock focus, but no explicit usage instructions are given.

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 the tool's read-only nature implicitly through 'Get' and lists return fields, but lacks details on error handling, rate limits, authentication needs, or whether it's a paid service beyond the pricing footnote. The description doesn't contradict any annotations (none exist), but could provide more behavioral context.

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

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

The description is well-structured with clear sections (purpose, args, returns, price) and front-loaded the core functionality. The pricing footnote, while useful for cost awareness, slightly detracts from pure conciseness as it's not essential for tool selection. Overall, most sentences earn their 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 2 parameters with 0% schema coverage and an output schema (which handles return values), the description is mostly complete. It explains both parameters thoroughly and states the return fields. However, for a tool with no annotations, it could better address behavioral aspects like error cases or rate limits to be fully comprehensive.

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

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

Schema description coverage is 0%, so the description must compensate fully. It successfully does so by explaining both parameters: token_address ('The token contract address (0x...)') and chain ('Blockchain network. Options: ethereum, base, polygon, bsc, arbitrum, optimism'), including the enum values for chain. This adds crucial meaning beyond the bare 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 specific action ('Get metadata') and resource ('ERC-20 token'), listing the exact fields returned (name, symbol, decimals, total supply). It distinguishes itself from sibling tools like get_token_price or get_token_sentiment by focusing on static token metadata rather than price, sentiment, or other dynamic 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: to retrieve basic token information. However, it doesn't explicitly mention when NOT to use it or name specific alternatives among the sibling tools (e.g., get_token_price for price data, get_token_sentiment for sentiment analysis). The pricing information implies usage considerations but isn't a functional guideline.

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 'real-time' and 'multiple DEX sources,' which adds some behavioral context, but fails to disclose critical traits like rate limits, error handling, authentication needs, or whether it's a read-only operation. The description is insufficient 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 with the core purpose. The 'Args' and 'Returns' sections are structured clearly, though the 'Price: $0.15' at the end is extraneous and doesn't add value, slightly reducing efficiency.

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, no annotations, and an output schema (implied by 'Returns'), the description is partially complete. It covers basic purpose and parameters but lacks usage guidelines, behavioral details, and output specifics beyond 'Token price in USD with source information,' leaving gaps for effective agent 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?

Schema description coverage is 0%, so the description must compensate. It adds meaning by explaining 'token_address' as 'The token contract address (0x...)' and 'chain' with options 'ethereum, base, polygon, bsc,' which clarifies beyond the schema's basic titles. However, it doesn't cover all parameter nuances, such as format requirements for 'token_address' or default behavior for 'chain.'

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

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

The description clearly states the tool's purpose: 'Get real-time token price from multiple DEX sources.' It specifies the verb ('Get'), resource ('token price'), and scope ('from multiple DEX sources'), though it doesn't explicitly differentiate from sibling tools like 'get_token_metadata' or 'get_trending_tokens'.

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. The description lacks context about prerequisites, such as needing a valid token address, and doesn't mention sibling tools like 'get_batch_quote' or 'get_token_metadata' that might serve related purposes.

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 fully disclose behavioral traits. It mentions the return values (sentiment score, social volume, trending topics) and includes a price ('Price: $0.25'), which adds some context about cost. However, it lacks critical details such as rate limits, authentication requirements, data freshness, or error handling, leaving 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 well-structured and appropriately sized: it starts with a clear purpose statement, lists parameters with brief semantics, specifies returns, and includes pricing. Each sentence adds value without redundancy. It could be slightly more front-loaded by integrating the price into the main flow, but overall it's efficient and 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 that there is an output schema (implied by 'Has output schema: true'), the description doesn't need to fully explain return values, which it partially does. However, with no annotations and 0% schema coverage, the description should provide more behavioral context (e.g., rate limits, errors) to be fully complete. It covers basics like purpose and parameters but misses advanced usage details.

