Riley Craig x402 Agent Store

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

The description adds useful behavioral context: it discloses the cost ($0.09 via x402) and the output nature (copy-pasteable configs). However, without annotations, it does not disclose safety properties, authentication requirements, error behavior, or side effects, leaving significant gaps.

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

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

The description is a single sentence that front-loads the cost and purpose, with no redundant text. It efficiently conveys the essential information in a compact, well-structured format.

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

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

With no output schema and no annotations, the description should explain expected return values and prerequisites. It states the output is configuration payloads and IaC templates, but lacks details on response structure, error cases, or setup requirements. It is adequate but has clear gaps for a tool with this complexity.

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

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

Schema coverage is 100%, so the baseline is 3. The description does not add parameter-specific semantics beyond the schema; the platform targets are already enumerated in the schema's enum, and the description adds no additional detail about parameters like pay_to, x_payment, or service_url.

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 ('Generate') and the resource ('configuration payloads and IaC templates'), listing the three target platforms (Salesforce Agentforce, Google Vertex AI, AWS WAF). This distinguishes it from sibling proxy tools like agentforce_proxy and vertex_proxy, which serve a different function.

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

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

No guidance is provided for when to use this tool versus alternatives. The description gives a use case but no explicit selection criteria, exclusions, or mention of alternative tools. The agent is left to infer 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?

No annotations are provided, so the description carries the full burden. It discloses the cost ($0.09 via x402), which is useful, but it does not explain the tool's behavior: whether it sends external requests, what the response looks like, whether a valid payment payload is required, or what side effects occur. This is a significant transparency gap.

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

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

The description is very short and contains no filler, but it under-specifies. The opening phrase 'Premium Salesforce Agentforce Fallback Node' is a title-like restatement, while the actual functional value ('Fallback routing for Salesforce Agentforce instances') is one clause. It is concise but at the cost of needed detail.

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 2-parameter tool with no output schema and no annotations, the description should explain return values, expected input semantics, and usage context. It only provides a cost note and a vague routing statement. The lack of any information about the response format or error conditions makes it incomplete for an agent to select and invoke it 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?

Schema coverage is only 50% (x_payment is documented, message is not). The description adds nothing about the parameters—neither 'message' nor 'x_payment' is elaborated. Since the description is the only place to clarify the undocumented 'message' parameter, the lack of any specification fails to compensate for the schema gap.

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

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

The description identifies a specific verb ('fallback routing') and resource ('Salesforce Agentforce instances'), which distinguishes it from sibling proxy tools like bedrock_proxy and vertex_proxy. However, 'Premium Salesforce Agentforce Fallback Node' reads as marketing language and does not clarify what fallback routing actually does operationally.

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 on when to use this tool versus alternatives. The phrase 'Fallback routing' implies a failover use case, but there is no explicit context, prerequisites, or exclusions. Sibling tool names (e.g., bedrock_proxy, vertex_proxy) suggest similar proxy patterns, but the description does not differentiate usage scenarios.

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

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

No annotations exist, so the description must fully disclose behavior. It states data comes from 'chain-verified receipts only,' implying read-only access, but does not mention permissions, rate limits, error handling, or what happens if the address is invalid. The limited transparency hinders tool selection confidence.

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

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

The description is a single, well-structured sentence that efficiently conveys the tool's output and data source without redundancy. Every element is necessary and front-loaded.

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

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

Given the tool's simplicity (one parameter, no output schema), the description provides essential information about the return value (passport, BotScore, tasks, volume, counterparties) and its source. However, it lacks details on the return format, historical depth, or interpretation of the BotScore.

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

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

The input schema has full description coverage (100%) for the single parameter 'address' (described as 'Agent wallet address'). The tool description adds no further detail about the parameter, so the baseline score of 3 is appropriate.

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

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

The description clearly states the tool provides a 'Public agent passport + BotScore (0-100)' with specifics like completed tasks, USDC volume, and counterparties. It distinguishes from siblings by focusing on agent reputation from on-chain data, though it lacks an explicit verb like '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?

No guidance is given on when to use this tool versus alternatives like smart_money_wallet_activity or crypto_market_metrics. The description implies usage for agent reputation checks but provides no context on prerequisites or trade-offs.

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 it discloses meaningful behavior: it queries a live/current model, ranks brands by mention share, and costs $0.02 via x402. It does not mention model variability or failure modes, but the core behavior is communicated transparently.

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

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

The description is two dense sentences with no filler. Cost and core behavior are front-loaded, followed by use cases, making it easy to scan and act 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?

For a simple one-required-parameter tool with no output schema, it covers the input category, output format, use case, and cost. Market defaults are left to the schema, and payment details are implied rather than fully specified, but an agent can invoke the tool correctly with what is provided.

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 category and market, covering 67% of parameters. The description reinforces that category is open-ended and references the x402 payment mechanism, but it does not explain the undocumented x_payment parameter or add parameter-level detail beyond the schema. It is adequate but not compensatory.

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 concrete behavior: ask a current model for recommendations in any category and receive a ranked shortlist of brands by mention share. It also frames itself as the inverse of a brand check, which distinguishes it from single-brand visibility tools in the sibling set. The verb and resource are specific.

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 names target use cases: competitive-intel, market-research, GEO, and sales agents. It also signals when this tool is preferable by calling itself the inverse of a brand check, implying single-brand checks are the alternative. However, it does not explicitly name an alternative tool or state when-not-to-use 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?

With no annotations provided, the description carries the full burden and does disclose a notable behavioral trait: the tool costs $0.01 and is paid via x402. It does not, however, clarify side effects, return format, pagination, rate limits, or whether the 'scores' are returned directly or whether 'competitor AI names' replace them, leaving meaningful behavioral ambiguity.

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

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

The description is short and front-loaded with the pricing detail, but the phrase 'with competitors AI names instead' is awkward and unclear, reducing the effectiveness of the single sentence. It is concise in length but not fully coherent in 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 has no output schema and no annotations, and the description leaves key invocation details unresolved: whether the x_payment parameter is actually required despite being marked optional, what category values are valid, and what the result structure looks like. The ambiguous final phrase further prevents an agent from confidently invoking or interpreting the tool.

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

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

Schema description coverage is 100%, so the input schema already documents both 'category' and 'x_payment' parameters. The description adds no extra meaning about how category values behave or how the x402 payment payload should be constructed, so the baseline score of 3 is appropriate.

