402 Dispatcher

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

Annotations are absent, so the description carries the full burden. It does disclose important behavioral facts: an inbound payment of $0.01 USDC is required and the call is paid through the x402 dispatcher treasury. However, it does not mention response format, failure behavior, refunds, or whether the operation is reversible, which leaves meaningful gaps for a paid remote call.

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 carry the payment requirement, the action, the treasury routing, and the accepted input forms. There is no filler or repetition; the most decision-relevant 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?

There is no output schema, yet the description does not state what the tool returns, such as the upstream response body, status code, or error behavior. It adequately covers the required parameter and accepted input sources, and the schema supplies body/query details, but for a paid, potentially mutating dispatcher call the absence of return-value and failure guidance keeps it from being 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 coverage is 100%, so the baseline is 3. The description adds value by explaining the accepted values for tool_name_or_url: a registered tool_name from list_discovered_apis / search_bazaar, or a full resource URL. It does not comment on body or query parameters, but the schema already documents those as optional with their own 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 states a specific action: pay for and call a discovered Bazaar HTTP resource. It also names the input source (tool_name from list_discovered_apis / search_bazaar, or a full URL), which sets it apart from discovery-only sibling tools. It could more explicitly distinguish itself from route_and_call and quote_route, but the core purpose is 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 gives clear context: use this after discovering a resource via list_discovered_apis or search_bazaar, and pass either the tool_name or URL. It does not explicitly say when not to use it or name alternatives like route_and_call, but the flow from discovery to paid invocation is implied strongly enough for an agent to select it.

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

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

With no annotations provided, the description carries the full behavioral burden. It adds useful context: the call is free, the data comes from paid dispatcher calls, and omitting the URL returns the full list. The read-only nature is evident from 'Show,' though output shape and rate limits are not disclosed.

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 compact, with no filler. It front-loads the cost signal ('FREE'), then states the core behavior, then the parameter behavior. Every sentence earns its place.

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

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

For a simple one-parameter, zero-required read-only stats tool, this is largely complete: action, data source, and list-all behavior are all covered. The absence of an output schema is partially offset by naming the actual stats returned, though aggregation or time-range details are unspecified.

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 optional 'url' parameter, so the baseline is 3. The description adds meaning beyond the schema by clarifying that omitting the URL lists all stats, which directly affects how an agent should invoke the tool.

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

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

The description clearly states the action ('Show') and the resource (success rate and latency stats) with a specific data source (x402dispatcher paid calls). It is distinct enough from sibling metric tools, though it does not explicitly name or differentiate from 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 implies when to use the tool—when API performance stats are needed—and provides a key invocation hint ('Omit url to list all'). However, it gives no explicit when-not-to-use guidance or comparison with sibling tools.

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

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

No annotations are provided, so the description carries the full behavioral burden. It communicates a read-only listing action and identifies the data source, and it hints at an operator-level access requirement. However, it does not disclose output shape, ordering guarantees behind 'recent', pagination behavior, or permission details.

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

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

The description is a single compact sentence with no filler. The access hint is front-loaded, and every remaining word adds meaning to the core action and resource.

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

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

For a simple tool with two optional parameters and no output schema, the description provides sufficient context to call it: it states the action, resource, and filter categories. It lacks explicit output field details and ordering semantics, but that is a minor gap for a list-style 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 schema already documents both parameters with 100% coverage, so the baseline applies. The description maps the ledger categories to the enum values (money-in/out/markup → in/out/markup) and loosely motivates the limit parameter via 'recent', but it does not add substantial meaning 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 uses a specific verb ('List') and names the exact resource: recent money-in / money-out / markup ledger entries from the V7 cashflow store. It clearly distinguishes this from financial siblings like get_pnl by focusing on raw ledger entries rather than computed profit/loss numbers.

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

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

There is no guidance about when to choose this tool over related alternatives such as get_pnl or get_paywall_status. The 'FREE (operator)' prefix hints at an access or cost characteristic, but it does not explain selection criteria, prerequisites, or when this tool should be avoided.

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 and a description centered on payment flow, the tool's actual behavior (e.g., return format, errors, rate limits) is not disclosed. The payment mention is confusing and does not clarify the prediction 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 in length but poorly structured, mixing payment instructions with the tool's purpose. It is not a clear, well-organized sentence but a run-on that obscures the main function.

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

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

The description lacks essential context about MBTA predictions, such as what data is returned, how to interpret results, or any prerequisites. It is incomplete and leaves an agent without sufficient information to decide on usage.

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 clear description for the single parameter `stop_id` with examples (`place-pktrm` or `70065`), which explains its meaning and format well. The tool description adds no further detail, but the schema itself is strong.

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 focuses on payment and settlement details rather than stating what the tool does. It mentions 'return live MBTA predictions' but buries it under payment instructions, making the purpose unclear and misleading.

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 does not indicate appropriate contexts, filtering scenarios, or distinctions from sibling tools.

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

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

With no annotations, the description carries the burden of explaining behavior. It adds the useful 'FREE' cost signal and describes a read-only 'show' operation, but it does not explicitly state that the tool has no side effects or describe the response format or error cases.

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, tightly scoped sentence with no filler. The 'FREE' marker is front-loaded and the data fields are listed efficiently.

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

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

For a zero-parameter status-checking tool with no output schema, the description names the key pieces of returned information and identifies the domain. It could be slightly richer by stating value types (e.g., boolean for enabled, currency for price), but it is substantially complete.

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

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

The tool has zero parameters and the schema is empty, so there is nothing for the description to add about inputs. The described return fields (enabled, price, network, payTo) help set expectations for what the no-argument call will reveal.

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 ('Show') and a precise resource ('inbound x402 paywall status'), then enumerates the returned fields: enabled, price, network, and Merchant payTo address. This clearly distinguishes it from the many sibling weather, chain, and API-calling 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 intended use is implied: call this to inspect whether the inbound x402 paywall is enabled and what its configuration is. However, the description does not explicitly state when to prefer this tool over alternatives like call_x402_api or quote_route.

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 is the sole source of behavioral information. It states the tool is FREE and summarizes from the cashflow ledger, but it does not disclose side effects, required permissions, rate limits, return format, or whether it is strictly 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 concise and well-structured, packing the tool's main purpose, output components, and source into a single sentence without unnecessary fluff or repetition.

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 names the expected output components (revenue, COGS, markup transfers, gross profit) and the data source (cashflow ledger), giving the agent enough context to call the tool. It lacks an explicit output schema or details about edge cases, but the core context is present.

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, `since`, is already documented in the schema as an optional ISO timestamp filter. The tool description adds no additional meaning beyond the schema, so parameter semantics are adequate but not enhanced.

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

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

The description clearly states the tool's purpose: to summarize PnL from the cashflow ledger, listing the specific components it computes (revenue, COGS, markup transfers, gross profit). This distinguishes it from related tools like get_cashflow, which likely return raw ledger entries.

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 should be used when a PnL summary is needed, and mentions it is FREE and operator-scoped. However, it does not explicitly state when to prefer this over get_cashflow or other alternatives, so the usage guidance is only implied.

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 disclosing behavior. It does disclose that the call is FREE, that the list is 'currently registered' (suggesting a live snapshot), and that results are scoped to Base and MAX_PRICE_USD. It does not describe return format, ordering, pagination, or rate limits, leaving notable gaps for a read-only list 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 just two short sentences with no wasted words. 'FREE.' is front-loaded and the action verb 'List' appears immediately. It avoids repeating the title and conveys the core information efficiently.

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

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

For a zero-parameter tool with no output schema, the description explains the source and scope but not what the returned items look like or how to consume them. An agent knows it will get a list of discovered APIs but cannot tell whether entries are endpoint URLs, names, IDs, or prices, and gets no guidance on ordering or output shape. This is a moderate 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?

The tool has zero parameters and an empty schema, so the baseline is 4. The description references filters like Base and MAX_PRICE_USD, but these are internal constraints rather than call arguments. There are no parameter meanings to add beyond what the schema already trivially covers.