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 lists parameters in an 'Args' section with brief explanations (e.g., 'token_address: The token contract address (0x...)'), adding meaning beyond the bare schema. However, it doesn't fully detail parameter constraints (e.g., valid chain values beyond the default 'ethereum'), leaving some ambiguity. With two parameters and partial compensation, a baseline score 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: 'Get AI-powered social sentiment analysis for a token.' It specifies the action ('Get AI-powered social sentiment analysis') and resource ('for a token'), which is clear and specific. However, it doesn't explicitly differentiate from sibling tools like 'get_sentiment_analysis' or 'get_stock_sentiment', which reduces it from 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 like 'get_sentiment_analysis' or 'get_stock_sentiment', nor does it specify contexts or exclusions for usage. The only implicit hint is the focus on tokens, but this is insufficient for effective 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the tool returns 'trading signals with entry/exit recommendations and confidence scores,' which gives some output context, but lacks critical details like rate limits, authentication needs, data freshness, or whether it's a read-only operation. The 'Price: $0.75' hint at cost is useful but insufficient for comprehensive 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 well-structured and appropriately sized, with a clear purpose statement followed by Args and Returns sections. The 'Price' note is concise and relevant. While efficient, the lack of usage guidance slightly reduces its overall effectiveness.

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 of trading signals and the presence of an output schema (which handles return values), the description is moderately complete. It covers purpose and parameters but misses behavioral traits and usage guidelines. With no annotations and incomplete parameter guidance, it falls short of being fully adequate 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?

Schema description coverage is 0%, so the description must compensate. It adds meaning by explaining 'token' as 'Optional token address or symbol to focus on' and 'chain' as 'Blockchain network' with options listed, which clarifies beyond the schema's basic titles. However, it doesn't fully detail parameter interactions or default behaviors, leaving gaps in 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 clearly states the tool's purpose: 'Get AI-powered trading signals and market recommendations.' It specifies the action (get) and resource (trading signals) with the qualifier 'AI-powered.' However, it doesn't explicitly differentiate from its sibling 'get_trading_signal' (singular vs. plural), leaving some ambiguity about their distinct roles.

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 'get_trading_signal' or 'get_arbitrage_opportunities,' nor does it specify prerequisites, ideal contexts, or exclusions for its use.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions a price ('Price: $0.50'), which hints at a paid service, but doesn't cover critical aspects like rate limits, authentication needs, error handling, or whether it's a read-only operation. The description is too sparse for a tool that likely involves external data fetching and financial implications.

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 front-loaded with the core purpose, followed by clear sections for Args and Returns. Every sentence earns its place, with no wasted words. The inclusion of price is concise and relevant. It efficiently communicates essential information in a minimal format.

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 (financial signal generation), no annotations, and an output schema (implied by 'Returns'), the description is reasonably complete. It covers purpose, parameters, and return values, though it lacks behavioral context like rate limits or error handling. The output schema reduces the need to detail return structure, but more transparency would be beneficial for a paid service.

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% description coverage. It explains that 'symbol' is a 'Trading pair symbol' with examples (e.g., ETH/USDC), and specifies 'timeframe' options (1m, 5m, etc.) with a default of '1h' implied. This fully compensates for the schema's lack of documentation, making parameters 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: 'Get trading signal for a specific symbol and timeframe.' It specifies the verb ('Get') and resource ('trading signal'), and while it doesn't explicitly differentiate from siblings like 'get_trade_signals', the singular vs. plural naming implies a more targeted function. However, it lacks explicit sibling differentiation, 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 prerequisites, context, or exclusions, and fails to distinguish it from similar tools like 'get_trade_signals' or 'get_forex_sentiment'. The only implicit guidance is the parameter requirements, but this is insufficient for effective 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 mentions the return format ('List of trending tokens with volume, price change, and social metrics') and includes a price ('$0.50'), which adds some behavioral context. However, it doesn't disclose important traits like rate limits, authentication requirements, data freshness, or potential side effects. The description is insufficient for a mutation-free but potentially complex data retrieval 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 well-structured and front-loaded with the core purpose. It uses clear sections (Args, Returns) and bullet-like formatting without unnecessary verbiage. Every sentence earns its place, and the price information is efficiently appended.

