xportalx

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

No annotations are provided, so the description must carry the full burden. It only lists actions (info, verify) and mentions 'FREE', which is a pricing/marketing note rather than an operational trait. It does not disclose side effects, permissions, rate limits, or any other behavioral context that would help an agent predict tool behavior.

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

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

The description is very short and front-loaded with the main purpose, but it ends with an unnecessary 'FREE' that adds no operational value. The structure is a fragment rather than a well-formed sentence, which slightly reduces clarity.

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

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

With 5 parameters, no output schema, and no annotations, the description provides minimal context. It does not explain what the tool returns, any prerequisites, possible errors, or how actions relate to parameters. The description is too sparse to fully equip an agent for correct invocation.

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

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

Schema coverage is 100%, so the baseline is 3, but the description actively confuses parameter semantics by introducing 'check rates' which does not correspond to any action enum value. Instead of adding value, it contradicts the structured schema, lowering the 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 identifies the tool as handling x402 payment facilitation with specific actions like getting payment info and verifying transactions. However, it also mentions 'check rates' which isn't an action in the schema, creating slight ambiguity. It doesn't strongly differentiate from sibling x402 tools, but the core purpose is understandable.

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

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

The description implies usage for x402 payment information and verification tasks, but provides no explicit guidance on when to use this tool versus alternatives like x402_proxy or x402_send. There are no exclusionary statements or contextual hints beyond the general action list.

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

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

No annotations are provided, so the description carries the full burden. It discloses that the tool is free ('FREE - no payment required'), which is useful cost-related context, and 'Get' implies a read-only operation. However, it does not mention potential rate limits, data freshness, or whether it uses a public API, leaving some behavioral aspects undisclosed.

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

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

The description is extremely concise, using just two short sentences. The core purpose is front-loaded, and the 'FREE' note is a valuable addition that doesn't waste words. Every word earns its place.

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

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

This is a simple tool with only two parameters and no output schema. The description conveys the basic purpose and cost, but does not describe the return format (e.g., price, timestamp, currency) or error behavior. Given the lack of an output schema, the agent has no idea what the response will look like, which is a notable gap.

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

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

Schema description coverage is 100%, so the baseline is 3. The description adds no additional meaning beyond the schema: 'symbol' and 'currency' are already described as crypto and fiat respectively. The phrase 'exchange rates' hints at the relationship between symbol and currency, but this is marginal.

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

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

The description clearly states the tool's function: 'Get cryptocurrency prices and exchange rates from Coinbase.' It uses a specific verb ('Get') and resource ('cryptocurrency prices and exchange rates from Coinbase'), and the name 'coinbase_price' aligns perfectly. While it doesn't explicitly compare to sibling tools, the source specification ('from Coinbase') helps distinguish it from other price-related tools.

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

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

No guidance is provided on when to use this tool versus alternatives. With many sibling tools (e.g., 'dexscreener_token', 'nansen_smart_money_holdings'), there is no indication of which tool is best for which scenario. The description lacks any context about use cases or exclusions.

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

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

With no annotations, the description carries the full burden. It discloses the cost ('0.01 USDC') and the behavior of following links to a specified depth. However, it does not describe rate limits, robots.txt handling, or whether it returns page content or just troves of links, leaving notable gaps.

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

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

The description is two sentences long, front-loaded with the core purpose, and the cost detail is relevant. There is no filler or repetition; every word earns its place.

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

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

The tool has no output schema, so the description should explain what the tool returns (e.g., list of URLs, page content, crawl report). It also lacks any caveats about potential costs beyond the flat fee. While parameters are fully covered, the missing output info and usage context make the description incomplete for a crawl 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 coverage is 100%, so parameters are already documented in the schema. The description adds no additional meaning beyond the schema, only restating 'up to specified depth' which is already captured by maxDepth. Thus, baseline 3 applies.

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

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

The description clearly states the tool's function: 'Crawl a website starting from a URL, following links up to specified depth.' It uses a specific verb ('crawl') and resource ('website'), and distinguishes from sibling tools like fetch_page by emphasizing link-following and depth.

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. The description does not mention when not to use it (e.g., for single-page fetches) or reference sibling tools. The cost mention is useful but does not serve as usage direction.

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

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

The description discloses the cost (0.01 USDC) and the behavior that the owner wallet is auto-detected from the x402 payment. However, this contradicts the input schema, which requires 'owner_wallet' as a mandatory field. This serious inconsistency misleads the agent about whether the parameter is needed, undermining trust in the tool's behavior.

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

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

The description is concise at three sentences. It front-loads the main purpose and then adds cost and usage details. The only issue is the contradictory owner-detection sentence, which could have been clarified or omitted, but overall the structure is efficient.