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 a specific verb ('List') and resource ('x402dispatcher APIs') and narrows the scope with 'Bazaar discovery (Base, within MAX_PRICE_USD)'. This makes the tool's basic function clear and distinguishes it from siblings like list_verified_apis. However, terms like 'Bazaar discovery' and 'MAX_PRICE_USD' are left unexplained, so the purpose isn't fully self-contained.

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 when-to-use guidance is provided. The description does not differentiate this from the closely related sibling list_verified_apis or mention alternative tools. An agent must rely on the name 'discovered' to infer this is for unverified APIs, which is implied rather than 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, the description carries the transparency burden. It discloses the read-only nature via 'List,' the dynamic filtering behavior via 'currently qualify,' and the evaluation basis through 'success/latency history,' plus a 'FREE' cost signal. It does not explain pagination or return formatting, but those are minor for a parameterless listing 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 entire description is one short sentence plus a cost label. It front-loads the important cost signal, states the exact resource and selection criterion, and contains no filler.

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

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

For a parameterless list operation, the description sufficiently tells the agent what is returned and why. It could be slightly more complete by contrasting with list_discovered_apis or describing the returned fields, but nothing essential to invoking this tool is missing.

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

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

There are zero parameters, so the schema already fully covers invocation and the 100% schema description coverage confirms nothing is undocumented. The baseline of 4 applies because no parameter documentation is needed.

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

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

The description names a specific action and object: 'List upstream APIs that currently qualify for the Verified routing tier.' It also adds the selection basis ('success/latency history'), which clearly differentiates it from sibling list_discovered_apis.

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

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

The phrase 'currently qualify for the Verified routing tier' makes it clear this tool is for retrieving verified-tier APIs, and the zero-parameter schema means there is no ambiguity about invocation. It does not explicitly mention alternatives or when-not-to-use conditions, so it stops 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?

With no annotations provided, the description carries the disclosure burden. It explicitly discloses that the tool is free, does not pay, and behaves differently per tier: economy sorts by price, while verified filters to reliable APIs and ranks by a success/latency/price score. This is meaningful behavioral detail for an agent deciding whether to invoke it.

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

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

The description is compact and front-loaded: it opens with 'FREE,' states the core action, and compresses tier behavior into two short clauses. The only minor redundancy is that 'FREE' and 'Does not pay' convey the same idea, but overall every sentence earns its place.

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

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

Given the tool's modest complexity, 100% schema coverage, and no output schema, the description covers the core behavior, tier semantics, and the critical no-payment constraint. It does not explicitly describe the return shape or contrast with sibling tools like search_bazaar or route_and_call, but the limit parameter already indicates ranked candidates are returned.

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

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

The input schema covers all parameters, so the baseline is 3. The description adds value beyond the schema by explaining the verified tier's ranking components ('success/latency/price score') and clarifying that economy 'sorts by price.' It does not describe limit or max_price_usd, but the schema already documents those adequately.

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 action and resource: 'Search the x402 Bazaar for APIs matching a task and rank them.' It also distinguishes itself from execution/payment tools with 'Does not pay,' which separates quote_route from siblings like route_and_call or call_x402_api.

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: use this tool to find and rank candidate APIs without paying. The tier explanation gives concrete selection guidance for economy versus verified. It does not explicitly name alternative tools or exclusion conditions, but 'Does not pay' and the ranking focus make the intended use apparent.

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 and discloses several important behaviors: it is a paid flow ($0.01 USDC inbound), money is paid upstream from Treasury, and errors trigger failover. This is meaningful for an agent deciding whether to invoke a financial tool. It stops short of describing permissions, reversibility, or detailed error/return behavior, but it provides genuinely useful 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 compact: three sentences cover payment, routing, tiers, and failover. The first sentence is a dense run-on with somewhat awkward phrasing, so it is not maximally readable, but every part contributes and 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?

Given a complex financial/routing tool with no output schema, the description covers the main workflow and tier semantics but leaves the return shape vague ('return data') and does not describe output/error structure or how this tool relates to quote-only siblings. It is adequate for initial selection but not complete for an agent that needs to know what a successful call returns or what failure surfaces look like.

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

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

Schema coverage is 100%, so the baseline is 3; the description adds real semantic value by defining economy as cheapest-first V3 and verified as reliability-scored V4, which enriches the tier enum. Framing 'failover on errors' also connects to the max_attempts parameter without repeating 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 names a concrete multi-step operation: collect a paid inbound fee, route a natural-language task to a Base x402 API, pay upstream from Treasury, and return data. This goes beyond the tool title and differentiates it from direct-call siblings by mentioning routing and payment. It is not a perfectly crisp one-liner due to jargon, but the core purpose is identifiable.

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 explains how to choose routing tiers (economy vs verified) and states failover behavior, which helps an agent select parameters. It does not explicitly tell an agent when to use this tool instead of quote_route or call_x402_api, nor when not to use it. The guidance is present but mostly 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 carries the full burden. It discloses that the tool is free and that it caches matches, which is a side effect. However, it omits other behavioral traits like rate limits, authentication requirements, or whether the operation is read-only. For a tool with no annotations, this is moderate but incomplete coverage.

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

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

The description is a single, front-loaded sentence that wastes no words. It begins with the cost note 'FREE' and immediately states the purpose and side effect, making it 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?

With no output schema, the description should hint at return behavior, but it only says 'cache matches' without stating what is returned. The constant MAX_PRICE_USD is mentioned without explanation, which could confuse agents. It is adequate for a simple search tool but leaves gaps regarding output format and the price cap.

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?

Both parameters (limit and query) have descriptions in the schema, covering 100% of parameters, so the baseline is 3. The tool description adds no additional meaning to the parameters beyond what the schema already states—it does not clarify query semantics or limit behavior further.

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

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

The description clearly states the tool searches a public catalog for paid APIs under a price cap and caches results for call_x402_api. It names the specific resource (Coinbase x402 Bazaar), the action (search), and the filtering criterion (price), distinguishing it from sibling list tools like list_discovered_apis and list_verified_apis.

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 its role as a precursor to call_x402_api by stating it caches matches for that tool, which signals when to use it. However, it does not explicitly contrast with alternatives or state when not to use it, such as when you want all APIs regardless of price.

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 paid nature (cost per call) and specifies the HTTP method (GET). It also indicates it proxies an upstream request. While it doesn't delve into error handling or rate limits, given the absence of annotations, this is useful and adds context beyond the schema. No contradictions.

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 relatively long but well-structured, covering pricing, functionality, alternatives, input formats, and an example in a logical flow. It is informative without being redundant, though slightly verbose. The key details are front-loaded, making it easy to scan.

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

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

The tool is simple and self-contained. The description explains what it returns, how to specify inputs, and when to use it, with an example. Since there is no output schema, the return fields are described adequately. All necessary information for a correct call is present, making 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?

The schema only defines generic 'body' and 'query' objects with additionalProperties, so the actual parameters (coins, currency) are not structurally defined. The description compensates by naming the parameters and giving examples, but it doesn't specify whether they are required or optional, nor their exact locations in the request (query vs body). This partial coverage warrants a mid-range 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: providing live crypto prices for one or many coins, returning last price, 24h change, volume, and market cap. It also distinguishes it from siblings by explicitly naming alternatives for ranked market-cap tables and candles, making it easy to select.

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 gives explicit guidance on when to use this tool: as the simplest crypto price read, and when to use alternatives. It also explains the input formats (ticker symbols for top ~50, CoinGecko IDs for all) and provides an example query, leaving no ambiguity about invocation.

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 behavioral burden. It discloses the paid fee structure ($0.0033 inbound and proxy), that data is live government data requiring no API key, and that the call is a GET returning clean JSON. This goes well beyond the generic schema and helps an agent understand cost, auth, and expected response shape.

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 dense line that packs purpose, output fields, cost, data source, method, and an example. It is front-loaded with the core purpose and every piece of information is relevant, though the upstream URL and pricing could arguably be trimmed without losing the main message.

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 GET API with no output schema, the description provides return fields, an example parameter, and cost/auth context. It lacks explicit error behavior or edge-case handling (e.g., invalid state code, missing area), but the core information needed to invoke the tool correctly is present.

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 only describes generic 'body' and 'query' objects with no specific parameters, so the description adds essential meaning by showing the ?area=CA query parameter and an example query object. This compensates for the schema's lack of domain-specific parameter documentation.