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 (2 parameters, no annotations, but with output schema), the description is reasonably complete. It covers the purpose, parameters, return format, and cost. The output schema likely details the return structure, so the description doesn't need to exhaustively explain return values. However, it lacks usage context and some behavioral details.

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 descriptions. The description compensates by documenting both parameters in the 'Args' section: 'chain' with specific blockchain options and 'limit' with a maximum constraint. This adds meaningful semantics beyond the bare schema. However, it doesn't explain parameter interactions 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: 'Get trending tokens across DeFi platforms.' It specifies the verb ('Get') and resource ('trending tokens'), and provides scope ('across DeFi platforms'). However, it doesn't explicitly differentiate from sibling tools like 'get_token_metadata' or 'get_token_price' which might retrieve different token 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 no guidance on when to use this tool versus alternatives. It doesn't mention any prerequisites, timing considerations, or comparison with sibling tools like 'get_token_sentiment' or 'get_trade_signals' that might also involve token analysis. The only implicit context is the need for trending token data.

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 'Price: $0.50', which hints at a paid service, but doesn't cover other critical aspects like rate limits, authentication needs, error handling, or whether this is a read-only operation. The description lacks details on what 'risk analysis' entails or how the scoring works.

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 sections for Args and Returns, making it easy to scan. It's front-loaded with the core purpose and avoids unnecessary fluff. The inclusion of 'Price: $0.50' is concise but could be integrated more smoothly. Overall, it's efficient with minimal 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?

Given no annotations, 0% schema coverage, but an output schema exists, the description is moderately complete. It covers the purpose, parameters, and return values at a high level, but lacks depth on behavioral aspects like error cases or performance. The output schema likely details the return structure, so the description doesn't need to explain return values extensively, but more context on usage and limitations would help.

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 explaining 'wallet_address' as 'The wallet address to analyze (0x...)' and 'chain' as 'Primary chain for analysis. Options: ethereum, base, polygon', which clarifies the format and options beyond the schema's basic titles. However, it doesn't detail constraints like address validation or chain-specific behaviors.

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

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

The description clearly states the tool's purpose: 'Get risk analysis and security scoring for any wallet address.' It specifies the verb ('Get') and resource ('wallet address'), making it easy to understand. However, it doesn't explicitly differentiate from sibling tools like 'get_credit_risk_score' or 'get_risk_metrics', which might also involve risk assessment but for different domains.

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, such as 'detect_fraud' or 'run_compliance_check' for related security tasks. Usage is implied only by the tool's name and description.

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 'real-time' and 'alerts,' implying timely notifications, but lacks details on rate limits, authentication needs, data freshness, or whether this is a read-only operation. The 'Price: $0.35' hints at a paid service but doesn't clarify billing conditions.

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

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

The description is well-structured and front-loaded with the core purpose, followed by parameter explanations and return details. Every sentence earns its place, with no redundant information. The 'Price' line is concise and relevant for cost-aware usage.

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 (2 parameters, no annotations, but with an output schema), the description is partially complete. It covers parameters and return value basics, but lacks behavioral context like rate limits or real-time constraints. The output schema existence reduces the need to detail return values, but more operational guidance would help.

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 effectively explains both parameters: 'chains' as 'List of chains to monitor' with a default, and 'min_value_usd' as 'Minimum transaction value in USD to alert on' with an implied threshold. This adds crucial meaning beyond the bare 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 tool's purpose: 'Get real-time whale transaction alerts across chains.' It specifies the verb ('Get'), resource ('whale transaction alerts'), and scope ('across chains'). However, it doesn't explicitly differentiate from sibling tools like 'detect_fraud' or 'get_trade_signals' that might also involve transaction monitoring.