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

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

Given no annotations and no output schema, the description should explain the return value and how the wallet is used afterward. It mentions usage for automated transactions and cost, but does not describe what the response looks like or how to reference the created wallet. The inconsistent statement about owner_wallet also leaves a gap in 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 100%, so baseline is 3. The description attempts to add meaning by stating the owner wallet is auto-detected and 'no need to provide it explicitly,' but this directly contradicts the schema's required 'owner_wallet' field. This confusion reduces the value of the parameter documentation, so a score below baseline 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: 'Create a custodial wallet for an AI agent using Privy.' It uses a specific verb ('Create') and resource ('custodial wallet'), and distinguishes itself from sibling tools like fund_wallet or withdraw_wallet by specifying the custodial nature for AI agents and the use case for automated transactions.

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 the tool: it is for creating a wallet for an AI agent, with a cost of 0.01 USDC, and the wallet can be used for automated transactions like swaps. It doesn't explicitly name alternatives, but the context is sufficient to infer its appropriate use case.

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

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

With no annotations, the description carries the transparency burden. It discloses that the data is real-time and that the tool is free, which adds some behavioral context. However, it does not mention potential rate limits, response format, or any limitations. For a read-only tool, this is adequate but not rich.

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

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

The description is two short sentences, front-loaded with the core purpose and followed by the free note. Every word earns its place, with no redundancy or filler. Excellent 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?

For a simple two-parameter read tool with no output schema, the description and schema together provide sufficient context. It lacks a detailed return structure, but the general 'price and market data' gives a reasonable expectation. The absence of output schema is partly compensated by the clear scope, making it almost 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 100%, so the baseline is 3. The description does not add any parameter-specific meaning beyond what the schema already provides. It mentions 'token price and market data' but does not elaborate on parameters, so no additional value is given.

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

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

The description clearly specifies a specific verb ('Get') and resource ('real-time token price and market data from DexScreener'). It distinguishes itself from sibling tools like coinbase_price by naming the data source, making it easy for an agent to select this tool for DexScreener 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 does not explicitly state when to use this tool vs alternatives, but the phrase 'from DexScreener' implies its context. There are no exclusions or alternative recommendations, leaving the agent to infer usage from the name and description. This meets the 'implied usage' level.

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

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

With no annotations, the description must disclose behavioral traits itself. It mentions cost (0.01 USDC) and output (NFT), which is helpful, but it omits critical behaviors like the two-step payment flow (initial 402 response requiring paymentProof) and any wallet prerequisites. The schema hints at this, but the description does not.

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

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

Three short sentences front-load the action and deliver key details (purpose, cost, output) with no unnecessary words. The structure is easy to scan and every word earns its place.

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

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

Given the tool's complexity (5 parameters, no output schema, no annotations), the description is somewhat thin. It provides the overall purpose, cost, and output, but not the registration workflow, payment proof steps, or endpoint configuration. The schema covers parameter details, but the description misses the process context needed for correct 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 100%, so parameters are already well-documented. The description adds marginal value by linking the recipientWallet to the NFT outcome, but it does not explain the paymentProof requirement or endpoint structure beyond schema.

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

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

The description uses a specific verb ('Register') and object ('your AI agent on-chain') with the ERC-8004 standard, clearly distinguishing it from sibling tools like verify_agent. It also states the outcome (an NFT), making the purpose unambiguous.

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

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

The description implies when to use the tool (when you want to register an AI agent on-chain) and notes the cost, but it does not provide explicit alternatives or when-not-to-use conditions. There is no reference to verify_agent or other sibling tools for context.

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

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

No annotations are provided, so the description must carry the full behavioral burden. It mentions 'AI-powered extraction' and a cost of 0.01 USDC, but it does not disclose whether the operation is read-only, the output format, potential failure modes, or any rate limits. This is a significant gap for a tool with no annotation support.

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

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

The description is one short sentence followed by a cost note. It is front-loaded with the verb 'Extract' and a specific resource, and every word earns its place without redundancy. This is exemplary 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?

With no output schema and no annotations, the description is expected to explain return behavior and additional context. It covers the core purpose but omits details about the output format, the optional 'intent' parameter, and error handling. It is minimally viable 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?

Schema description coverage is 100%, so the schema already documents all parameters, setting a baseline of 3. The description adds some connecting context by mentioning 'JSON schema' and 'AI-powered' (relating to the intent parameter), but it does not meaningfully enhance understanding of parameter formats or syntax beyond the schema.

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

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

The description clearly states the tool extracts structured data from a web page using a JSON schema, providing a specific verb, resource, and mechanism. However, it does not explicitly distinguish itself from sibling tools like crawl or fetch_page, so it falls short of a 5.

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

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

The description implies usage when you need structured data from a web page with a defined schema, but it gives no explicit guidance on when to use this tool versus alternatives. There are no stated exclusions or references to sibling tools, so the guidance is only implicit.