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

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

The description clearly states the tool returns Active National Weather Service alerts for a US state, and enumerates the specific output fields (event, severity, headline, affected areas, onset/expiry). This distinguishes it from sibling weather tools that provide forecasts, current conditions, or METARs.

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

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

The description gives a clear usage context: US state alerts from the NWS, with a concrete example query ?area=CA and the HTTP method GET. It does not explicitly name alternative sibling tools or say when not to use it, but the specificity of 'alerts for a US state' provides enough context for an agent to select it over other weather 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?

With no annotations, the description carries the full burden. It discloses the paid nature, upstream URL, and GET method, but does not clarify side effects, response format, rate limits, or whether 'geocoded' means the caller supplies coordinates or the upstream resolves city names. It is not misleading, just 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 a single compact sentence that front-loads pricing, then covers purpose, upstream URL, HTTP method, and a concrete example. No words are wasted and every element serves tool selection or invocation.

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 GET weather proxy with no output schema, the description provides enough to call it correctly: upstream, method, example query, and forecast range. It could be more complete by stating whether 'days' is optional and explaining the response, but these are minor for this task.

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 only provides generic 'body' and 'query' containers with no domain parameters. The description compensates by giving a concrete example query using 'city' and 'days', and states the 1-7 day range. It adds meaning beyond the generic schema, though it does not formally define required vs optional fields.

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 opens with a specific action and object: 'Get current weather conditions and a one-to-seven-day forecast for a geocoded location from Open-Meteo.' It names the upstream service, making it distinguishable from the many sibling weather tools even without inspecting 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?

The intended use is implied by 'Get current weather...' and the example query, but there is no explicit when-to-use guidance, no exclusions, and no mention of alternative weather siblings. Given the large sibling set, explicit routing would have been valuable.

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 behavioral burden and does so unusually well. It discloses the paid cost, the fallback behavior between NOAA/NWS observation and MET Norway model, explicit labeling of data type, bounded SI fields, source provenance, and the upstream HTTP method and URL.

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 dense sentence that front-loads the cost signal and then efficiently covers input, source behavior, output labeling, units, provenance, and upstream details. Every phrase earns its place with no filler or repetition.

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 output schema and no annotations, the description does a strong job of explaining what is returned: a current weather snapshot labeled as observation or model, with bounded SI fields and source provenance. The main completeness gap is the lack of concrete parameter names or an example showing how to specify the city or coordinates in the body/query.

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 descriptions are generic wrappers for 'body' and 'query', so the description adds some meaning by specifying city/locality name or exact coordinates as accepted inputs. However, it does not explain how those inputs map to specific body or query fields, which is a meaningful gap for actually invoking the tool correctly.

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: 'Get one current weather snapshot' for a city/locality name or exact coordinates. It also differentiates the tool by specifying the NOAA/NWS or MET Norway source and the explicit observation-versus-model labeling, making it easy to distinguish from sibling forecast and alert weather 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 establishes clear context: this tool is for a single current-weather snapshot, not forecasts or alerts. It does not explicitly name alternative sibling tools or state exclusion conditions, but the 'current weather' framing and source details give adequate guidance for when this tool is appropriate.

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 only behavioral detail provided is the cost ('[PAID inbound $0.0033 → then proxy $0.0033]'). It does not mention authentication requirements, rate limits, error handling, or side effects. Since annotations are absent, the description fails to fully disclose the tool's behavioral contract.

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 front-loads the core purpose but then includes auxiliary details (pricing, upstream URL, HTTP method) that, while useful, make it slightly cluttered. The structure is a single paragraph, which is acceptable, but the extra metadata could be separated or condensed.

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 gives a high-level idea of the output ('normalized day/night or hourly periods') but lacks specifics about response fields, error codes, or data format. Given the absence of an output schema, this is insufficient for an agent to know exactly what to expect.

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

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

The description mentions the conceptual inputs ('city/locality name or exact coordinates') but does not map them to the schema's generic properties (body, query). The schema itself provides no specific fields, so the description offers no practical guidance on how to structure the request 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 action: 'Get a global weather forecast' with specific input types ('city/locality name or exact coordinates') and output characteristics ('normalized day/night or hourly periods'). It uses a specific verb and resource, making the purpose unambiguous and distinct from other weather tools in terms of scope and coverage.

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 choose this tool over the many weather-related sibling tools. It explains internal data source preferences (NOAA/NWS vs. MET Norway) but does not contrast this tool with alternatives or specify scenarios where it is the recommended choice.

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 that this is a paid operation, names the upstream endpoint, and specifies POST, which adds useful behavioral context. However, with no annotations present, it leaves important behavioral details unstated such as authentication expectations, response behavior, failure modes, and whether any user-visible side effects occur.

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 all elements add value: cost, endpoint, upstream URL, and HTTP method. It is not bloated, though it reads more like a machine-generated proxy label than a human-friendly explanation.

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

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

Given the lack of annotations, lack of output schema, and a generic input schema, the description does too little to explain how the Exa search request should be formed or what the caller can expect in return. It identifies the upstream but leaves critical invocation and response details to inference.

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 full descriptions for the two generic parameters, body and query, so the baseline is 3. The description does not add Exa-specific parameter semantics or examples, but the stated POST method does help reinforce that the body parameter may be the appropriate place for the Exa search payload.

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 a specific resource (Exa /search endpoint), the upstream URL, and the HTTP method (POST). It is easy to understand what the tool does at a high level, though it does not differentiate itself from the sibling x402_stableenrich_dev_api_exa_search_39, which appears to target the same endpoint.

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

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

No guidance is given about when to use this tool versus any sibling, including the other Exa search wrapper. It does not state use cases, exclusions, or alternative tools, so the agent must infer usage entirely from the name and endpoint.

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 discloses that the API is paid, that it uses eth_call, and that it returns allowance information. However, it does not describe output format, error behavior, or whether the query parameters are all required, which are meaningful gaps for a paid external API call.

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 dense but each part earns its place: cost, functional semantics, upstream URL, HTTP method, and a concrete example. It is front-loaded with the paid nature and purpose. The example JSON is long but necessary because the schema lacks named query parameters, so it is justified.

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 covers the key invocation details: paid cost, upstream endpoint, method, example parameters, and the meaning of the return value. However, there is no output schema and no mention of return format, units, or required parameter enforcement, so an agent may still be uncertain about the exact response shape and required fields.

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 only describes generic 'body' and 'query' objects with no named properties, so the schema alone is not very informative. The description compensates by providing an explicit example query with contract, network, owner, and spender, giving the agent concrete parameter meaning beyond the generic 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 function: checking ERC20 allowance via eth_call, specifically how much a spender is approved to move from an owner's wallet. It provides an example query with contract, network, owner, and spender, making the purpose concrete. It does not explicitly differentiate from sibling tools, but the operation and resource are 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 provides an upstream URL, HTTP method, and example query, but gives no guidance on when to use this tool versus alternatives such as erc20_balance or other chain tools. There is no explicit when-to-use or when-not-to-use context, leaving the agent to infer usage solely from the stated purpose.

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 paid cost ($0.0011 inbound then $0.0011 proxy), HTTP method (GET), upstream URL, and endpoint behavior (eth_blockNumber). It does not describe output shape or error behavior, but for a simple read-only block-height lookup the expected result is largely inferable.

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

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

The description is a single compact block that front-loads the cost and core purpose, then gives the upstream endpoint, method, and an example query. There is no filler or repetition.

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 GET proxy with no output schema, the description provides the key invocation details: cost, method, URL, and example query. It is incomplete about whether the network query is required, what the exact response body looks like, and how to distinguish this tool from the similarly named block_number_19 sibling.

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 only provides generic body and query objects, so the schema alone is not endpoint-specific. The description adds the crucial example query {"network":"ethereum"}, giving the agent a concrete parameter to send. It does not enumerate all accepted network values or state whether the query is required, so it is not exhaustive.

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 a specific resource ('Latest Ethereum block height - current chain tip') and the underlying method (eth_blockNumber), making it clear this tool returns the current block height. It does not explicitly contrast itself with the near-identical sibling x402_api_onesource_io_api_chain_block_number_19, so it stops short of full sibling differentiation.