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 'detect_fraud' for suspicious activity or 'get_trade_signals' for trading insights, nor does it specify prerequisites or exclusions for usage.

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 limited behavioral insight. It mentions 'risk assessment' in returns and a price, but doesn't disclose critical details like required permissions, rate limits, whether revoke_risky is destructive, or error handling. For a tool with potential write operations (revoke_risky), this is a significant gap 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 appropriately sized and front-loaded with the core purpose. The Args and Returns sections are structured clearly, and the price is efficiently noted. Every sentence earns its place, though the action options could be more detailed without sacrificing 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 3 parameters with 0% schema coverage, no annotations, but an output schema exists, the description is moderately complete. It covers basic purpose, parameters, and returns, but lacks behavioral context (e.g., safety of revoke_risky) and detailed usage guidelines. The output schema reduces need to explain return values, but more context on tool behavior is warranted.

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 explaining wallet_address is 'to check', chain as 'Blockchain network', and action options ('list, revoke_risky'). However, it doesn't detail format requirements (e.g., wallet address validation), chain options beyond default, or what 'risky' means for revoke_risky. The description partially compensates but leaves gaps.

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: 'Manage token approvals for a wallet' with specific actions (list, revoke_risky) and mentions risk assessment. It distinguishes itself from siblings by focusing on token approvals rather than other wallet or blockchain operations. However, it doesn't explicitly differentiate from tools like 'get_wallet_risk_score' which might overlap in risk assessment.

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 alternatives is provided. The description mentions actions but doesn't specify scenarios for choosing 'list' vs 'revoke_risky', prerequisites, or how it differs from sibling tools like 'get_wallet_risk_score' or 'detect_fraud'. Usage is implied through parameter descriptions but not clearly articulated.

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 'AI-powered' and includes a 'Price: $1.00' which suggests a paid service, but doesn't disclose critical behavioral traits like rate limits, authentication requirements, whether this is a read-only analysis or triggers actual trades, or what happens with the recommendations.

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 clear sections (purpose, args, returns, price). The 'Price: $1.00' line could be integrated more smoothly, but overall it's efficient with minimal waste. The structure helps with readability despite some formatting issues.

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) but no annotations and 0% schema description coverage, the description provides basic purpose and parameter context but lacks important behavioral information. For a financial optimization tool that likely involves complex calculations and potentially paid services, more disclosure about limitations, accuracy, or implementation details would be beneficial.

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 provides some parameter semantics by describing 'holdings' as 'List of current holdings' with example structure and 'risk_tolerance' as 'Risk level' with options, which adds meaningful context beyond the bare schema. However, it doesn't fully explain the 'chain' field in holdings or provide format details for 'amount'.

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 'AI-powered portfolio optimization recommendations' and specifies it returns 'rebalancing recommendations and optimal allocation', which gives a specific verb+resource combination. However, it doesn't differentiate from sibling tools like 'track_portfolio' or 'get_risk_metrics' that might overlap in financial analysis domains.

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. There's no mention of prerequisites, when this optimization is appropriate, or how it differs from other portfolio-related tools in the sibling list like 'track_portfolio' or 'get_risk_metrics'.

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 discloses the tool's behavior: testing connectivity, returning platform status/version/services count, and mentions a price ('Price: $0.25'), which is valuable context about cost implications. However, it doesn't cover other behavioral aspects like rate limits, authentication requirements, error conditions, or whether it's read-only/destructive. The price disclosure adds some value beyond basic functionality.

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 clear sections: purpose statement, Args, Returns, and Price. Each sentence earns its place by providing essential information without redundancy. The front-loaded purpose statement immediately conveys the tool's function, followed by organized 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 low complexity (1 optional parameter) and the presence of an output schema (which handles return values), the description is reasonably complete. It covers purpose, parameter meaning, return overview, and cost. However, without annotations, it could benefit from more behavioral context (e.g., idempotency, side effects) to fully guide the agent, though the output schema mitigates some 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?