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

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

No annotations are provided, so the description must carry the full burden. It mentions 'FREE' (a cost trait) and implies read-only via 'lookup' and 'reference', but it does not explicitly state that it is a safe read operation, what happens with no parameters, return format, or error 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 extremely concise: two short clauses that front-load the main purpose. Every word earns its place, including the value-add 'FREE'.

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

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

Given the simple dual-mode nature, the description covers the primary use cases but leaves gaps: no mention of expected output, no guidance on what happens if both or neither parameter is provided, and no explicit read-only note (since annotations are absent). This is minimally acceptable for a simple lookup 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 coverage is 100%, so both parameters are already described. The description adds a slight mapping: jobId for 'lookup job failures' and failure_code for 'get failure code reference', but this largely mirrors the schema. No additional syntax, examples, or relationships are provided.

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: 'lookup job failures or get failure code reference', with specific resources (job failures, failure code reference) and two distinct modes. The initial verb 'Understand' is vague, but the rest clarifies. It doesn't explicitly differentiate from sibling tools, though none appear similar.

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 usage is implied: use this tool to understand job failures or get a failure code reference. The word 'FREE' hints at a cost advantage, but there is no explicit when-to-use vs alternatives, nor exclusions or alternative tool references.

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 cost and structured output, but omits side-effect warnings for non-GET methods, authentication requirements, timeouts, or error behavior. 'Fetch' implies read-only, but supporting POST/PUT/DELETE without caveats is a meaningful 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?

Two sentences, zero filler. 'Cost: 0.01 USDC' is useful and the rest is tight and front-loaded.

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

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

Without output schema or annotations, description provides core purpose and cost, but lacks guidance on edge cases, response format beyond JSON/XML, or error handling. It is adequate for a simple fetch but not fully complete for an arbitrary HTTP client.

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 75% (url, body, headers described; method only has enum). The description adds no extra parameter details, but the schema is already self-explanatory for most params. At 75% coverage, the baseline of 3 is appropriate.

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

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

Description clearly states verb+resource: 'Fetch structured JSON/XML data from any API endpoint.' It differentiates from sibling fetch_page/fetch_pdf/crawl by targeting APIs and data feeds, making the tool's specific role unambiguous.

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

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

'Best for REST APIs and data feeds' gives clear context for when to use. However, it does not explicitly state when not to use or name alternatives, so it stops short of a full usage guide.

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

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

No annotations are provided, so the description carries the burden. It adds useful context like the cost (0.01 USDC) and the static HTML focus, but does not disclose behavior such as redirects, timeouts, or error handling, which are typical for a fetch 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 two short sentences, front-loaded with the primary purpose and followed by a clear cost statement. Every word earns its place with no 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?

For a simple two-parameter tool, the description covers purpose and cost but omits the return format and failure behavior. Since there is no output schema and no annotations, a bit more detail about response type or limitations would make it complete.

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

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

Schema coverage is 50% (only 'url' has a description). The description does not elaborate on the 'method' parameter or add syntax details beyond the schema. It reinforces the URL purpose but does not compensate for the missing method semantics.

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

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

The description uses a specific verb ('Fetch') and clearly identifies the resource ('raw HTML content from any web page'). It also distinguishes itself from sibling tools like fetch_api and fetch_pdf by emphasizing 'raw HTML' and 'static HTML scraping'.

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

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

Provides clear use context with 'Best for static HTML scraping', but does not explicitly state when to avoid this tool in favor of alternatives. The guidance is implied rather than exclusionary.

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 disclosure burden. It adds useful context by stating the return format ('structured text with page numbers') and the cost ('0.01 USDC'), but it does not mention potential pitfalls, loading constraints, or failure 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 compact and front-loaded: the first sentence states the core action and target, the second adds return format and cost. Every word earns its place with no fluff.

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

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

For a simple one-parameter tool with no output schema, the description is largely complete. It explains the return value and pricing. It could be improved by clarifying when to use it instead of sibling fetch/crawl tools and addressing edge cases like password-protected or very large PDFs.

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

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

Schema description coverage is 100% with a single 'url' parameter fully documented in the schema. The tool description adds no further parameter-level detail, so the schema already provides adequate semantics.

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

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

The description clearly states the specific action and resource: 'Fetch and extract text content from PDF documents.' It also mentions the output format, which distinguishes it from sibling tools like fetch_page or crawl that handle non-PDF content.

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

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

The description implies usage for PDF text extraction, but it does not explicitly state when to use this tool over alternatives such as fetch_page or markdown_convert. There are no exclusions or alternative tool recommendations.

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

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

With no annotations, the description carries the full burden. It discloses the dynamic pricing model (amount + 0.01 fee), the transfer of the exact requested amount, and the auto-detection mechanism. This is substantial behavioral context, though it doesn't mention risks or error handling.