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?

Usage is implied by the description: an agent should call this when it needs the current Ethereum block number. There is no explicit when-not-to-use guidance or mention of alternatives, so the guidance is minimal.

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 behavioral transparency burden. It adds useful behavioral context: the call is paid ($0.0033 inbound/proxy), uses GET, hits a specific upstream URL, and is a read-style 'Fetch' operation. However, it does not disclose auth requirements, rate limits, error behavior, or response format, 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 compact and front-loaded with the cost and the core action, followed by the upstream URL, method, and example query. The phrase 'then proxy $0.0033' is slightly cryptic, but the overall structure earns its place with useful details in a single sentence.

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 API with no output schema and no annotations, an agent needs more context to call it correctly: how to specify the block number/tag/hex given the schema only exposes query/body, what the response contains beyond 'block header and transaction hashes', and whether any auth is required. The description provides an endpoint and an example but leaves essential request-building details unspecified.

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 only provides generic 'body' and 'query' objects with 100% description coverage but no concrete parameter details. The description adds the example query {"network":"ethereum"} and the upstream path /:number, which is helpful. It does not explain how number/tag/hex map to the schema or how path, query, and body interact, so semantic clarity remains partial.

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 a specific action and resource: 'Fetch an Ethereum block header and transaction hashes by number, tag, or hex via eth_getBlockByNumber.' This distinguishes it from most sibling chain tools by naming the exact endpoint behavior. It does not explicitly contrast with sibling block-related tools, so it stops short of a 5.

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

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

There is no guidance on when to use this tool versus alternatives like x402_api_onesource_io_api_chain_block_number_15, x402_api_onesource_io_api_chain_tx_hash_17, or other chain tools. The path and method imply usage, but no conditions, exclusions, or selection criteria are provided.

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

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

With no annotations, the description carries the burden of behavioral disclosure. It does disclose that the operation is read-only, sends no transaction, and includes cost and upstream URL/method details. However, it does not explain auth requirements, output/return behavior, error cases, or how the body/query are forwarded to eth_call.

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 brief and dense, conveying cost, purpose, upstream, and HTTP method in a single line with no wasted words. The pricing bracket is placed first, slightly delaying the core purpose, but the rest is 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?

There is no output schema, annotations are absent, and the input schema is generic. The description does not tell an agent how to compose the eth_call request or interpret the response, which is a significant gap for a generic POST proxy among many similar endpoint tools.

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

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

Schema description coverage is 100%, so the baseline is 3. The description adds no parameter-specific meaning: the schema only provides generic 'body' and 'query' objects, and the description does not explain how to structure the eth_call payload (e.g., contract address, calldata, block).

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 a specific operation: simulate a read-only Ethereum contract call via eth_call, and explicitly notes no transaction is sent. This distinguishes it from sibling chain endpoints like tx_hash, estimate_gas, and balance endpoints by naming the exact RPC method and behavior.

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 read-only contract simulation without sending a transaction — but it gives no explicit guidance on when not to use it or which alternative sibling tools to choose instead. With many similar chain_* tools, clearer routing would help.

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 behavioral disclosure burden. It discloses the paid cost, upstream URL, and GET method, which is useful, but it does not describe the response format, possible error behavior, or authentication needs.

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 packs cost, purpose, upstream endpoint, method, and example into one dense line with no filler. The most important selection information (purpose and cost) appears at the front.

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 is a simple read-only chain-ID lookup, and the description supplies enough to select and invoke it: endpoint, GET method, and example query. The lack of an output schema is partially mitigated by the self-describing purpose, though an explicit response shape would make it fully complete.

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

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

The schema only defines generic body/query objects, so the example query {'network':'ethereum'} adds the concrete parameter name and value needed to call the upstream API. This meaningfully compensates for the schema's generic additionalProperties.

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 a specific action—confirming the Ethereum chain ID (EIP-155) via eth_chainId for a given network. It explicitly names the resource (chain ID) and includes an example query, which distinguishes it from sibling chain tools like block_number, balance, and tx_hash.

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

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

The description gives a clear use case: 'confirm which chain a network is on,' supported by the example query. It does not explicitly exclude alternatives or name sibling tools, but for this simple endpoint the context is clear enough.

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

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

There are no annotations, so the description carries the behavioral disclosure burden. It discloses the paid pricing model ($0.0033 inbound then proxy $0.0033), the upstream endpoint, the HTTP method, and the return type. It stops short of describing response formatting or error behavior, but for a simple GET read it is reasonably transparent.

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 dense sentence that front-loads the pricing and then states the purpose and call details. Every segment earns its place, though the formatting is somewhat run-on.

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 covers purpose, endpoint, method, pricing, and return content, which is decent for a simple tool. However, it does not specify how to pass the address parameter or describe the response structure, and there is no output schema to fill that 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?

The schema already describes its generic body and query parameters, so the baseline is 3. The description adds an example query and identifies the upstream :address path placeholder, but it never explains how to supply the address through a schema that only exposes body and query. This is a meaningful 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 operation: 'Check if an Ethereum address is a contract via eth_getCode - returns deployed bytecode.' It names a specific verb, resource, and underlying RPC method, which also helps distinguish it from the many sibling chain 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 gives concrete context: use this tool to inspect an Ethereum address's deployed bytecode, with method GET and an example query. It does not explicitly name alternatives or exclusion conditions, but the intended use case is clear enough for an agent to select it.

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

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

With no annotations, the description does carry the burden. It usefully discloses the paid cost, best-effort nature, and batched-RPC mechanism. However, it does not describe return shape, failure behavior, or what 'PAID inbound -> then proxy' means for the caller, so transparency is only partial.

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 with cost, behavior, and upstream details. It packs useful facts into a small space with no 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?

The tool has no output schema, so the description should cover return values and critical invocation details. It provides cost and purpose but omits the address parameter syntax, expected result semantics, and error behavior, leaving too much unstated for a tool in a large sibling family.

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's body/query descriptions are generic, and the only concrete example is an example query with network=ethereum, which omits the critical contract address despite the upstream URL containing :address. The description does not explain how to supply the address, so the agent cannot reliably invoke the tool correctly.

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 a specific operation: best-effort contract introspection via batched RPC, and enumerates exact outputs (bytecode presence, token metadata, ERC20-like/ERC721/ERC1155 classification). This is enough to distinguish it from sibling chain tools such as code_address or nft_metadata, even without naming 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?

There is no explicit guidance on when to choose this tool over the many sibling onesource chain tools. The description implies the purpose but does not state conditions, prerequisites, or alternatives, so an agent gets no routing help.

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

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

No annotations are present, so the description carries the disclosure burden. It discloses the paid cost, GET method, and eth_call execution mechanism. However, it does not mention authentication requirements, rate limits, or expected error/return 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 dense but not bloated: it packs cost, purpose, endpoint, method, and example into a compact block. The lack of paragraph separation makes it slightly harder to parse, but every element carries useful 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?

With no output schema and no annotations, the description remains incomplete: it does not explain how to pass the ENS input, what the response shape is, or how authentication/errors are handled. The cost and endpoint are helpful, but the central invocation detail is missing.

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

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

The schema has 100% coverage for its two generic fields, so the baseline is 3. However, the description's endpoint includes an ':input' path parameter that is absent from the schema, and the example query does not show how the actual ENS name or address should be supplied. This creates a critical gap rather than clarifying parameter usage.

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 a specific action ('ENS resolve'), a clear bidirectional mapping (.eth name to address and reverse), and names the upstream resource and method. This clearly distinguishes it from the many other OneSource chain tools in the sibling list.

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 intended use is obvious: resolve ENS names or addresses on Ethereum via the provided endpoint. It gives the method, upstream URL, and an example query, making the usage context clear, even though it does not explicitly name sibling alternatives or exclusion conditions.

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

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

No annotations are present, so the description carries the behavioral disclosure burden. It discloses the paid pricing, upstream URL, HTTP method, and that the call uses eth_call/balanceOf, which clearly implies a read-only operation. It stops short of detailing side effects or failure behavior, but for this simple read endpoint the disclosure is strong.

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?