Schema description coverage is 0%, so the description must compensate. It provides the parameter 'message' with semantics: 'Optional message to include in ping' and includes a default in the schema. This adds meaningful context beyond the schema's type/format. With only one parameter well-explained, it adequately compensates for the schema's lack of descriptions.

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

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

The description clearly states the tool's purpose: 'Test connectivity to Coin Railz x402 payment infrastructure.' It specifies the verb ('Test connectivity') and target resource ('Coin Railz x402 payment infrastructure'), making it distinct from sibling tools that focus on analysis, transactions, or data retrieval rather than connectivity testing. However, it doesn't explicitly differentiate from potential similar connectivity tools (none are present in siblings).

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

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, appropriate contexts, or exclusions. While the purpose is clear, the lack of usage context leaves the agent without direction on when this connectivity test is needed versus other operations in the payment infrastructure ecosystem.

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 provides minimal behavioral context. It mentions a price ('Price: $500') which is useful cost disclosure, but doesn't describe authentication needs, rate limits, whether this initiates a paid service, response time expectations, or what 'preliminary assessment' entails beyond the output schema.

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

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

The description is efficiently structured with clear sections (purpose, Args, Returns, Price). Each sentence earns its place, though the 'Returns' section could be more specific given the output schema exists. The formatting with bullet-like sections aids readability.

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 paid consultation request tool with 3 parameters and an output schema, the description covers the basics but has gaps. The price disclosure is helpful, but without annotations, it should better explain behavioral aspects like whether this initiates a binding transaction, what 'preliminary assessment' means, and how this differs from free compliance tools in the sibling set.

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?

With 0% schema description coverage, the description compensates well by explaining all three parameters in the Args section: 'entity_type' with example options, 'jurisdictions' with examples, and 'services' with examples. This adds meaningful context beyond the bare schema, though it doesn't specify if the listed options are exhaustive or just 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 as 'Request AML/KYC compliance consultation' - a specific verb ('Request') and resource ('compliance consultation') with domain context ('AML/KYC'). However, it doesn't differentiate from sibling tools like 'run_compliance_check' or 'request_payment_processing', which might have overlapping compliance domains.

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 about when to use this tool versus alternatives. The description doesn't mention prerequisites, appropriate contexts, or how this differs from sibling tools like 'run_compliance_check' or 'request_smart_contract_audit' that might also involve compliance aspects.

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 tool sets up payment processing and includes a price ('$50/hour'), which suggests this might be a paid service. However, it doesn't disclose important behavioral aspects like whether this is a read-only or mutating operation, what permissions are required, whether it's rate-limited, what happens if setup fails, or what the integration process entails beyond returning 'instructions.'

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 begins with a clear purpose statement, then lists parameters with brief explanations, followed by return information, and ends with pricing. The 'Args:' and 'Returns:' sections create helpful structure. The only minor inefficiency is the inclusion of 'Price: $50/hour' which might be better placed elsewhere or formatted differently.

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 this is a 3-parameter tool with no annotations but with an output schema, the description provides basic but incomplete context. It covers the purpose and parameters at a high level and mentions what the tool returns. However, for a tool that presumably creates or configures payment processing (a potentially complex operation), the description lacks important details about prerequisites, side effects, error conditions, and the actual behavioral impact of invoking 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 description provides basic semantic information about the three parameters: merchant_id is a 'Merchant identifier,' payment_type has 'Options: one-time, subscription, escrow,' and currencies are 'Accepted cryptocurrencies.' However, with 0% schema description coverage, this leaves significant gaps. The description doesn't explain format requirements for merchant_id, whether currencies array has specific format constraints, or what happens when payment_type uses the default 'one-time' value versus other options.

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: 'Set up multi-chain payment processing for merchants.' This is a specific verb ('Set up') with a clear resource ('payment processing') and scope ('multi-chain'). However, it doesn't explicitly distinguish this tool from its many siblings, which include various financial and blockchain-related tools but no obvious payment processing alternatives.