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

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

The description is concise (three sentences) and front-loaded with the purpose. The pricing and example are useful and every sentence contributes value. No waste.

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

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

For a single-parameter tool with no output schema, the description is fairly complete. It explains what will be transferred, the fee structure, and provides an example. Missing some edge-case behavior, but overall sufficient for a straightforward funding operation.

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

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

The input schema already describes the 'amount' parameter with full coverage, including the fee. The main description adds an example but doesn't introduce new parameter meaning beyond what the schema provides. Baseline of 3 is appropriate.

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

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

The description clearly states the tool's function: 'Fund your custodial wallet with USDC.' This is a specific verb and resource, and it differentiates from the sibling tool 'fund_wallet_eth' by specifying the currency (USDC).

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 the tool, including an example and the requirement that the owner wallet is auto-detected from x402 payment. It doesn't explicitly mention alternatives or exclusions, but the USDC-specific wording makes the intended use unambiguous.

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

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

With no annotations, the description carries the full burden of explaining behavior. It discloses the dynamic pricing mechanism (paying USDC equivalent of ETH amount plus a fixed fee) and the owner wallet auto-detection from x402 payment. The concrete example further clarifies the pricing model. While it doesn't mention reversibility or potential failures, it gives the essential behavioral context for this funding 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 sized, with a clear main sentence, a pricing rule sentence, and a practical example. It is front-loaded with the primary purpose. The example adds value by concretizing the pricing, though it could be seen as slightly redundant with the schema's example. No unnecessary fluff 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?

For a single-parameter funding tool, the description covers the essential aspects: what it does, how pricing works, and how the owner is determined. It is complete enough for an agent to understand the mechanics and likely outcomes. It does not specify edge cases like minimum amounts or failure modes, but given the presence of an example and clear pricing, it is sufficiently complete.

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

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

The input schema already provides a comprehensive description for the 'amount' parameter, including an example and explanation of the fee. The tool description adds a worked example of the cost implication, which is helpful but does not fundamentally expand the parameter meaning beyond what the schema already covers. With 100% schema coverage, the baseline of 3 is appropriate.

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

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

The description clearly states the tool's function: funding a custodial wallet with ETH for gas. The verb 'Fund' directly conveys the action, and specifying the resource (custodial wallet) and the specific use case (gas) gives it a clear purpose. It also distinguishes itself from siblings like fund_wallet by emphasizing the ETH-specific and x402-payment context.

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: when you need to fund a custodial wallet with ETH for gas, paying in USDC. It does not explicitly name alternatives or exclusions, but the implied usage is evident from the wording. It also clarifies the auto-detection of the owner wallet from x402 payments, which helps the agent understand the intended flow.

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

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

No annotations are provided, so the description must carry the burden. It discloses the free nature, network, and balance types, but doesn't explicitly state it's a read-only operation or describe potential side effects (though 'check' implies none).

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

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

The description is two concise sentences, immediately stating the purpose and then adding key details (free, network, balances) without any fluff.

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

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

For a single-parameter tool with no output schema, the description sufficiently covers what the tool does, what it returns, and on which network. It lacks error-handling details but the complexity is low.

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

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

The input schema provides a full description of the owner_wallet parameter. The tool description adds no new semantic information beyond what the schema already states, so a baseline score of 3 is appropriate.

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

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

The description clearly states the tool checks the balance of a custodial wallet, specifies the balances returned (ETH and USDC) and the network (Base). This distinguishes it from sibling tools like send_tokens, withdraw_wallet, and fund_wallet.

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?

It explicitly mentions the tool is FREE with no payment required, indicating when it's appropriate to use. While it doesn't name alternatives, the context is clear for a balance-checking task.

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

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

No annotations are provided, so the description carries the full burden. It discloses the cost (0.01 USDC), which is a behavioral trait, but does not mention potential errors, rate limits, authentication, or safety profile. The description is thin on behavioral context beyond the basic conversion and cost.

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

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

The description is extremely concise, with two short sentences and a cost note. Each phrase adds value: the conversion action, the LLM use case, and the cost. There is no wasted text.

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

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

For a simple one-parameter tool, the description covers the core function and return format (Markdown), and adds cost information. It does not explain output schema or error handling, but given the simplicity and absence of an output schema, it is largely complete.

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

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

The schema already fully documents the single 'url' parameter with a clear description. The tool description adds no additional parameter semantics, so 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 converts a web page to clean Markdown format, specifying the verb and resource. It distinguishes itself from siblings like fetch_page (raw HTML) and extract (structured data) through the output format, though it does not explicitly name alternative tools.

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

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

The description suggests usage for LLM consumption, providing a clear context. However, it does not explicitly contrast with alternative tools or explain when not to use it, leaving usage guidance implied rather than explicit.