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

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

The description clearly identifies the resource as proprietary AI-visibility scores for 25 major brands across 5 industries, which gives an agent a concrete sense of scope. However, it lacks an explicit verb like 'get' or 'list', and the phrase 'with competitors AI names instead' is ambiguous about exactly what the tool returns versus its siblings.

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

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

There is no guidance on when to use this tool instead of closely related siblings such as ai_category_ranking, ai_visibility_signal, brand_ai_visibility_check, or crypto_ai_visibility. No use conditions, exclusions, or alternatives are mentioned, so the agent must guess based on the name.

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. It usefully discloses that the feed costs $0.005 and is paid via x402, and that it reports current checks rather than historical aggregates. It does not describe the response shape, streaming vs. snapshot mechanics, or whether the x_payment payload is required to access the feed, leaving non-trivial 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?

One compact sentence with no filler; the price and payment mechanism are front-loaded, and the feed content follows immediately. Every word contributes meaning.

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?

Low complexity and full schema coverage help, but with no output schema the description must convey what the caller gets back. It says the feed is of 'which brands/categories are being checked... right now' but leaves the response format and any payment-required caveats unspecified, so the tool is adequate but not fully complete.

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

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

The schema already documents x_payment as an optional signed x402 payment payload, so the baseline is 3. The description adds the cost context ('$0.005 via x402'), which explains why the parameter matters and ties the fee to the payment mechanism. It does not add syntax or construction details, but the schema coverage is complete.

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 what the tool provides: a live feed of which brands/categories are being checked for AI-search visibility, with the temporal qualifier 'right now' distinguishing it from a static index or ranking. The noun-phrase form 'live feed' is a minor weakness; it lacks an explicit verb like 'returns' or 'lists', so the main action is implied rather than fully stated.

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 'live feed ... right now' implies real-time monitoring usage, so an agent can infer when this tool is appropriate over a static index or ranking. However, it never names alternatives such as ai_visibility_index or brand_ai_visibility_check, nor does it state when not to use this 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 discloses the $0.09 cost via x402 and its fallback routing behavior, which is useful context beyond the bare schema. However, it says nothing about request/response behavior, failure modes, or whether payment is required, and with no annotations available that gap is significant.

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 one-sentence description is very compact and front-loaded with the price and type, but it sacrifices necessary detail for brevity. It is not a tautology, yet it is too sparse to fully inform the agent about how to invoke the tool.

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

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

This is a moderate-complexity proxy tool with 3 parameters and no output schema, yet the description provides no return format, error handling, or concrete usage example. The agent would need to infer too much about the tool's behavior, making the description 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?

With only 33% schema description coverage, the description must compensate for missing parameter details, but it only loosely relates 'Ollama-Compatible' to the model parameter and 'x402' to x_payment. The required prompt parameter is entirely unaddressed, leaving its semantics 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 identifies the tool as a 'Premium Ollama-Compatible Proxy' with 'Fallback routing for autonomous LLM crawlers,' but it lacks a clear verb stating the core action (e.g., 'generate completions for given prompts'). The name 'api_generate' and the prompt/model schema imply an LLM generation proxy, but the purpose remains vague compared to siblings like llm_chat_completions.

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 'Fallback routing for autonomous LLM crawlers' suggests a specific scenario when to use this tool, but it does not explicitly contrast it with alternatives such as llm_chat_completions or bedrock_proxy. No exclusions or conditions are provided, so usage guidance is implied rather than explicit.

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

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

With no annotations, the description carries the full burden. It discloses the cost ($0.09 via x402) and the lookup types, implying a read-only network operation. It does not describe return format, error handling, or rate limits, but the main behavior is clear for such a simple lookup 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?

A single sentence conveys the purpose, cost, and data sources with no unnecessary words. It is front-loaded with the price and clearly structured with a dash separating the title from the details.

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

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

For a simple 2-parameter tool with no output schema, the description lists the exact enrichments (RDAP, MX, Wikipedia), states the cost, and identifies the required input domain. It could mention the output format or what happens on invalid domains, but this is sufficient for the tool's simplicity.

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 baseline is 3. The description adds meaningful context by stating the cost and the x402 payment method, which directly relates to the x_payment parameter beyond what the schema says. It does not redundantly repeat schema details.

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

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

The description clearly states the tool looks up specific data points: company domain registration age (RDAP), DNS MX mail servers, and Wikipedia metadata. The verb 'lookup' is specific and the resource is well-defined. This differentiates it from siblings like wikipedia_lookup or web_search.

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 use for B2B lead enrichment by stating 'B2B Domain & Lead Enrichment' and lists the data sources. However, it does not explicitly state when to use this tool over alternatives like web_search or wikipedia_lookup, nor does it mention exclusions or prerequisites beyond payment.

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 well: it discloses the cost ('$0.09 via x402'), the fact it is a single call, the specific data sources (live DEX liquidity, 24h volume, buy/sell flow, momentum, pair age), the integration of GoPlus honeypot/tax/owner-risk checks, and the explicit limitation that it never trades or promises returns. It lacks details on failure modes or rate limits but is substantially transparent for a read-only intelligence tool.

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

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

The description is a single dense sentence, but every clause adds meaningful information: purpose, data aggregated, risk checks, classification output, and limitations. It is front-loaded with the most important facts ('$0.09 via x402: one ranked Base launch-intelligence call') and contains no filler. It is slightly long but 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?

Despite lacking an output schema, the description covers what is returned (classifications), what inputs it uses (parameters), what data sources are consulted, and its non-trading nature. For a tool with only three parameters and no output schema, this is quite complete. It could be improved by hinting at the format or scale of results, but it is adequate for an agent to invoke 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?

Schema description coverage is 67% (two of three parameters have descriptions). The tool description does not mention any parameters directly, so it fails to compensate for the undocumented x_payment parameter. While 'limit' and 'min_liquidity' are already explained in the schema, the description adds no extra meaning, and the payment parameter remains a mystery. This is a clear 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 has a specific verb ('finds') and a clear resource ('new/boosted Base tokens'), and it states the exact output: 'returns transparent REVIEW/WATCH/LOW_SIGNAL/REJECT classifications.' It also distinguishes itself from sibling tools by explicitly focusing on 'Base launch-intelligence' and ranking, which contrasts with crosschain_attention_radar or token_launches_feed.