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. While the sibling list includes tools like 'request_compliance_consultation' and 'request_smart_contract_audit' that might be related in a financial services context, there's no explicit comparison or context for choosing this specific payment processing tool. The description simply states what it does without indicating appropriate use cases.

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

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

No annotations are provided, so the description carries full burden. It mentions 'comprehensive' audit, price, and estimated delivery time, which adds some behavioral context. However, it lacks critical details: whether this is a paid service requiring authorization, if it's a one-time or recurring request, rate limits, or what happens after submission (e.g., asynchronous processing). For a tool with financial implications, this is insufficient.

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 clear sections (Args, Returns, Price) and uses bullet-like formatting. It's front-loaded with the core purpose. The price note is slightly extraneous but relevant. Overall efficient with minimal 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?

Given no annotations, 3 parameters with 0% schema coverage, and an output schema (implied by 'Returns'), the description is moderately complete. It covers parameters and return intent but lacks behavioral details like error handling or authentication needs. The output schema likely handles return values, so description focus on process is adequate but not thorough.

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 lists parameters and adds meaning: 'contract_address: Contract to audit', 'chain: Blockchain network', and 'scope: Audit scope. Options: quick, standard, full'. This clarifies semantics beyond schema titles. However, it doesn't explain parameter formats (e.g., chain values beyond default 'ethereum') or dependencies, leaving gaps.

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: 'Request comprehensive smart contract security audit.' It specifies the verb ('request') and resource ('smart contract security audit'), making the action clear. However, it doesn't explicitly differentiate from sibling tools like 'scan_smart_contract' or 'run_compliance_check', which might have overlapping security 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 no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing a contract address), exclusions, or compare it to siblings like 'scan_smart_contract' for lighter analysis. The price mention hints at cost considerations but isn't explicit usage guidance.

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

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

No annotations are provided, so the description carries the full burden. It mentions the tool runs checks and returns status, flags, and actions, but lacks critical behavioral details: it doesn't specify permissions needed, whether it's read-only or mutative, rate limits, or error handling. The mention of 'Price: $1.00' hints at a cost, but this isn't elaborated (e.g., per call, billing implications).

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, followed by Args and Returns sections that are easy to parse. The 'Price' note is concise but could be integrated better. There's minimal fluff, though the separation into sections aids readability without verbosity.

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, 0% schema coverage, but an output schema exists, the description is moderately complete. It covers the basic purpose and parameter meanings, and the output schema handles return values, so the description doesn't need to explain those. However, for a tool with potential side effects (e.g., cost, compliance implications), more behavioral context would improve completeness.

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

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

Schema description coverage is 0%, so the description must compensate. It adds meaningful context: 'entity_id' is explained as an identifier for entities like wallet addresses, and 'check_type' lists specific options (aml, kyc, sanctions, pep) with a default noted. This goes beyond the bare schema, providing practical usage semantics, though it doesn't detail format constraints or 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: 'Run AML/KYC compliance checks.' It specifies the action ('Run') and resource ('compliance checks'), with additional context about the types (AML, KYC, sanctions, PEP). However, it doesn't explicitly differentiate from sibling tools like 'detect_fraud' or 'get_wallet_risk_score', which might have overlapping domains in financial risk assessment.

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. The description doesn't mention prerequisites, appropriate contexts, or comparisons with sibling tools like 'detect_fraud' or 'get_credit_risk_score'. Usage is implied through the description of what it does, but no explicit when/when-not instructions are given.

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 a price ('$2.00'), which is useful context about cost. However, it lacks critical behavioral details: whether this is a read-only or mutating operation, rate limits, authentication needs, execution time, or what happens with invalid inputs. For a security analysis tool with no annotations, 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 and front-loaded: the first sentence states the purpose, followed by structured sections for Args, Returns, and Price. Each sentence earns its place, though the 'Price' line could be integrated more smoothly. No redundant information is present.