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 must carry the behavioral disclosure burden. It adds two useful traits: the tool is 'FREE' and it 'returns cost breakdown for each tool.' However, it does not mention any other behaviors such as whether network calls are made, authentication requirements, or potential rate limits, leaving some gaps.

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

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

The description is two short sentences, front-loaded with the main purpose and immediately followed by a key value proposition ('FREE'). Every word earns its place; there is no filler or redundancy.

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

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

For a zero-parameter, no-output-schema tool, the description sufficiently covers the main aspects: what it does, that it's free, and the type of return value. It could be slightly more specific about the return structure, but given the simplicity, it is largely complete.

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

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

The tool has zero parameters, so schema coverage is trivially 100%. Per rubric, the baseline is 4, and the description does not need to explain any parameters. It adds context about the output (cost breakdown), which aligns with the parameter-free nature.

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

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

The description clearly states the tool's function with a specific verb and resource: 'Get pricing information for all MCP tools.' It distinguishes itself from sibling tools like coinbase_price or x402_proxy_price by explicitly scoping to 'all MCP tools' rather than a specific asset or service.

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 a clear use case: when you need pricing/cost details for MCP tools themselves. It provides context but does not explicitly mention when not to use it or name alternative tools, so it lacks the full 'when-not' guidance of a 5.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It adds useful context about the cost ('0.01 USDC') and the backing source (Nansen Token Screener). However, it does not disclose response format, rate limits, or whether the operation is read-only. This is a moderate level of 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 three concise sentences that front-load the purpose, include concrete examples, and state the cost. Every sentence earns its place with no unnecessary 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?

Without an output schema or annotations, the description should explain what the user gets back and how this differs from sibling tools. It does not describe the response structure or clarify the 'holdings' aspect in the name. It is adequate for a simple screening tool but leaves notable 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 100%, so the baseline is 3. The description adds example natural-language queries that clarify the 'input' parameter, but it does not explain the relationship between 'input' and 'query' or between 'chain' and 'chains'. The added value over the schema is marginal.

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 ('Screen tokens') and the resource ('Smart Money activity using Nansen Token Screener'). However, it does not explicitly distinguish this from the sibling tool 'nansen_smart_money_netflows', and the tool name 'holdings' is not directly explained. The core purpose is nevertheless clear.

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 natural language query examples ('what are whales buying on base?') that imply when the tool should be used. However, it does not explicitly contrast with alternatives or state when not to use it. The usage context is implied rather than explicitly guided.

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

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

No annotations are provided, so the description must carry the transparency burden. It discloses the cost (0.01 USDC) and natural language support, which are useful. However, it does not explicitly state whether this is a read-only operation, describe return format, or mention any rate limits or prerequisites, leaving some behavioral ambiguity.

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

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

The description is two sentences, front-loaded with the core purpose, followed by natural language examples and cost. Every sentence provides distinct value with no redundancy or filler.

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

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

Given the moderate complexity (8 optional parameters, no output schema), the description covers the essential context: what the tool does, how to phrase queries, and cost. It does not explicitly describe response structure, but the absence of an output schema and the tool's tracking nature make this less critical. The default parameters and enum are documented in the schema, so the description is reasonably complete.

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

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

Schema description coverage is 100%, with each parameter documented clearly (chain, input, limit, etc.). The tool description does not add parameter-specific semantics beyond the schema, so it stays at the baseline of 3. The natural language examples imply 'input' usage but do not add technical details.

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

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

The description clearly states the tool tracks net capital flows from Smart Money wallets, with specific examples of natural language queries. This distinguishes it from sibling tools like nansen_smart_money_holdings, which focus on holdings rather than flows.

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 concrete usage examples ('are whales accumulating ETH?', 'smart money flows for PEPE last 7 days') that clarify the intended query style. However, it does not explicitly mention when to avoid this tool or name alternatives, but the natural language focus and flow-tracking purpose give a clear sense of appropriate 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, the description discloses useful behavioral traits: it supports natural language, auto-resolves symbols to addresses, and costs 0.01 USDC. However, it does not mention output format, error behavior, rate limits, or any authentication requirements, leaving significant gaps in behavioral 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 three sentences, front-loaded with the core purpose, and contains no redundant information. Every sentence earns its place: purpose, usage examples, and cost.

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

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

The tool has 6 optional params and no output schema, but the description gives enough to select it. Missing return-value details and more explicit guidance on when this tool supersedes the specific Nansen siblings, leaving some context incomplete for an agent to predict behavior 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 coverage is 100%, but the description adds value by explaining auto-resolution of symbols to addresses and showing how the 'input' parameter works with natural-language queries. This enriches the parameter semantics beyond the schema's straightforward field 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 it provides 'Full token analytics' and gives concrete natural-language examples, making its purpose evident. It distinguishes itself from the more specific Nansen sibling tools (holdings, netflows, wallet profiler) by being a general-purpose token analytics interface, though it lacks a precise verb like 'query' or 'analyze'.