Every part of the description earns its place: pricing, purpose, upstream source, method, and example. The key behavioral summary is front-loaded and there is no filler or repetition of the title.

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 is relatively simple, but there is no output schema and no annotations. The description gives enough context to construct a valid request, including network, contract, wallet, and token_id, and explains the meaning of the returned balance. It does not specify response format or error cases, but for a balanceOf endpoint the core context is present.

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 only defines generic body/query containers, so the actual query parameters are undocumented in the schema. The description compensates by providing a complete example query with address, contract, network, and token_id, giving the agent concrete parameter semantics. It could be improved by separately labeling each parameter, but the example is sufficient.

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 returns an ERC1155 token balance via balanceOf (eth_call) and explains it as 'how many copies of a token_id a wallet holds.' This specific verb+resource scope differentiates it from sibling tools like ERC20 balance or NFT owner endpoints.

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 this tool — when an ERC1155 balance for a specific token_id and wallet is needed — and provides method and example query. However, it does not explicitly state when not to use it or name alternatives such as erc20_balance or erc721_tokens.

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 that the call is a GET, uses eth_call, and incurs a cost ($0.0033 inbound and proxy). However, it does not describe the response format, error handling, or any side effects beyond the cost. The mention of the upstream endpoint adds some transparency, but key behavioral details like return data structure are omitted.

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

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

The description is information-dense without being bloated. It front-loads the cost, states the purpose, and gives technical details plus an example in a compact format. Every sentence adds value, and the structure flows logically from cost to function to 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?

The description covers the tool's purpose, mechanism, and an example, but lacks critical details for full usability. There is no mention of the response format (e.g., whether it returns a raw integer or a decimal), how to handle errors, or whether the network parameter is required or supports multiple networks. Given no output schema and no annotations, these gaps make the description insufficient for a new agent to fully anticipate 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 schema only has generic 'body' and 'query' fields with vague descriptions. The description compensates by providing an explicit example with address, contract, and network parameters, clarifying what should be passed in the query. This adds concrete semantics beyond the schema, which is essential for correct invocation.

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 'ERC20 token balance for any Ethereum wallet' and names specific tokens (USDC, USDT, DAI). It specifies the mechanism (balanceOf via eth_call) and the upstream endpoint, making the purpose unambiguous. However, it does not explicitly differentiate from sibling chain tools like allowance or total_supply, though the focus on balance is evident.

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

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

The description gives no guidance on when to use this tool over alternatives. It provides an example query but does not mention any conditions, exclusions, or preferred scenarios. Since many sibling chain tools exist (e.g., allowance, transfers, total_supply), the lack of usage direction leaves the agent to infer applicability from the 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?

No annotations are provided, so the description carries the burden. It does disclose the paid pricing model, the upstream endpoint, HTTP method, and that it returns raw Transfer events. However, it does not describe any authentication needs, response format, pagination, or rate limits, leaving notable 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 compact and front-loads the paid pricing and core purpose before the upstream URL and example. It is slightly dense with pricing notation, but every sentence carries operational information, and there is no 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?

There is no output schema and no annotations, so more context would be valuable. The endpoint, method, cost, and an example query are present, but the description lacks guidance on expected response shape, accepted query parameter variations, pagination, or how this tool differs from the many adjacent OneSource tools.

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

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

The input schema is generic with only 'body' and 'query' additionalProperties objects, so it provides almost no parameter meaning. The description compensates by giving a concrete example query with 'address', 'contract', and 'network', which tells the agent which fields matter in practice, even though it does not explain each parameter in prose.

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 fetching ERC20 Transfer logs via eth_getLogs, stating the resource as 'raw Transfer events for a token or wallet'. This distinguishes it from sibling chain tools like balance, allowance, or NFT metadata, so an agent can tell what it does.

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 ERC20 transfer event logs are needed and provides an example query, but it does not explicitly state when to prefer this tool over alternatives or when not to use it. Given the large number of sibling OneSource chain tools, this is a missed opportunity but not misleading.

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 behavioral burden. It discloses the paid cost ($0.0088 inbound and proxy), the HTTP method (GET), the upstream URL, the underlying mechanism (tokenOfOwnerByIndex via eth_call), and an example query. Missing details like pagination behavior and response format are gaps, but the description is far more transparent than most.

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 dense but every component earns its place: purpose, cost, mechanism, upstream URL, method, and example query. It is front-loaded with the core purpose and cost before the technical details. The phrasing is slightly run-on and cluttered, but it remains compact and useful.

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 and no annotations, so the description should explain both inputs and outputs. Inputs are reasonably covered by the example query, but the response format is not described, and there is no mention of pagination or limit behavior for the 'every token_id' promise. This leaves some uncertainty for an agent about what the tool will return.

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 is generic, only defining 'body' and 'query' with additionalProperties, so it provides no tool-specific parameter meaning. The description compensates by showing an example query with address, contract, and network parameters and their concrete values. This is essential for correct invocation and goes well 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 a specific verb and resource: 'List every ERC721 NFT token_id a wallet owns in a collection' via tokenOfOwnerByIndex. This clearly separates it from sibling chain tools like erc20_balance, nft_metadata, and nft_owner, so an agent can identify the intended operation without opening the schema.

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

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

The description gives clear context for when to use the tool: when the task is to enumerate all ERC721 token IDs owned by a wallet in a collection. It also provides the upstream method (GET), the exact endpoint, and a concrete example query. However, it does not explicitly name sibling alternatives or state when not to use it.

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

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

With no annotations, the description carries the full burden. It discloses that the tool is paid and that it performs an estimate (non-mutating), but it omits other behavioral traits like rate limits, authentication, 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 short and direct, containing the core purpose plus essential metadata (cost, upstream URL, HTTP method). It avoids unnecessary verbosity while retaining structure.

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 lacks an output schema and provides minimal parameter detail. An agent cannot fully understand how to construct a request or interpret the response, making it incomplete for autonomous use.

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

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

The schema describes two generic objects (body and query) with no specific fields or meanings. The description does not clarify what parameters should be provided, leaving the agent without actionable input guidance.

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 action (estimate gas consumption), the method (eth_estimateGas), and the use case (before signing a transaction). It is concise and distinct from generic chain 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?

It provides a contextual hint ('before signing it') but does not explicitly compare to alternatives or state when not to use this tool. The usage context is implied rather than explicitly scoped.

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 behavioral burden and does a good job: it discloses the paid nature of the call, the upstream URL, the HTTP method, and the available filters. It does not mention rate limits or response shape, but the core read-query behavior and cost are clear.

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 dense and efficient; billing, purpose, upstream endpoint, method, and an example are all packed in without fluff. It is somewhat run-on and lacks clear sentence breaks, but every segment earns its place and the most important details are 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 no output schema and no annotations, the description provides enough to make a basic call using the example, but it leaves the exact syntax for topic and block-range filtering undocumented. The upstream URL helps, but an agent would still need to infer parameters for anything beyond the simplest contract-address query.

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 only exposes generic body and query objects, but the description adds real parameter meaning through an explicit example query with contract and network fields. It also names conceptual filters (contract, topic, block range), going beyond the generic schema while not fully documenting every parameter name or type.

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 a specific verb and resource: "Query Ethereum contract event logs via eth_getLogs." It also names concrete filters (contract, topic, block range), which clearly distinguishes this from the many sibling chain tools for balances, transfers, and 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 gives clear context for when to use this tool: whenever Ethereum contract event logs are needed. It does not explicitly name sibling alternatives or state when not to use it, but the purpose is specific enough that selection is not 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?

With no annotations, the description carries full responsibility for behavioral disclosure. It mentions paid pricing and the HTTP method, but omits critical details such as authentication, rate limits, error behavior, or whether the operation is strictly read-only. The limit of 20 tokens is noted, but no consequences of exceeding it are stated.

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 moderately concise but includes extraneous pricing prefixes and upstream URL. The structure is logical (purpose, constraints, example) and not overly verbose, though the clutter slightly detracts from 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?

The description provides enough to separate this tool from single-token balance tools, but it lacks essential operational context such as how to pass multiple ERC20 addresses, expected response shape, or maximum batch size enforcement. An agent would need additional probing to use it correctly.