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 on when to use this tool: for ranked Base launch intelligence with risk checks. It also includes an exclusion: 'Market intelligence only; it never trades or promises returns,' which tells the agent not to use it for trading or financial advice. However, it does not explicitly name alternatives or state 'use this instead of X,' 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?

No annotations are provided, so the description carries the full burden. It only discloses the cost ($0.09 via x402) and mentions payment, but does not describe side effects, response format, or what 'fallback routing' actually does (e.g., failover criteria, latency, 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 very short, but it is padded with promotional language ('Premium') and repeats the fallback concept in both sentences. A more tightly written single sentence could convey the essentials.

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 proxy tool with no output schema and minimal annotations, the description lacks crucial context: expected return format, prerequisites (e.g., x402 payment), and when to use it. The cost is noted but not the actual behavior or use case.

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 50% coverage (only x_payment is described). The tool description adds no meaning for the required 'prompt' parameter, leaving agents to guess what should be sent. It does mention x402 in relation to payment, but not the parameter 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 states the resource (AWS Bedrock) and the concept of fallback routing, but lacks a clear action verb like 'send' or 'generate.' It is not a tautology, but the purpose is vague and could be inferred more strongly from the 'prompt' parameter.

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 vertex_proxy or llm_chat_completions. The word 'Fallback' implies a secondary-use scenario, but it is not explicitly stated when or how to choose this over 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 burden and does disclose cost, methodology (real buyer questions through an LLM), and key outputs (score, mention rate, competitor names, evidence). However, it does not specify side effects, permission requirements, rate limits, or what happens when the x402 payment is absent, and 'full evidence' remains vague.

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 dense sentence, but it packs in price, payment method, methodology, and outputs without obvious filler. It is front-loaded with the premium cost and purpose, making it compact and reasonably well structured, though the telegraphic style slightly hurts 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?

There is no output schema or annotations, so the description must explain expected outcomes; it lists the main outputs but omits payment/payload behavior, market default implications, and any error or edge-case handling. It is adequate for a simple audit tool but incomplete for a paid API without a defined response contract.

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 all four parameters, so baseline 3 is appropriate. The description adds little beyond the schema—it mentions score and audit but does not detail how brand, category, market, or x_payment affect the call.

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 live brand AI-visibility audit with specific outputs: score 0-100, mention rate, competitor AI mentions, and evidence. The verb 'audit' plus the resource 'brand' gives a specific purpose, and the LLM-based buyer-question methodology distinguishes it from sibling tools like ai_visibility_index or ai_visibility_signal.

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 versus alternatives, nor any exclusions or prerequisites beyond 'PREMIUM' and x402 payment. The description implies it is for brand AI-visibility measurement, but it does not name sibling tools or provide decision criteria.

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 well: it discloses parallel execution, one-payment pricing, and that per-read failures surface individually with a partial flag so a batch never falsely reports success. It omits rate limits and the auth/payment mechanics behind x_payment, keeping it from a 5.

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 pricing and value proposition are front-loaded, and each sentence contributes distinct information (cost, batching benefit, failure semantics). It is slightly dense across three sentences 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?

With no output schema or annotations, the description still conveys the essential behavioral contract (parallelism, partial-failure flag, single-payment model) needed to invoke correctly. Return-shape detail is thin, but the failure-handling disclosure covers the main risk of a batch tool.

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

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

Schema coverage is 67% and the description reinforces the reads combinations ('any combination') while listing the op categories, and the 'x402'/$0.005 phrasing adds context for the otherwise undocumented x_payment parameter. The chain selection and its default are left to the schema, so it adds value but not full 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 states a specific verb (batch reads), resource (on-chain reads), and scope (up to ten reads for one payment, run in parallel) and enumerates the exact read categories, so an agent can distinguish it from the individual chain_* siblings without opening a 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?

It gives a clear use case ('Reconciling a wallet') and the rationale for batching versus one payment per read, which implies the when-to-use context. It stops short of explicitly naming the alternatives (e.g. chain_native_balance) or stating exclusions, so it is clear but not fully routing.

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 well: it discloses the $0.005 x402 payment requirement, that it accepts height or latest/finalized/safe, and the supported chains. It doesn't cover rate limits, auth beyond x402, or error behavior, but the cost/payment disclosure is genuinely useful context not available elsewhere.

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

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

Front-loaded with the price then the payload contents, packed into a few dense sentences with no filler. The routing contrast is well placed after the content list, though the opening price token is slightly abrupt.

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 compensates by enumerating the returned fields, and it covers accepted inputs and supported chains. An agent has enough to call it correctly; only edge details like pagination or error behavior are absent.

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 67%; the schema documents chain and number, and the description reinforces these ('Accepts a height or latest/finalized/safe', lists the six chains). The x_payment parameter is undocumented in both, and the description adds no format detail beyond the schema, so baseline 3 is appropriate.

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

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

States a specific verb+resource ('the full header of any block') and enumerates exactly what it returns: timestamp/age, transaction count, gas used vs limit with utilization and congested flag, base fee, miner and parent hash. It explicitly contrasts with the sibling chain_block_number, so an agent can distinguish them without opening either 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 line '/chain/block-number says WHERE the chain is; this says WHEN that block happened and how contested it was' gives a clear selection rule against the nearest alternative. It stops short of stating when-not-to-use or listing other siblings, but the core routing guidance is present.

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

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

With no annotations, the description must carry the whole behavioural load, and it does disclose real value: the $0.005 x402 cost, the per-chain finality thresholds (Ethereum 64, Polygon 128, OP-stack 60), and the no-receipt-vs-failed distinction. It still omits the mechanics an agent needs to act — how x_payment must be supplied, whether the call is a pure read, and latency/retry behaviour — which is a meaningful gap for an unannotated paid endpoint.

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

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

Front-loaded with the paid cost and the core question, then returns, then the two anti-footgun caveats in ascending order of importance. Dense but every sentence carries information; only the rhetorical closing clauses could be trimmed.

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 compensates by enumerating the return fields (status, block, tip, confirmations, gas used, fee paid, log count), and it supplies the chain-specific finality thresholds an agent needs to interpret them. The remaining hole is the undocumented payment parameter and the lack of any sibling routing guidance.