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 2 parameters with 0% schema coverage and an output schema (implied by 'Returns'), the description is moderately complete. It covers parameter semantics and return types but lacks behavioral context (e.g., cost implications, error handling). For a tool with no annotations and a price, more details on execution and limitations would improve completeness.

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

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

Schema description coverage is 0%, so the description must compensate. It adds meaning by explaining 'contract_address' as 'The contract address to scan (0x...)' with format hint, and 'chain' as 'Blockchain network' with enumerated options ('ethereum, base, polygon'). This clarifies parameter purposes beyond schema titles. However, it doesn't detail constraints (e.g., address validation) or default behavior for 'chain'.

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 'security analysis on a smart contract' with a specific verb ('Perform security analysis') and resource ('smart contract'). It distinguishes from most siblings (e.g., get_token_price, get_wallet_risk_score) by focusing on contract security rather than pricing or wallet analysis. However, it doesn't explicitly differentiate from 'request_smart_contract_audit' which might be a similar sibling.

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 prerequisites (e.g., needing a contract address), exclusions (e.g., unsupported chains beyond listed options), or comparisons to siblings like 'request_smart_contract_audit'. The 'Args' and 'Returns' sections are informative but don't constitute usage guidelines.

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 a price ('Price: $0.20'), which is useful cost context, but lacks other critical details like rate limits, authentication needs, error handling, or whether it's a read-only operation. The description states it returns 'current odds,' but doesn't explain format or limitations.

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 front-loaded with the core purpose, followed by parameter and return details, and ends with price. It's concise with no wasted sentences, though the 'Args:' and 'Returns:' formatting could be slightly more integrated for flow.

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 covers return values), no annotations, and low schema coverage, the description is moderately complete. It includes purpose, parameters, returns, and price, but misses behavioral traits like rate limits or error cases. For a search tool with cost implications, more context would improve completeness.

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

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

Schema description coverage is 0%, so the schema provides no parameter descriptions. The description adds basic semantics: 'query: Search query' and 'limit: Number of results to return,' which clarifies purpose but lacks depth (e.g., query syntax, limit range). It compensates partially but not fully for the schema gap, warranting an average 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 tool's purpose: 'Search Polymarket events by keyword.' It specifies the verb ('search'), resource ('Polymarket events'), and scope ('by keyword'), making the function unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'get_polymarket_events' or 'get_polymarket_odds', 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 doesn't mention sibling tools (e.g., 'get_polymarket_events' for unfiltered listing or 'get_polymarket_odds' for specific odds), prerequisites, or exclusions, leaving the agent to infer usage 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 full burden for behavioral disclosure. It mentions what information is returned ('Progress updates, timeline, and budget status') but doesn't describe how the tool behaves: whether it's a read-only query, requires authentication, has rate limits, returns real-time vs. historical data, or what format/specificity the outputs have. For a tool with zero annotation coverage, this leaves significant 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 appropriately sized and front-loaded with the core purpose first. The 'Args:' and 'Returns:' sections are structured clearly. However, the 'Price: $2.00' line is extraneous and doesn't belong in a tool description meant for AI agents, slightly reducing efficiency.

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), no annotations, and a simple single-parameter input, the description is moderately complete. It states the purpose and outlines returns at a high level. However, for a tool with zero annotation coverage and no behavioral context, it should provide more operational details about how tracking works and what the agent can 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%, so the schema provides no parameter documentation. The description adds minimal value: it names the single parameter ('project_id') and states it's 'The construction project ID' but doesn't explain format, where to obtain it, or validation rules. With only one parameter, the baseline is 4, but the description doesn't fully compensate for the schema's lack of documentation, warranting a 3.

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

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

The description clearly states the tool's purpose: 'Track construction project progress and milestones' - a specific verb ('track') and resource ('construction project progress and milestones'). It distinguishes itself from sibling tools, which are mostly finance/crypto related, making its domain clear. However, it doesn't specify what 'tracking' entails operationally beyond the high-level concept.