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

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

The description implies usage for broad token questions and shows example queries ('analyze VIRTUAL token', 'who holds the most PEPE?'), giving clear context for when to use it. It does not explicitly mention alternatives or exclusions, but the sibling tools are clearly more specialized, so the context is sufficient.

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

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

No annotations are provided, so the description carries the burden. It discloses the cost (0.01 USDC) and the nature of the operation (returns data, no mention of mutation). However, it does not state whether the tool is read-only, any prerequisites, or error behavior, leaving gaps in behavioral disclosure.

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

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

The description is three sentences, front-loaded with the core purpose. Each sentence provides distinct information: purpose, usage examples, return types, and cost. 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?

The description explains the return values (balances, labels, transactions) which is necessary since there's no output schema. It also covers the natural language capability. However, with 7 optional parameters, it doesn't clarify which parameter to prefer or how the tool behaves when multiple are provided, so it's not fully complete.

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

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

Schema description coverage is 100%, so the baseline is 3. The description adds usage examples for natural language queries ('profile vitalik.eth') that clarify how to use the input/query parameters but does not add significant new semantics beyond the schema.

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

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

The description states 'Comprehensive wallet analysis' and gives concrete examples of queries and return types (balances, Nansen labels, transactions). It clearly indicates the tool profiles wallets, distinguishing it from sibling tools like get_wallet_balance by offering a broader scope. However, it does not explicitly name alternatives, so it's not a full 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 implies the tool is for comprehensive profiling via the word 'comprehensive' and the list of return types, but it does not explicitly state when to use this tool versus simpler alternatives like get_wallet_balance. There is no 'use X instead' guidance, making usage context implied rather than explicit.

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

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

With no annotations, the description must carry the full burden of behavioral disclosure. It discloses the cost (0.01 USDC) and auto-detection of the sender from x402 payment, which is useful. However, it does not mention irreversibility, error handling, or what happens on insufficient balance, leaving some gaps in transparency.

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

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

The description is concise at four sentences, with the primary action front-loaded in the first sentence. It efficiently includes cost, sender detection, and use cases without redundant phrasing. Every sentence adds value.

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

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

For a simple 2-parameter tool with no output schema, the description covers the essential aspects: purpose, cost, sender mechanism, and common use cases. It is slightly incomplete in explaining post-send behavior or error conditions, but given the tool's simplicity and full schema coverage, it is largely sufficient.

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

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

Schema coverage is 100% (both 'amount' and 'to_address' have descriptions), so the baseline is 3. The description adds no additional parameter-level details beyond the schema; it only restates the general purpose. Thus, it meets the baseline without adding extra semantic 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: 'Send USDC from your custodial wallet to ANY wallet address.' It specifies the resource (USDC), the source (custodial wallet), and the scope (any address). It also lists explicit use cases ('pay other agents, transfer to exchanges'), which distinguishes it from sibling tools like swap or withdraw_wallet.

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 usage context via 'Use this to pay other agents, transfer to exchanges, or send to any address.' However, it does not mention when not to use the tool or name alternative tools, so it falls short of full explicit when/when-not 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, the description carries the full burden. It discloses key behaviors: uses 2Captcha, bypasses reCAPTCHA/hCaptcha, pairs with Claude AI for content retrieval, and includes a cost of 0.01 USDC. This goes beyond basic functionality and reveals operational dependencies and pricing. It does not cover failure modes or rate limits, but the provided detail is valuable.

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

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

The description is two sentences long, starts with the core purpose, and front-loads the most important information. Every clause is informative: purpose, method, delegation, and cost. There is no filler or redundancy, making it highly efficient.

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

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

The tool has 4 parameters, no output schema, and no annotations. The description explains the overall workflow and cost but leaves ambiguity about what exactly is returned (e.g., content directly or a tool recommendation) and lacks failure/success indicators. Given the lack of output schema, the description should clarify return format; 'extract content' is vague. It is adequate but not fully complete for a tool with these 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 100%, so the baseline is 3. The description does not add any parameter-specific meaning beyond the schema; it mentions 'extract content' which aligns with the intent parameter but does not elaborate on any parameter nuances. The schema already fully documents each parameter, so the description adds no incremental value here.

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 a specific verb and resource: 'Solve captchas on protected pages and extract content.' It distinguishes itself from sibling tools by being the only one addressing captcha bypass, and it names specific captcha types (reCAPTCHA/hCaptcha). This is unambiguous and action-oriented.

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: 'on protected pages' and explains that after solving, Claude AI selects the best tool to retrieve content. This gives a clear scenario for when to use the tool. However, it does not explicitly mention alternatives or when not to use it, so it lacks full exclusions compared to a direct comparison.