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 67%: hash and chain are documented, but x_payment has no schema description. The description adds context useful for x_payment by stating the $0.005 x402 cost, but never explains what value the parameter should carry. The two documented parameters are handled entirely by the schema, so the net contribution is thin.

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?

Names a specific resource (a transaction, addressed by hash and chain) and a specific purpose: did it land, how deep, is it final. It goes beyond a bare restatement by framing the finality question. It does not, however, name or contrast with the obvious sibling chain_transaction_status, leaving the boundary between the two to inference.

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?

Gives clear context for use — checking whether a payment is settled — and warns that 'a success with two confirmations is not a settled payment' and that 'no receipt yet' must not be conflated with 'failed'. What is missing is a routing rule: nothing tells the agent when to pick this over chain_transaction_status or chain_transaction_explain.

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?

Since no annotations are provided, the description carries the full transparency burden. It discloses that this is a live ENS registry, that the call costs $0.005 and is paid via x402, that resolution works in both directions, and that the avatar is returned only when set. It does not describe failure modes or behavior for names/addresses with no ENS mapping, but it provides substantial and accurate 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 tightly written and front-loaded. The first sentence states the full functionality with examples, the second sentence explains the practical use case, and the third sentence adds data-source and payment context. Every sentence contributes to the agent's understanding without repeating schema information.

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

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

Given there is no output schema and no annotations, the description covers the important parts: what inputs do, what outputs to expect in both directions, the cost/payment model, the live registry source, and the intended use case. It could be more complete with explicit behavior for invalid names or addresses without a reverse record, but overall it is sufficiently complete for a simple resolver-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?

Schema coverage is 67%: name and address already have descriptive schema text, and the description adds examples and directional semantics. However, the x_payment parameter is not described in the schema, and the description only hints at it through '$0.005 via x402' without explaining how to set the parameter. The description also does not state explicitly that exactly one of name or address should be supplied.

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 first sentence clearly specifies the action: resolve ENS in either direction on Ethereum, with exact examples for both name-to-address and address-to-name. It is specific about the resource (Ethereum ENS registry) and distinguishes itself from sibling chain_* tools by covering bidirectional ENS resolution plus avatar support.

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 concrete use case: the identity lookup that wallet, payment, and UX agents perform to verify destinations or display human-readable names instead of raw hex addresses. It also frames this as a paid alternative to running your own resolver, which helps an agent decide when to invoke the tool. It does not explicitly name alternatives or state when not to use it, but the context is clear.

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, so the description carries the full burden. It discloses useful context: the $0.005 x402 cost, the read-only nature (implies 'estimate'), and 6-chain coverage. However it never states what the estimate returns (a gas unit figure?), what the x_payment parameter expects, or payment/auth requirements beyond the price mention.

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 core purpose is front-loaded, and the second sentence covering parameter passing is short. The '$0.005 via x402' prefix is dense but useful pricing signal rather than waste. Slightly cramped in one long sentence, but nothing is redundant.

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 6-parameter paid tool with no output schema and no annotations, the description covers purpose, cost and chains but leaves the return value, error modes (e.g. revert/data decoding failures) and payment mechanics unstated. Adequate but with clear gaps.

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

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

Schema coverage is 67%, so the schema already documents to/data/chain/value. The description's 'Pass to (+ optional from/value/data)' adds little beyond restating required vs optional, and it omits chain and x_payment entirely. Baseline 3 is appropriate since the schema does most of the work.

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+resource: 'estimate the gas a transaction will use (eth_estimateGas) across 6 chains'. This is clearly distinguishable from per-block siblings like chain_gas_price or chain_fee_history because it is transaction-specific rather than network-baseline. The underlying RPC method is even named.

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?

Frames the use case explicitly: the 'pre-send read tx-building, trading and settlement agents make to size gas and avoid out-of-gas reverts.' This tells an agent when this tool is appropriate (before sending a tx to size gas). No alternatives are named, 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?

There are no annotations, so the description carries the full behavioral burden, and it does disclose meaningful traits: the $0.005 x402 price, a 25-block default window, automatic narrowing when a node refuses on result size, and that every cap/narrowing is named in the response rather than applied silently. It still omits return format specifics and any rate-limit or payment-flow detail beyond the price.

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?

One dense paragraph that is front-loaded with price and core purpose, then behavior, then scope. The trailing chain list is slightly redundant with the schema enum, but overall it is tight and every clause carries information.

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

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

For a 9-parameter tool with no annotations and no output schema, the description covers purpose, key behavioral guarantees, and supported chains well. It stops short of explicitly restating the 'address or topic0 required' constraint (left to the schema) and gives no return-shape detail, but it is largely complete.

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

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

Schema coverage is only 33% across 9 parameters, so the description must compensate. It does describe the address, topic, and block-range parameters in prose and lists the supported chains, but it says nothing about topic1-3 ordering, toBlock/fromBlock formats, or x_payment, so it only partially fills the gap left by 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?

States a specific verb+resource: raw event logs by contract address and/or indexed topics over a block range, and maps it to the underlying primitive (eth_getLogs), calling itself 'the indexing primitive.' This distinguishes it from sibling read tools like chain_batch_reads and get_chain_call without opening any 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?

It establishes context by labeling itself 'the indexing primitive' and describing the contract-address/topic/block-range shape, which implies when it is the right tool. However, it never names an alternative or states an explicit when-not condition versus siblings such as chain_batch_reads or get_chain_call, leaving routing to inference.

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 does disclose cost and access ('$0.005 via x402') and the output shape, which is valuable. It stops short of stating read-only status, rate limits, or failure behavior, so it only partially covers the behavioral profile.

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

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

Front-loaded with cost and purpose, then outputs, then the sibling contrast, then supported chains. Sentences are informative and mostly earn their place, though the 'single gas number' sentence leans slightly rhetorical.

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?

No output schema exists, so the description usefully describes return content (trend, percentiles, utilization, recommendations). It covers the primary parameters adequately but leaves x_payment unexplained, a minor gap for a 3-param tool.

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

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

Schema coverage is 67%. The description repeats the chain list already given in the schema and mentions 'N blocks' matching the blocks param, adding no syntax beyond the schema. The x_payment parameter remains undocumented in both description and schema, leaving a 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?