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

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

The schema is generic with only 'body' and 'query' objects, and the description does not systematically explain parameters. The example query hints that 'address' and 'network' are expected, but it does not clarify how ERC20 tokens are supplied or their exact format. This leaves parameter semantics 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 function: retrieving live wallet balances for native ETH plus up to 20 ERC20 tokens in a single batch. This distinguishes it from sibling tools that handle single-token balances, 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 usage for multi-token balance checks via the 'bounded RPC batch' phrase, but it does not explicitly contrast this with alternatives like calling individual balance endpoints. It provides pricing and method but lacks clear when-to-use vs. when-not-to-use 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 does useful behavioral work: it discloses the paid cost ($0.0011 inbound and proxy), specifies the HTTP method (GET), names the upstream endpoint, and reveals that multiple RPC calls (eth_chainId, eth_blockNumber, eth_gasPrice, latest block header) are batched internally. It stops short of documenting auth, rate limits, error behavior, or the response format.

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 dense but every part adds value: cost, fields returned, batched RPC methods, upstream URL, HTTP method, and an example query. The pricing bracket up front is a minor distraction, but overall it is compact and front-loaded with the tool's core purpose.

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

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

For a straightforward GET tool with no annotations or output schema, the description covers the endpoint and a working example, but it omits the supported network values, whether the network parameter is required, and what the response payload will look like. These gaps leave an agent with enough to attempt a call but not full confidence about valid inputs or returned data.

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

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

The schema only defines generic body and query containers, so the description adds key meaning by showing the actual query parameter 'network' with an example value 'ethereum'. This partially compensates for the schema's lack of a dedicated network parameter, though it does not enumerate supported networks or state whether network is required.

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

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

The description clearly identifies the resource (EVM network info) and enumerates the exact data fields returned: chain ID, block height, gas price, chain head age, and chain characteristics. It is distinguishable from sibling chain-specific tools because it presents these as a single batched read, though it lacks an explicit verb such as 'get' or 'retrieve'.

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

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

The phrase 'in one batched RPC call' implies this tool should be chosen when multiple network metrics are needed at once, and the example confirms the intended query shape. However, there is no explicit statement of when to prefer this over sibling tools such as chain_id, block_number, or gas_price, and no when-not-to-use 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 and reveals meaningful behavior: the call is paid at two stages ($0.0088 inbound and proxy), uses eth_call, and supports multiple metadata resolution schemes. It does not disclose error handling or response shape, but the disclosed traits go well beyond a minimal description.

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 packs cost, purpose, resolution modes, upstream URL, HTTP method, and an example query into a compact block with no filler. It is dense and slightly run-on, but every element earns its place and is front-loaded after the cost prefix.

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 GET proxy with a generic schema and no output schema, the description supplies the upstream URL, method, cost, and a concrete example query. Missing explicit parameter documentation and response/error expectations are gaps, but the tool is still invocable from the description alone.

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 only defines generic body and query objects, so the example query adds essential semantics by showing contract, network, and token_id as the actual upstream parameters. It does not formally document each parameter's type or constraints, but the example compensates for most of the schema's genericness.

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

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

The description clearly identifies the resource as NFT metadata for ERC721 and ERC1155 tokens, specifies the mechanism (eth_call) and the resolution methods (IPFS, Arweave, data URI, HTTP). This is specific enough to distinguish it from sibling tools like nft_owner or erc721_tokens, even without an explicit imperative verb.

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 purpose is clear enough that an agent can infer when to select this tool for NFT metadata lookups. However, there is no explicit guidance on when not to use it or which sibling tools are better alternatives, so the usage context is only implied.

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 side effects and safety. It mentions pricing and that it is a proxy, but does not explicitly state that this is a read-only operation, nor does it describe authentication requirements, error handling, or potential rate limits. The read-only nature is implied by 'ownerOf' and 'eth_call' but not stated.

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 structured with pricing, method, upstream, and example in a compact format. It includes all necessary information without excessive verbosity, 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?

While the description specifies the endpoint and example, it lacks details on the response format, error cases, or any authentication needs. Given the absence of an output schema, the description should explicitly mention what the response contains (e.g., owner address) to be fully complete. It also does not provide context on when to use this over sibling tools.

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

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

The schema provides only generic descriptions for body and query objects. The description's example reveals the actual query parameters (contract, network, token_id), adding meaning beyond the schema, but it does not formally document all parameters or their types. The optional body parameter remains unexplained.

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: looking up the current owner of an ERC721 NFT by token_id via ownerOf. It also provides the method (GET), upstream URL, and an example, leaving no ambiguity about the tool's 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 gives an example but does not explicitly state when to use this tool versus alternative chain tools like erc721_tokens or nft_metadata. No conditions or scenarios for selection are mentioned, leaving the agent to infer usage context from 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, the description carries the full disclosure burden and does reveal that the call is paid, proxied, uses GET, and hits a specific upstream URL. However, it omits response format, failure behavior, and how the wallet address is passed, leaving meaningful 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 dense and wastes little space: it packs cost, purpose, upstream URL, method, and an example query into one compact line. The embedded example JSON is slightly awkward in plain text but the overall 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?

There is no output schema, so the description itself must make the invocation clear, but it does not say how to specify the required wallet address and gives no usage guidance relative to the many sibling tools. An agent cannot confidently call this tool correctly from the description alone.

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 only defines generic body and query containers, and the description adds an example query and mentions an upstream :address path parameter. But it never explains how the wallet address is supplied, which is the core input for this tool, so the parameter semantics remain critically unclear.

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 that the tool returns the next transaction nonce for any Ethereum wallet via eth_getTransactionCount, which is a specific operation and resource. It is easy to distinguish from sibling chain tools such as balance, allowance, or block_number, though it does not explicitly name an alternative.

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

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

There is no guidance on when to use this tool instead of the many similar chain tools, nor any mention of exclusions or alternative tools. The phrase 'for any Ethereum wallet' only describes scope, not how to choose this tool among the siblings.

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

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

With no annotations, the description carries the full burden and does disclose useful traits: it is a GET request, it is paid ('PAID inbound $0.01 → then proxy $0.0110'), and it proxies the pending block via eth_getBlockByNumber. However, it omits response format, error behavior, rate limits, and whether the network parameter is required or restricted.

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 labeled: payment info, semantics, underlying method, upstream URL, method, and example query. The leading bracket notation is somewhat cryptic but not verbose, 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 simple GET proxy, the description covers the essential mechanics: URL, HTTP method, example query, and the meaning of 'pending'. However, there is no output schema and no description of the response shape, and the full set of accepted query parameters is not specified, leaving an agent to infer some 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 schema describes only generic 'body' and 'query' objects, so the description adds meaningful specificity with Method: GET and the example query {"network":"ethereum"}. This tells the agent a concrete query parameter name and value beyond the schema. It still leaves other possible query parameters undocumented.

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 names a specific resource and behavior: 'Pending block - transactions not yet mined' and ties it to eth_getBlockByNumber("pending"). This distinguishes it from sibling chain tools like block_number or tx_hash. It loses a point because it is a sentence fragment prefixed by ambiguous payment notation, rather than a clear declarative statement.

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

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

The description gives invocation details (Method: GET, upstream URL, example query) but does not state when to use this tool versus sibling onesource chain tools, nor does it provide exclusions or decision rules. 'Pending block' implies usage for unmined transactions, but that guidance is implicit 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 carries the behavioral burden. It discloses the HTTP method (GET), the upstream endpoint, the pricing, and the expected result (implementation address). This makes the read-only nature and the operation fairly clear, though it does not mention failure modes, response format, or auth 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 a single dense line that front-loads purpose and then gives endpoint, method, and an example query. There is some clutter from the pricing bracket and inline JSON, but every major fact needed for a basic call 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?

Core call details are covered: purpose, method, endpoint, cost, and an example query. However, there is no output schema or annotations, and the description still leaves gaps around how the address parameter is supplied, whether network is required, exact response shape, and error behavior. This is adequate but incomplete.

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

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

The schema only documents generic 'body' and 'query' objects, so the description adds real value by showing the upstream path placeholder ':address' and an example query {'network':'ethereum'}. It does not exhaustively enumerate accepted query parameters or clarify whether network is required, but it compensates for the generic schema better than most.