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

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

The description discloses the cost (0.10 USDC), security differences between modes, and that bridge mode returns a URL. However, it does not disclose the return format for private key/Privy modes (e.g., transaction hash) nor potential side effects like token approval or failure behavior. With no annotations, the description has a high burden but remains incomplete.

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 efficient, using sections for the three modes and clearly stating the cost. It front-loads the main purpose and avoids excessive repetition of schema details. While it is somewhat long, every sentence adds value and the formatting 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 tool with 9 parameters, no output schema, and no annotations, the description covers modes, cost, and wallet prerequisites. However, it lacks information about return values, error handling, and does not mention slippage defaults (though those are in the schema). It also omits the need for wallet funds, leaving gaps for an agent to fully understand the tool's behavior.

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

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

The input schema has 100% coverage with each parameter having a description. The description reinforces which parameter maps to which mode, but this is already present in the schema descriptions. It does not introduce significant new parameter-specific semantics beyond the schema, so it meets but does not exceed the baseline.

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 'Execute a token swap on Base via 0x DEX Aggregator,' specifying the verb, resource, and context. It further differentiates itself by detailing three distinct operational modes, which distinguishes it from any potential sibling tools.

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

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

The description provides explicit guidance on which mode to use: Privy mode is recommended, private key mode is noted as less secure, and bridge mode is for browser sign-in. It also references create_wallet as a prerequisite. It stops short of explicitly stating when not to use the tool or naming alternative tools.

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

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

No annotations are provided; the description states it is FREE and implies a non-mutating verification action, but it does not disclose return format or guarantees about state changes. Some burden is met but not fully detailed.

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

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

Two short sentences, front-loaded with purpose, cost note appended. No redundant wording.

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?

Simple tool with no output schema; description gives purpose and cost but omits explicit return value or error behavior. Still adequate for selection given low complexity.

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

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

All three parameters are described in schema (100% coverage); the description does not add additional parameter-level detail. Baseline 3 applies.

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

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

Description uses specific verb 'verify' plus resource 'wallet signature (EIP-191)' and purpose 'to authenticate an agent'. It clearly distinguishes from sibling financial/transaction tools.

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

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

Mentions authentication context and adds 'FREE - no payment required', implying it is a lightweight utility. However, it does not explicitly list alternatives or exclusions, so it provides clear context but no exclusions.

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

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

With no annotations, the description carries the transparency burden. It discloses the cost (0.01 USDC) and the auto-detection mechanism, which are significant behavioral traits. It does not cover reversibility or failure modes, but for a simple withdrawal, this is adequate.

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

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

The description is concise, with two sentences conveying purpose, cost, and destination. No unnecessary words, and the key information is front-loaded.

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

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

For a tool with one parameter and no output schema, the description provides sufficient context: purpose, cost, and destination auto-detection. It does not explain the result or confirmation, but that is not essential for this simple withdrawal operation.

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

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

The only parameter, amount, is fully described in the schema with 100% coverage, including an example and a balance requirement. The description does not add further parameter-specific detail, so the baseline of 3 is appropriate.

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

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

The description clearly states the specific action (withdraw USDC), the source (custodial wallet), the destination (owner wallet), and adds cost and auto-detection details. This distinguishes it from sibling tools like send_tokens or fund_wallet, which are 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 implies the use case: withdrawing USDC from the custodial wallet to the owner wallet, with the owner auto-detected via x402 payment. It provides clear context but does not explicitly mention when not to use this tool or name alternative tools.

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

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

No annotations are provided, so the description must disclose behavioral traits. It mentions 'automatic payment' and pricing, but omits critical behaviors such as the two-step 402 challenge flow (initial response then payment proof), the requirement for a funded wallet, and the fact that this will actually spend USDC. The paymentProof parameter in the schema hints at the flow, but the description itself lacks this transparency and side-effect disclosure.

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

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

The description is three short, information-dense sentences. It front-loads the primary purpose, then adds pricing and network details. No redundant or extraneous wording. Every sentence earns its place.

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

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

The tool has moderate complexity (5 params, no output schema, no annotations) and involves financial transactions. The description explains pricing and network but not the overall workflow, prerequisites (e.g., funded wallet), error conditions, or return behavior. The paymentProof parameter implies a two-step process, but the description doesn't provide enough context for an agent to invoke the tool correctly in all scenarios.

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

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

Schema description coverage is 100%, so the schema already documents all five parameters with descriptions. The tool description adds no additional parameter-level meaning beyond what's in the schema. Baseline 3 applies because the schema does the heavy lifting and the description doesn't need to compensate.

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

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

The description clearly states the tool's function: 'Access x402-protected APIs with automatic payment.' This is a specific verb+resource combination that distinguishes it from sibling tools like x402_proxy_price and x402_send. It also adds relevant details about dynamic pricing and USDC on Base, further clarifying its purpose.