States a specific verb+resource (EIP-1559 fee history) and enumerates the concrete outputs: base-fee trend, priority-fee percentiles, mean block utilization, and recommended maxFeePerGas/maxPriorityFeePerGas. It also distinguishes itself from sibling chain_gas_price by contrasting 'a single gas number' with trend 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?

The line 'A single gas number cannot tell you whether fees are rising; this can' clearly signals when to reach for this tool over chain_gas_price or chain_estimate_gas. However, there is no explicit when-not guidance or statement of prerequisites beyond the payment note.

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 exist, so the description carries the full burden, and it delivers unusually concrete operational context: cost ($0.002), payment rail (x402), data source (Blockscout), and freshness (live). It leaves read-only status implicit rather than stated and says nothing about rate limits or failure modes, but for a simple price read this is well above the norm.

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 price is front-loaded in the first token, then purpose, scope, and provenance in a compact block with no redundant sentences. Minor promotional phrasing ('every trading, sniping and settlement agent') costs a little density but does not obscure the facts.

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 low-complexity read tool with no output schema and no annotations, the description supplies what an agent needs: what is returned (three fee tiers in gwei), the chain scope, the data source, and the payment requirement. Only the read-only nature and the `x_payment` input format remain 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?

Schema coverage is 50%: `chain` is documented in the schema, but `x_payment` is undocumented there and the description only hints at it via 'via x402' and the $0.002 price. The chain list in the description matches the schema rather than adding format or default details beyond the parenthetical 'default ethereum'. Partial compensation for the coverage gap, so a mid 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?

States a specific verb and resource — live gas prices split into slow/average/fast tiers in gwei — and enumerates the supported chains (Base, Ethereum, Optimism, Arbitrum, Polygon, Gnosis). An agent immediately knows what it gets back. It never names a sibling (e.g. chain_estimate_gas or chain_fee_history) to draw the boundary explicitly, 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?

Frames the use case clearly: 'the pre-transaction read ... before sending a tx to size the fee,' which tells an agent when to reach for it. It also implies an alternative ('one paid call instead of running your own RPC'). There is no explicit when-not guidance or named sibling alternative, so it is clear context rather than full routing.

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 usefully discloses cost ($0.005 via x402), that the result is a single round trip, and the verdict semantics across the supported chains. However, it does not explain the x402 payment requirement or the x_payment parameter, and gives no rate-limit or failure-mode 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 value proposition and price are front-loaded, and the three sentences are mostly economical. There is mild redundancy between the 'replaces X calls' claim and the 'one-sixth the price' claim, but nothing wasteful enough to hurt.

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 does a reasonable job: it names the chains, the aggregated data and the verdict it returns. It leaves the x402 payment mechanics and the x_payment parameter unexplained, which is the main completeness gap.

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

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

Schema coverage is only 50%, with x_payment entirely undocumented. The description restates the supported chains (Base, Ethereum, Optimism, Arbitrum, Polygon, Gnosis, Robinhood) which mirrors the chain param description and the default, but adds nothing about x_payment or how the payment field is supplied, so it does not compensate for the coverage gap.

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

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

The description states a specific verb and resource (a composite 'heartbeat' read) and unpacks exactly what it aggregates: chain-id, block-tip, block-freshness, gas, fee-history and finality. It also names its return (HEALTHY/CONGESTED/STALE verdict), so an agent can distinguish it from chain_id, chain_gas_price, chain_fee_history and get_chain_block_number without opening any 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?

It frames itself as a 'pre-action heartbeat' and explicitly names the sibling calls it replaces, which gives strong positive routing guidance. It does not state when the granular siblings would be preferable (e.g. when you need only one datum), so the 'when-not' side is left to inference.

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, and the description does not mention whether the tool is read-only, has side effects, requires authentication, or costs anything beyond the implied x402 payment. This leaves behavioral impact entirely unspecified.

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

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

The description is extremely concise, conveying the tool's purpose and a key differentiator in two sentences. No unnecessary words 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 tool is simple, but the description does not mention the output format (e.g., integer, hex) or explain how the payment parameter works. Without an output schema, this missing information leaves the tool incompletely specified.

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 'chain' parameter is well described with allowed values and a default. However, 'x_payment' has no description and its role is unclear. Since half the parameters are undocumented, the description only partially adds value 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 indicates the tool returns the EIP-155 chain ID for any of 6 chains, and mentions a use case of confirming the chain before signing. It lacks an explicit verb like 'get' or 'retrieve', but the intent 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?

It provides a specific scenario (confirming chain before signing) and contrasts with a single-chain alternative, implying use for multi-chain needs. However, it does not explicitly state when to avoid this tool or compare with other sibling tools that might also return chain-related data.

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

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

With no annotations, the description carries the full burden well: it discloses the pricing model ($0.005 via x402), the authoritative data source (the chain's own GasPriceOracle.getL1Fee), and fork-robustness (Ecotone, Fjord and later). It stops short of rate limits or failure behavior, and the payment requirement is stated as cost rather than an auth precondition.

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?

Four dense sentences with essentially no filler; each conveys distinct information (cost, definition, data source, scope). It front-loads price rather than purpose, which slightly delays the core 'what it does' signal, but otherwise the structure is tight.

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 4-parameter, no-output-schema, no-annotation tool, the description supplies the essential context: what is computed, from where, on which chains, and at what cost. The main gap is the absence of any statement about the returned value's shape or units, though with no output schema that is a minor omission.

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 75% and the description adds real meaning: it explains that passing data prices the actual transaction exactly, implying it overrides the bytes-based default (1200) documented in the schema, and it reinforces the chain constraint. It adds little for the x_payment parameter, which remains opaque.

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?

Names a specific resource (the L1 data-availability fee for OP-stack transactions) and a precise scope (the portion ON TOP of L2 execution gas). It explicitly carves itself out from sibling estimators by noting ordinary gas estimators omit this half, so an agent can distinguish it from chain_estimate_gas and chain_gas_price 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?

Gives a clear actionable condition ('Pass data=0x... to price your actual transaction exactly') and a hard constraint ('Base and Optimism only'). It implies complementarity with ordinary gas estimators but never states the explicit when/when-not versus siblings like chain_estimate_gas, leaving that to inference.

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 data is 'live from Blockscout', mentions the cost ($0.003 via x402), and implies it is an on-chain RPC read (which suggests a read-only operation, but it does not explicitly state safety). It also reveals the scope of chains. This extra information adds context beyond what annotations would typically provide, even though annotations are missing. It is not misleading; however, it could be more explicit about being a read-only operation.