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: detect upgradeable proxy patterns and return the implementation address behind a proxy. It names specific patterns and the underlying mechanism, making the tool's purpose evident. It does not explicitly differentiate from sibling chain tools like storage_37 or code_address_33, so it stops 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 use case is inferable: call this when you need to discover whether an address is an upgradeable proxy and find its implementation address. However, there is no explicit guidance about when not to use it or which sibling tool to prefer, so the agent must infer routing from the purpose 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, the description carries full burden; it discloses the paid nature with specific fees, the upstream endpoint, HTTP method, and the response fields. It omits auth/rate-limit details, but the key read-only and cost behavior is transparent.

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 dense but compact, with cost, behavior, upstream, method, and example all present in a few clauses. It is slightly run-on but contains no filler 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?

It covers cost and return content, but not the required transaction hash input, network requirements/values, error behavior, or what happens for unmined hashes. Without an output schema or richer parameter schema, this is not enough to invoke reliably.

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 only describes generic body/query containers, and the description adds only an example query with network=ethereum. It does not explain how to supply the required transaction hash, despite the upstream URL containing :hash, so the critical parameter semantics are missing.

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 returns an Ethereum transaction receipt via eth_getTransactionReceipt, specifying the returned content: status, gas, and event logs for a mined transaction. This verb+resource combination distinguishes it from sibling chain tools such as block_number, allowance, or pending.

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 gives clear context: use for mined Ethereum transaction receipts, and specifies the GET method and upstream endpoint. It does not explicitly name alternatives or when-not-to-use, but the 'mined' condition is a useful eligibility signal.

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 behavioral burden. It discloses the paid nature ($0.0055 inbound and proxy), upstream URL, GET method, and proxy behavior. It does not mention response format, authentication, rate limits, or error behavior, which are 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 compact and information-dense, packing cost, purpose, upstream endpoint, method, and an example query into one line. It is slightly unstructured but contains no filler.

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

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

For a simple GET proxy, it covers the essential invocation details: cost, endpoint, method, and example. However, with no output schema and no annotations, it does not explain the response shape or format, leaving moderate ambiguity about what the tool actually returns.

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

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

The schema only describes generic body and query containers, so the example query is the main source of parameter meaning. It supplies concrete names and values for contract, network, and slot, adding real value beyond the schema. More explicit type/format documentation would improve it further.

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?

States a specific verb and resource: 'Read a raw storage slot from any Ethereum contract via eth_getStorageAt.' This clearly distinguishes it from sibling chain tools such as allowance, call, or balance, and the example query reinforces the exact operation.

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 use case is implied: use this when you need a raw storage slot from an Ethereum contract. However, it does not explicitly compare against sibling tools or state when not to use it, leaving the agent to infer the correct context.

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

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

With no annotations provided, the description carries the full burden. It discloses the paid cost, proxying behavior, upstream endpoint, HTTP method GET, and the eth_call mechanism. It does not describe response format or error behavior, but the read-only nature is strongly implied by GET and totalSupply.

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 information-dense: cost, purpose, upstream, method, and an example query all appear without filler. The key facts are front-loaded, and every segment contributes useful guidance.

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 read-only API call, the description covers cost, endpoint, method, and an example request. The main gaps are the lack of an explicit response format and supported network values, but the description is still adequate for an agent to select and invoke the tool correctly.

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

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

The input schema only documents generic body and query wrapper objects, so the description's example query adds critical meaning by revealing the actual parameters 'contract' and 'network'. This compensates for the schema's lack of specific parameter definitions, though not all possible query options are documented.

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 what the tool does: returns the total supply of an ERC20 or ERC721 token contract via totalSupply (eth_call). It is specific enough to distinguish this tool from the many chain-related siblings, such as balance, allowance, or block number 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 establishes the clear use case: querying total supply for an ERC20 or ERC721 contract. It implicitly excludes ERC1155 and other operations, but it does not explicitly name alternatives or state when not to use it.

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

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

The description notes the method is GET, suggesting read-only behavior, but does not explicitly state that it has no side effects or require special permissions. It also includes cost information but does not clarify potential side effects or rate limits, so transparency is only partial.

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 packs pricing, upstream URL, method, and example into one string, which is somewhat cluttered but still under 200 characters. It is front-loaded with pricing rather than the core purpose, which slightly reduces clarity, but overall it is 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?

The description provides expected output fields but omits details on how to construct the request (e.g., where to put the hash) and does not address error handling or response format. Given the lack of an output schema, this leaves significant gaps for an agent to call correctly.

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

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

The input schema includes 'body' and 'query' objects with generic descriptions, but the description does not explain how to specify the transaction hash, which is critical. The upstream URL has a path parameter ':hash' but the schema does not mirror it, causing ambiguity about parameter usage.

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 returns full Ethereum transaction details by hash, listing specific fields (from, to, value, calldata, block) and the underlying method. It distinguishes itself from sibling chain tools like balance or block number, so the purpose is unmistakable.

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 retrieving transaction details given a hash, but does not explicitly state when to prefer this over alternatives (e.g., receipt or pending transactions). It provides an example query but lacks conditions or exclusions, leaving usage guidance 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?

With no annotations present, the description carries the full transparency burden and does a good job: it discloses the paid fee, the proxy behavior, the upstream URL, the GET method, and JSON return format. It does not mention units, error behavior, or whether coordinates are mandatory, but the core behavior is clearly visible.

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 dense and efficient, front-loading cost, then purpose, fields, source, protocol, and an example query with no filler or repetition. It reads like compact metadata rather than prose, but every sentence earns its place.

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

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

For a simple GET weather endpoint with no output schema, the description is nearly sufficient: it provides the upstream URL, method, query example, response format, and observable variables. It stops short of specifying units or the exact response structure, but the agent has enough to make a correct call.

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 only provides generic 'body' and 'query' objects, so the description adds real value by giving the example query with 'lat' and 'lon' keys. This tells the agent exactly how to invoke the tool, going beyond the 100% 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 identifies the tool as returning latest observed current-weather conditions near a US coordinate, listing the specific data fields (temperature, wind, humidity, visibility, pressure) and naming the National Weather Service as the source. Even without naming any sibling directly, it is distinguishable from forecast, alert, METAR, and location-specific weather 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 intended use is implicitly clear: use this for current observed weather near a US lat/lon coordinate. However, the description does not explicitly state when not to use it or mention alternative sibling tools, so the agent must infer routing from the 'current' and 'US coordinate' wording.

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 does most of the work: it discloses cost ($0.0033 each side), method GET, JSON output, and upstream source. It stops short of error behavior, response shape detail, or rate limits, which leaves a gap for a paid proxied API.

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 dense but economical, packing cost, source, format, method, URL, and an example into a compact block. The embedded JSON example is slightly noisy but earns its place by conveying the query parameters.

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

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

For a GET-style weather data fetch, it provides enough to construct a call: station, optional taf, method, URL, and response format. It lacks a more detailed return-structure or error-case description, but no output schema exists to cover that.

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 only defines generic body/query containers, so without the description a caller would not know what to send. The example query supplies the real parameter semantics: station as an ICAO code and optional taf boolean.

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 names a specific resource (METAR/TAF weather reports) and target (any airport ICAO code), and distinguishes it from weather-current, forecast, and alert siblings. The upstream URL and NOAA source further pin down what the tool does.

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 clearly establishes when to use it: for raw/decoded METAR or optional TAF at an ICAO airport code. It doesn't explicitly state alternatives or when not to use it, but the METAR/TAF scope is clear enough against the sibling weather 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?

With no annotations provided, the description carries the burden and does a good job: it discloses that the tool is paid with precise costs ($0.01 then $0.0110), which payment networks are accepted, the upstream URL, the HTTP method, and the return fields. It lacks details about rate limits, failure modes, or units, but meaningfully exceeds a minimal 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 dense but organized: payment details are front-loaded, the core behavior follows, and the upstream/method/example are appended compactly. The Chinese phrase '实时天气查询。' is redundant with the English text but not harmful, and every other part 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 large number of sibling weather tools, the description provides enough context to identify this as coordinate-based current weather with payment requirements and output fields. There is no output schema, but the description covers the main return values. It could be more complete with units or response structure, but it is sufficient for selection and invocation.