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

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

The description implies when to use the tool (for accessing x402-protected APIs when automatic payment is desired), but it does not explicitly mention alternatives or exclusions. Sibling tools exist (e.g., x402_proxy_price, x402_send), yet no guidance is given on when to choose one over the other. Usage is inferred but not directly spelled out.

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

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

With no annotations, the description bears the full burden of behavioral disclosure. It reveals that the tool is FREE and returns a cost breakdown, which implies a read-only probe. However, it does not explicitly state that it does not execute the actual x402 request or what side effects might occur (e.g., hitting the target URL for pricing). The description adds some transparency but lacks explicit guarantees about safety and behavior beyond the free aspect.

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

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

The description is extremely concise, consisting of one short sentence with a clarifying phrase. It front-loads the core purpose ('Get dynamic pricing') and appends essential behavioral details about cost breakdown and free status. Every word earns its place, with no unnecessary filler or repetition of schema information.

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

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

For a tool with a single parameter and no output schema, the description is fairly informative (mentions cost components and free nature). However, it omits details about the return format (e.g., string, number, units) and does not clarify whether the tool actually contacts the target URL to probe pricing. It is adequate but could be more complete for an agent to fully anticipate outcomes.

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

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

The input schema has 100% coverage: targetUrl is described as 'The x402-protected target URL to probe for pricing.' The tool description adds minimal extra meaning beyond that, merely contextualizing it as part of 'proxy requests' and 'target cost.' Since the schema already covers the parameter fully, the description provides no significant additional semantics, warranting the baseline score of 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: 'Get dynamic pricing for x402 proxy requests.' It specifies the verb (Get), resource (dynamic pricing), and scope (x402 proxy requests), and distinguishes itself from siblings like x402_proxy or x402_send by focusing solely on pricing. The added detail about returning total cost (proxy fee + target cost) further clarifies its specific role.

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

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

The description implies usage when pricing information is needed ('Get dynamic pricing') and notes it's FREE, suggesting it can be used without cost. However, it does not explicitly state when to use this tool versus alternatives like x402_proxy or x402_send, nor does it provide exclusions or prerequisites. Usage context is present but not fully explicit.

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

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

With no annotations, the description carries the full burden and explains the two-step fee and transfer flow, including the 0.01 USDC platform fee and that tokens go from the sender to recipient. It lacks error-case details but is genuinely transparent for a send 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 three sentences, front-loaded with the main purpose, followed by the stepwise flow and use cases. No wasted words.

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

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

For a two-parameter tool with no output schema, the description covers purpose, behavior, fee, and use cases, making it sufficiently complete.

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

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

Schema coverage is 100%, so the baseline is 3. The description adds no additional parameter detail beyond the schema's descriptions of amount and to_address.

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

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

The description clearly states the tool's function with a specific verb ('Send'), resource ('USDC'), and scope ('to ANY wallet address via x402 payment'). It distinguishes from siblings by referencing the x402 payment protocol and the direct transfer mechanism.

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?

It provides clear use cases—'paying agents, tipping, or sending to any address'—but does not explicitly mention alternatives or exclusions, so it falls short of a 5.

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

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

No annotations are provided, so the description carries full burden. It does disclose that the tool is FREE and lists the returned data types, which add some context beyond the schema. However, it does not mention whether it is a read-only operation, any rate limits, or what 'comprehensive' means in terms of data coverage. Thus, it provides moderate transparency.

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

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

The description is a single, well-structured sentence of about 26 words that front-loads the core action and data types. However, the phrase 'FREE - no payment required' is redundant, as 'FREE' alone implies no payment, so it is not perfectly 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?

For a read-only tool with two well-documented parameters and no output schema, the description provides a clear list of the returned data (NFTs minted, owned, creator profile, total mints/collections, estimated earnings). It lacks explicit mention of output format or corner cases, but it is sufficient for most use cases. The lack of annotations and output schema is offset by the clear purpose and data list.

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

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

Schema description coverage is 100%, so the schema already describes 'chain' and 'address' parameters. The description does not add any additional parameter semantics or examples, so it scores at the baseline 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 'Get comprehensive Zora NFT wallet data' with a specific resource (Zora NFT wallets) and lists concrete data points (NFTs minted, NFTs owned, creator profile, total mints/collections, estimated earnings). This distinguishes it from sibling tools like nansen_wallet_profiler or get_wallet_balance, which are for other platforms or generic balances.

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

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

The description implies usage for Zora-specific NFT wallet data but does not explicitly say when to use this tool over alternatives or exclude other tools. There is no mention of conditions like 'use this when you need Zora data' or 'not for general wallet balance checks,' so it relies on implied context.

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