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

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

The description is somewhat long but front-loaded with the key benefit (core on-chain RPC read) and then provides details about the data included and chain coverage. It is structured but could be trimmed for clarity. However, every sentence adds value—no fluff.

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

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

Given the tool's moderate complexity (6 chains, output includes balance, USD value, transaction count), the description covers the essential functionality. It does not explain output format, but no output schema is given, so the description is the only source. It mentions they are 'live' and 'from Blockscout', which is good. It could mention pagination or rate limits, but for a balance check tool, this is adequate.

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

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

Schema description coverage is 67% (two of three parameters are described). The description adds the meaning of the address and chain, specifying the chain options and default. It does not describe the x_payment parameter, but that is likely a payment mechanism and not essential for the core functionality. The description adds meaning for the chain parameter beyond the schema's description, but the coverage is not 100%, so the description partially compensates.

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: reads the native coin balance for any address across multiple chains, providing live USD value and outgoing transaction count. It explicitly distinguishes from sibling tools, especially noting the comparison to 'onesource's Ethereum-only' tool and the 6 chain support.

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

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

The description implies the use case: high-frequency balance checks for wallet-tracking, settlement, and trading agents. It contrasts with a sibling tool (onesource) but does not explicitly mention usage exclusions or specifics like when to use alternatives. It says 'vs onesource's Ethereum-only' which is a clear alt hint, but no explicit when-to-use vs other chain 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 full burden, and it discloses the cost/payment model ($0.005 via x402), the read-only nature ('Read from the contract'), and a freshness guarantee. It omits rate limits, failure modes, and error behavior, so it falls short of complete but adds real 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?

Front-loaded with cost and purpose, then return fields, then the freshness rationale and supported chains. Slightly dense but every clause earns its place; 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?

No output schema exists, so the description must describe returns — it lists the returned fields and the tokenURI classification scheme, which is sufficient to interpret the result. Missing only edge-case behavior for a 4-param read tool.

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

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

Schema coverage is 75%, covering chain/contract/token_id, but the x_payment parameter is undocumented in the schema; the description's '$0.005 via x402' explains that parameter's purpose. It also clarifies what the tokenURI value is classified into, adding 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?

States a specific verb+resource (reads NFT ownership and metadata) and enumerates the exact return fields (ownerOf, tokenURI, collection name/symbol). It is clearly distinguishable from siblings like chain_token_identity or chain_token_supply without opening any 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?

Gives a clear use rationale: 'Read from the contract, so it is correct for tokens minted seconds ago and collections no marketplace has indexed.' That tells the agent when this beats an indexed/marketplace source, but no alternative sibling is named and there are no explicit exclusions.

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

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

No annotations are provided, so the description carries the full burden. It usefully discloses the cost model ('$0.005 via x402'), which explains the x_payment parameter, and 'read' implies a non-mutating operation. It says nothing about what is returned (raw hex word), error behavior on invalid slots, or payment failure 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?

One tight sentence front-loads the price and the core verb/resource, then adds chains and audience. Every clause is load-bearing, though the trailing audience list is slightly crammed and could be trimmed.

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, it covers cost, purpose, chain scope, and required inputs adequately. The remaining gap is the shape of the return value (raw storage word) and payment/error semantics, which an agent would need to infer.

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 75% and the schema already documents slot format, address format, and the chain enum-like list with a default. The description only adds 'Pass address + slot', which repeats the required set without new syntax or constraint detail; the x_payment param is only implied by the x402 mention.

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?

Names the exact operation ('read a raw contract storage slot (eth_getStorageAt)'), the scope (6 chains), and the consumer ('audit, proxy-resolution and advanced trading agents'). It is clearly distinguishable from sibling reads like get_chain_call, get_chain_code, or chain_batch_reads.

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?

Gives concrete use contexts (direct state inspection, audit, proxy resolution) which imply when to reach for this over a decoded call tool. However, it never names an alternative sibling or states an exclusion (e.g., 'use get_chain_call for ABI-decoded function calls'), so routing is left partly to inference.

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 cost ($0.005 via x402), the contract-read data source, legacy bytes32 decoding, and that a missing decimals() is flagged rather than assumed. It omits return format and error behavior, so not a full 5.

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

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

Front-loads what the tool does before elaborating on why it matters. The indexer-gap sentence is somewhat promotional but earns its place by justifying usage. Slightly longer than needed.

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 3-param, no-annotation, no-output-schema tool it covers purpose, cost, data source, and edge-case handling well. Missing only return-format expectations and the meaning of x_payment, which is a modest gap.

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

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

Schema coverage is 67%: chain has an inline enum with default, token is described, but x_payment is undocumented. The description adds no parameter-level detail beyond the schema, so baseline 3 for adequate structured coverage is correct.

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 specific verb+resource: reads ERC-20 name, symbol, decimals, total supply straight off the contract plus an existence check. It distinguishes itself from siblings like chain_token_supply and dex_token_data by naming the contract-vs-indexer mechanism.

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

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

Gives clear when-to-use context: 'The first read to make on an unknown contract' and the fresh-launch / no-explorer-coverage case where indexer-backed lookups fail. It contrasts against the alternative class (indexer-backed lookups) but does not name a specific sibling to route to or state exclusions.

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

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

With no annotations provided, the description carries the full behavioral burden. It discloses meaningful traits beyond the schema: the call costs $0.01 via x402, data is live from Blockscout, and it is a one-call replacement for running an RPC. It does not cover rate limits, failure behavior, or auth prerequisites, so it is strong but not exhaustive.

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

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

Three sentences, each earning its place: the payload and scope, the use case, and the data-source/value proposition. The concrete output fields are front-loaded, and there is zero filler or repetition 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?

Despite having no output schema and no annotations, the description covers the returned fields, supported chains, cost, and data freshness, which is enough for an agent to call the single required parameter correctly. The gaps are the undocumented x_payment parameter and unspecified error behavior for unsupported inputs, which keep it from a 5.