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

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

The schema only describes generic body and query wrapper objects, so the description adds real value by identifying the actual upstream parameters ('Pass lat and lng') and providing an example query shape. This compensates for the schema's lack of tool-specific parameter documentation.

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

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

The description clearly states the tool returns current weather for a coordinate via Open-Meteo and lists the data fields (temperature, humidity, wind, precipitation, weather code). It does not explicitly differentiate itself from the many sibling weather tools, so it stops 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?

It gives a clear use context: 'For AI agents needing current weather, weather data, temperature and conditions by location.' It also says to pass lat and lng and notes that payment can be made on Base or Solana. However, it does not mention exclusions or when to prefer a sibling weather tool.

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 partially discloses behavioral aspects: it states that the tool reuses existing app.tenna.ai output with no extra AI call, and that it is experimental with no demonstrated edge. It also mentions pricing details and a preview limit. However, it does not describe side effects, required authentication, or output behavior, leaving some opacity.

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 highly repetitive, repeating the same phrases multiple times (e.g., 'Latest sealed five-minute...'). It includes redundant lines and mixes unrelated information like pricing and preview eligibility, making it poorly structured and inefficient. The important details are buried in 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?

The description lacks essential context for an agent to use the tool effectively. It does not explain what the forecast is, what the output will look like, or how to construct a valid request. Although it provides an upstream URL and method, it omits response format, input schema details, and any error handling or constraints beyond the pricing mention.

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

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

The schema defines only two opaque parameters, 'body' and 'query', as generic optional objects. The description merely repeats the schema text without explaining what content should be placed in these objects, no examples or field names are provided. This adds no semantic value beyond the schema itself.

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 attempts to convey the tool's function as a forecast provider, but it is inconsistent and verbose, mixing pricing and eligibility details without a clear action verb or resource. It mentions 'Latest Sealed BTC Forecast' but then refers to 'LUMI, TENNA, and consensus forecast' without clarifying the relationship, making the purpose ambiguous.

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 includes pricing and preview eligibility details, but these do not constitute usage guidelines. There is no mention of alternative tools or specific scenarios where this tool is preferable.

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 does meaningful work: it discloses the paid cost flow ($0.0011 inbound and proxied), the upstream URL, the HTTP method (GET), the data provider (Open-Meteo), and the returned data categories. It does not mention rate limits or error behavior, but for a read-only weather proxy the key behavioral context is present.

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 with the cost indicator, then states what the tool does, its inputs, outputs, and upstream details. The embedded example query is slightly dense but earns its place because the schema lacks specific parameter definitions.

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

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

Despite having no output schema and no annotations, the description covers the essential invocation details: cost, query parameters, upstream URL, HTTP method, and returned fields. It lacks explicit routing guidance among the many sibling weather tools, but an agent has enough context to call this tool correctly.

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

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

The schema only defines generic body and query containers, so the example query in the description is essential. It names the actual parameters (lat, lon, location), gives example values, explains that location is an alternative to lat/lon, and notes that lat must be used with lon. This goes well beyond the schema and is critical for correct invocation.

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 a clear, specific purpose: real-time weather data and a 3-day forecast for any location, with explicit input options (city name or lat/lon) and output fields (temperature, humidity, wind, precipitation, conditions). This differentiates it from narrower weather siblings by emphasizing worldwide coverage and the forecast window.

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: use when needing weather for any location, or for a 3-day forecast, and accept either city name or coordinates. However, it does not explicitly state when to prefer this tool over the many sibling weather tools, nor does it mention exclusions or alternatives.

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

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

With no annotations provided, the description carries the behavioral disclosure burden. It discloses the paid cost structure, upstream URL, HTTP method GET, and the data categories returned. It does not detail response structure, error behavior, or rate limits, but the provided cost and upstream details add meaningful transparency.

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

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

The description packs cost, purpose, data fields, source, upstream URL, method, and an example query into a single compact sentence. There is no fluff or redundant restatement of 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?

For a simple GET tool with zero required parameters and no output schema, the description covers the essential context: what data is returned, where it comes from, how much it costs, and how to call it. It could be more explicit about exact response property names or supported query parameters, but it is sufficiently complete for likely 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%, and both parameters (body, query) are already described generically in the schema. The description adds only an example empty query and confirms GET, which is minor additional guidance 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 provides real-time Seoul weather with temperature, sky, humidity, and wind, sourced from KMA official data. This distinguishes it from the many generic or other-region weather sibling tools without needing to open schemas.

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 clearly indicates this tool is for Seoul current weather, which gives strong contextual guidance for when to use it. It does not explicitly name alternatives or state when not to use it, but the Seoul-specific scope is clear enough for 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?

The description discloses cost ('PAID inbound $0.01 → then proxy $0.0110'), indicates it is a POST request, and mentions an upstream URL, which gives some insight into its operation. However, it does not describe the return format, side effects, authentication requirements, or rate limits. Since no annotations are provided, this partial disclosure is insufficient for full 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 relatively concise, containing the core purpose, cost, and method in a single sentence. However, the structure is somewhat cluttered by mixing pricing notation, tool type, and technical details without clear separation. It is efficient overall but not impeccably 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?

The description fails to provide essential context for using the tool effectively. It omits expected output (search results format), any required input parameters beyond generic body/query, and error handling or edge cases. This leaves the agent without sufficient information to invoke the tool confidently.

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 describes 'body' and 'query' only as generic optional JSON and query string parameters, repeating the schema structure without explaining what data they should contain or how they relate to the search functionality. The description does not elaborate on parameter usage, making them semantically empty.

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 is an 'Exa Search' tool for 'neural search across the web', providing a specific verb and resource. This distinguishes it from other search tools in the sibling list, such as 'search_bazaar' or generic weather tools, by explicitly describing the neural search capability.

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

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

There is no explicit guidance on when to use this tool over alternatives like other search tools (e.g., 'search_bazaar' or 'x402_api_exa_ai_search_35'). The description does not mention any conditions, use cases, or reasons to prefer this tool, leaving the agent to infer when it is appropriate.

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 pricing, keyless access, pay-per-call model, hourly refresh/freshness metadata, agent-ready JSON, and the GET method. It does not cover error handling or rate limits, but provides substantial 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 dense but organized with useful labels: cost, scope, return fields, freshness, upstream, method, and example. No filler is present, though the many clauses are packed into a single block.

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?

Since there is no output schema, the description appropriately summarizes return values: current conditions, 5-day forecast, daily highs/lows, and precipitation probability. It omits units and exact response structure, but is sufficient for a simple GET weather 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 input schema only describes generic body/query wrappers, so the description adds essential meaning: the query should contain 'location', city names auto-geocode, and lat/lon is supported. The example query '{"location":"London"}' is especially useful and goes 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 a specific verb+resource: 'Live weather for any city or lat/lon worldwide' plus a 5-day forecast. The worldwide scope and forecast detail help differentiate it from narrower weather siblings, though it does not explicitly name 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?

Usage is implied through the example query and 'any city or lat/lon worldwide', but there is no explicit when-to-use guidance or mention of alternatives. With many weather-related sibling tools, an explicit routing statement would improve the definition.

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 but only states the data source, method, and an example query. It omits the response format, error behavior, rate limits, and what 'PAID inbound' actually means operationally.

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 and front-loaded with the core action, followed by source, method, and example. The pricing bracket is terse and not overly verbose, so the overall structure is clean.

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 large set of weather-related sibling tools, the description does not differentiate this tool or indicate when it is the best choice. There is no output schema and no mention of return units, location formats, or failure modes, leaving the context incomplete.

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

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

The input schema only exposes generic body and query objects with no named properties. The description adds an example city query, which helps slightly, but the body parameter and any other accepted query fields remain completely unexplained.

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 it retrieves live current weather for any city from Open-Meteo via a GET endpoint and includes an example query, making the primary purpose evident. It does not explicitly name sibling alternatives, but the action is 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?

No guidance is provided on when to use this tool instead of the many sibling weather tools, or how the paid proxy flow affects usage. The 'PAID' marker is not explained as a usage condition.

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