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. There are no explicit when/when-not instructions, no mention of prerequisites, and no comparison to any other tools (though siblings appear unrelated to construction). The only contextual clue is the domain itself, which is insufficient for proper usage decisions.

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 'Price: $0.75,' which hints at a paid service, but doesn't disclose other behavioral traits like rate limits, authentication needs, data freshness, or error handling. For a tool with financial implications and no annotations, this is a significant gap 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 well-structured and appropriately sized. It starts with the core purpose, lists args and returns in clear sections, and ends with pricing. Each sentence adds value, though the 'Price' line could be integrated more smoothly. There's minimal waste, making it efficient 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's complexity (financial analytics with 2 parameters), no annotations, and an output schema (implied by 'Returns'), the description is moderately complete. It covers purpose, parameters, returns, and pricing, but lacks behavioral context (e.g., rate limits, data sources) and doesn't fully detail parameter usage. The output schema likely handles return values, reducing the burden on the 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?

Schema description coverage is 0%, so the schema provides no parameter descriptions. The description adds basic semantics: 'wallet_address: The wallet address to track' and 'chains: List of chains to include in portfolio.' This clarifies the purpose of each parameter but lacks details like format examples, chain name conventions, or default behavior when chains is null. It partially compensates for the schema gap but not fully.

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

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

The description clearly states the tool's purpose: 'Get comprehensive portfolio tracking and analytics.' It specifies the verb 'Get' and the resource 'portfolio tracking and analytics,' making it clear this is a retrieval/analysis tool. However, it doesn't explicitly differentiate from sibling tools like 'get_multi_chain_balance' or 'optimize_portfolio,' 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 doesn't mention sibling tools like 'get_multi_chain_balance' (which might provide balance data) or 'optimize_portfolio' (which might involve recommendations), nor does it specify prerequisites or exclusions. The only implicit context is the need for a wallet address and optional chains.

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 'verify and register' and 'on-chain identity NFT details', implying a write operation with blockchain interaction, but fails to detail critical behaviors: required permissions, costs beyond the stated price (e.g., gas fees), whether registration is irreversible, rate limits, or what happens if verification fails. The price is noted, but other operational traits are missing.

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 concise, with purpose stated upfront, followed by args and returns sections, and a price note. Each sentence adds value, such as specifying the standard and optionality of proof. However, the 'Price: $2.00' line, while useful, could be integrated more smoothly, and some redundancy exists between the description text and schema titles.

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 (blockchain identity verification with two parameters, no annotations, but an output schema exists), the description is moderately complete. It covers purpose and parameters briefly, and the output schema likely handles return values, reducing the need for detailed output explanation. However, it lacks critical context like authentication needs, error handling, or integration with siblings (e.g., 'create_agent_wallet'), leaving 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?

Schema description coverage is 0%, so the schema provides no parameter details. The description adds minimal semantics: it lists 'agent_address' and 'proof' with brief notes ('The agent's wallet address', 'Optional identity proof or attestation'), but doesn't explain formats (e.g., Ethereum address checksum), proof requirements, or examples. This partially compensates for the schema gap but leaves key details unclear, warranting 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 tool's purpose: 'Verify and register an AI agent's on-chain identity (ERC-8004).' It specifies the verb ('verify and register'), resource ('on-chain identity'), and standard ('ERC-8004'), making it distinct from siblings like 'create_agent_wallet' or 'scan_smart_contract'. However, it doesn't explicitly differentiate from all siblings, such as 'run_compliance_check', which might have overlapping identity verification 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 provides no guidance on when to use this tool versus alternatives. It lacks context about prerequisites (e.g., whether an agent wallet must exist first), exclusions (e.g., not for human identities), or comparisons to siblings like 'create_agent_wallet' or 'run_compliance_check'. The mention of 'ERC-8004' hints at blockchain context but doesn't clarify usage scenarios.

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