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 67%, with address and chain already described. The description adds some value by clarifying that address must be an ERC-20/721 token contract and by listing the supported chains, but it leaves x_payment completely unexplained in both the schema and description, and it adds no format or syntax detail 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 with precise scope: it returns 'total supply, holder count, decimals, and live USD price / market cap' for 'any ERC-20/721 token contract' across six named chains. The listed fields and the ERC-20/721 target clearly distinguish it from siblings like chain_token_identity and chain_native_balance without needing to open 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 second sentence gives explicit use-case context: 'the supply read trading, valuation and risk agents make to size circulating supply, dilution and holder distribution before pricing or trading a token.' This tells an agent when to reach for this tool, but it does not name alternatives or state when not to use it, stopping 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, the description carries the full burden: it discloses the paid cost ($0.005 via x402), the live source (Blockscout), that it is a read operation, and lists returned fields. However it omits key operational behavior such as x_payment prerequisites, failure/error handling, and whether payment is retried or required per 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?

Front-loads the cost and core purpose, and most of the long sentence earns its place by enumerating outputs and chains. There is minor promotional padding in 'one paid call instead of running your own indexer + ABI decoder,' but overall it is dense and useful rather than rambling.

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

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

Without an output schema or annotations, the description does substantial compensating work by listing return contents (actors, asset changes, status, fee, decoded method) and supported chains. It still leaves the x_payment parameter and error/not-found behavior unexplained, which an agent needs for a paid 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?

Schema coverage is 67%: hash and chain are documented in the schema, and the description reinforces them by naming the hash input and enumerating the supported chains. The x_payment parameter has no description in either the schema or the description, leaving the payment mechanism 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?

States a specific verb ('decode'), resource ('transaction by hash'), and output ('plain-English explanation'), then distinguishes itself from chain_transaction_status with 'The read agents make to UNDERSTAND a tx, not just confirm it landed.' An agent can tell exactly what this does and how it differs from the status sibling.

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

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

Gives clear when-to-use context ('for wallet UX, accounting, risk, dispute and trading agents') and a when-not contrast ('not just confirm it landed'). The alternative is implied rather than named, so it stops short of the explicit sibling routing a 5 would require.

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 for behavioral disclosure. It adds useful context: the exact cost ($0.008 via x402), that it is a read operation, the live data source (Blockscout), and supported networks. It does not cover rate limits, failure modes, or invalid-hash behavior, but for a simple read lookup it provides solid 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 compact and front-loaded, packing the core purpose, returned fields, use case, networks, source, and cost into four short sentences. It earns its length, though the second sentence contains a grammatical awkwardness ('The read every...') and the structure could be slightly cleaner.

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 3 simple parameters and no output schema, the description covers the essentials: what it returns, which chains it supports, how it is paid for, and where the data comes from. It could be more complete by explaining x_payment and possible error conditions, but it is sufficient for a low-complexity lookup tool.

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

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

The schema already documents hash and chain, covering 67% of parameters, so the description does not need to repeat those basics. It adds value by explaining the hash-based lookup and supported chains, but it does not explain the undocumented x_payment parameter or connect the '$0.008 via x402' pricing to that parameter. Thus it stays at the baseline rather than rising above it.

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 names the action ('look up any transaction by hash') and the specific resource (transaction status by hash), while enumerating the returned fields: confirmation status, block number, confirmations, value, from/to, fee paid, gas used, and decoded method. It also frames the exact use case for settlement, trading, and payment agents, making it easy to distinguish 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 provides clear context for when to use it: 'The read every settlement, trading and payment agent polls after sending a tx to confirm it landed.' It also gives practical guidance about using one paid call instead of running an RPC. However, it does not explicitly name alternatives or state when not to use it, 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?

No annotations exist. The description mentions 'read' and 'free-data' but also '$0.01 via x402', creating confusion about cost and idempotency. No behavioral details like side effects or auth requirements are provided.

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 with key info in the first. The second sentence is slightly awkward but still efficient. Minor punctuation issues do not detract significantly.

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 fails to explain return format, error handling, or usage of 'x_payment'. Significant gaps remain for agent selection.

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

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

Schema coverage is 50% with only 'domain' described. The description adds no detail about 'x_payment' and does not clarify parameter formatting or constraints beyond the schema's minimal info.

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 enriches company/domain data with RDAP, DNS, and Wikipedia data, distinguishing it from related tools like b2b_lead_enrichment or wikipedia_lookup.

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 use for sales, research, and qualification agents but lacks explicit when-to-use or when-not-to-use guidance, and does not mention 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, the description carries the burden of disclosure and does well: it reveals the $0.01 x402 cost, the combined data sources, and the recommendation output. It does not fully describe failure modes or the exact mechanics of x_payment, but it is honest about the paid, aggregator nature of the 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 dense sentences efficiently cover cost, behavior, output, use case, and alternative. The most important facts are front-loaded, and every sentence earns its place without fluff.

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

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

For a paid connector with no annotations and no output schema, the description covers the core invocation context: what it does, what it costs, what it returns, and when to use it. The main missing piece is the x_payment parameter format, but the description still gives enough context for an agent to decide whether and how to call this tool.

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

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

The schema already documents address and chain well, including defaults and options. The description adds only general payment context via '$0.01 via x402' but does not explain the undocumented x_payment parameter's structure or requirements. With 67% schema coverage, the description does not need to compensate heavily, but the x_payment gap remains.

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 this tool fuses GoPlus security checks and Dexscreener market data into a single GO/CAUTION/AVOID recommendation. It names the specific resources and the aggregate behavior, and it differentiates itself from alternatives like chaining separate rug-check and DEX calls.

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

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

The description explicitly frames this as the call trading and sniping agents should make instead of chaining separate rug-check and dex tools. It gives a clear use case and names the alternative pattern, though it does not list specific sibling tools 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?

With no annotations, the description carries the full transparency burden. It adds useful behavioral context: the $0.09 cost via x402, the World Bank public-domain source, live indicator data, and the inclusion of the year for each value. However, it does not disclose potential failure modes, response format, or details about payment handling, leaving some important operational ambiguity.

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

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

The description is a single, dense sentence that packs in cost, scope, indicators, data vintage, source, and target audience. Every clause contributes information, and the use of em-dashes and lists keeps it readable. It is slightly long but appropriately so for the number of indicators and context it conveys.

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

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

Without an output schema, the description compensates by listing the exact indicators returned and noting that each includes its year, giving an agent a solid mental model of the response. Combined with the source and cost information, this covers most of the essential context, though it omits the response format and any x_payment mechanics. The tool is simple enough that this is nearly 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 description coverage is 50%: 'country' is described with ISO2/ISO3 examples, but 'x_payment' has no description. The tool description mentions the $0.09 x402 cost but does not explain how the 'x_payment' parameter should be used or what value it expects. It also adds useful context for 'country' by stating 200+ countries, but the critical payment parameter remains underspecified.

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 (macro/economic indicators for 200+ countries) and enumerates the specific indicators (GDP, inflation, unemployment, etc.), which effectively distinguishes it from similar macroeconomic tools like us_macro_regime. However, it lacks an explicit imperative verb (e.g., 'retrieve' or 'get'), relying on the tool's noun name to convey the action.

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 'For macro, finance, research and trading agents' gives a target audience and the 'in one call' efficiency suggests a broad lookup use case, but it does not explicitly state when to choose this tool over alternatives or when not to use it. No sibling tools are named, and no exclusions 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 full burden. It discloses the per-call cost ($0.09 via x402), the output classification set, the conditional nature of contract-risk coverage ('where supported'), and explicit non-trading/non-predicting behavior. This is strong, though it doesn't address rate limits, error cases, or behavior on unsupported chains.

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 pack a large amount of relevant information with no filler: the cost, the chains, the compared metrics, the gap-naming behavior, the output classes, and exclusions. Information is front-loaded and every phrase contributes value.

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

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

For a tool with no output schema and only 4 parameters, the description covers purpose, inputs (chains, data fields), outputs (classifications), cost, and exclusions. It addresses the variable risk-coverage behavior and explicitly lists the output categories, making the tool's behavior sufficiently complete for selection and correct invocation.

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

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

Schema description coverage is 75% (limit, chains, min_liquidity have descriptions; x_payment does not). The description adds some context for chains (explicitly listing the four chains) and mentions data dimensions that map to filtering (liquidity, volume), but it does not compensate for the undocumented x_payment parameter. Baseline 3 is appropriate.

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

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

The description clearly states a specific verb+resource: compares current token discovery attention across four named chains, and joins multiple data dimensions to produce research classifications. This distinguishes it from siblings like dex_token_data (single chain) and token_security_check (risk-only) by emphasizing crosschain aggregation and classification output.

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 on what the tool does and its scope (crosschain research, not trading/profit prediction). It implicitly signals appropriate use cases (comparing attention across chains) but does not name alternative tools or explicitly state when not to use it beyond the 'never trades or predicts profit' clarification.

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 reasonably well: it discloses the cost and payment rail ('$0.09 via x402'), the exact model being probed, the shape of the returned signal, and an important caveat that the returned names are 'unverified, not checked against the category'. It stops short of covering latency, determinism, caching, or failure behavior for a paid 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 dense sentences with no filler; the price is front-loaded ahead of the capability statement. The opening '$0.09 via x402:' fragment is slightly abrupt but does deliver cost information immediately.

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?

No output schema exists, so the description must explain returns, and it does: score 0-100, mention rate, and the names the model gave, plus the caveat about their reliability. Payment is flagged. It is largely complete for a single-call scoring tool, missing only error or empty-category 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?

Schema coverage is 67%, so the baseline is near 3. The description adds useful context for 'project' and 'category' by explaining the comparison is against 'the best in its category', but it says nothing about 'x_payment' beyond the x402 mention, leaving that parameter opaque in both schema and 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 gives a concrete verb+resource: it asks one named model (llama-3.3-70b on Workers AI) whether it recommends a given token/protocol/chain for a category, and returns an AI-visibility score, mention rate, and the names produced. That is far more specific than the name alone. It does not, however, contrast itself with near-identical siblings such as ai_visibility_index, ai_visibility_signal, and brand_ai_visibility_check, so an agent must guess which one to pick.

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 closing line frames it as 'a narrative/attention signal for crypto trading and research agents', which implies when it is useful. There is no explicit when-not guidance, no mention of the sibling visibility tools, and no statement about when a single-model snapshot is insufficient.

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. It discloses the cost ($0.09 via x402) and the real-time nature, but does not explain the payment flow, response format, rate limits, or side effects. This is minimal disclosure for a potentially paid 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 a single sentence, making it concise and easy to parse. The pricing info at the start is a bit distracting but not harmful. It is appropriately sized for the tool's simplicity.

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 clear scope of the data returned, but lacks context on the unusual x402 payment mechanism and no output schema is present, leaving the agent to infer the exact response structure. Sufficient but not rich.

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

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

Schema description coverage is 100%, so the baseline is 3. The description does not add semantics beyond the schema; it focuses on outputs (price, cap, volume) rather than explaining the ids or x_payment parameter beyond what the schema already provides.

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 live crypto market metrics including price, market cap, and 24h volume. The scope is specific and the resource (cryptocurrencies) is clear, though the verb is implicit rather than explicit.

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

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

No guidance is given on when to use this tool versus siblings like crypto_prices. The description does not mention alternatives, prerequisites, or context for when this tool is preferred.

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. It usefully discloses the $0.01 x402 cost and the spot/historical nature of the data. However, it does not describe response shape, error behavior, rate limits, or whether this is a safe read-only operation.

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

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

One dense sentence covers cost, data type, identifier formats, and examples. Every element earns its place and the most important caveat ('Prefer ?coins=') is placed at the end as a recommendation.

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 is sufficient for a straightforward price lookup but leaves gaps: no output schema, no annotations, no explanation of how to request historical vs spot data via the 'at' parameter, and no mention of the response format.

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 high, but the description adds real value by clarifying that 'coins' is preferred and supports tickers or chain:address formats, while 'ids' is legacy CoinGecko IDs. This goes beyond the schema's terse examples, though x_payment 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?

Description clearly states a specific function: retrieving spot or historical USD prices. It distinguishes from crypto sibling tools by specifying identifiers (ticker, CoinGecko id, chain:address) and giving concrete examples (BTC, ETH, bitcoin, base:0x…).

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

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

No explicit guidance on when to use this tool instead of siblings like crypto_market_metrics, dex_token_data, or get_crypto_liquidations. 'Prefer ?coins=' is parameter guidance, not alternative selection guidance.

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

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

No annotations are provided, so the description must carry the burden. It mentions a cost and a 'verdict' but lacks details on data sources, freshness, rate limits, or whether it is read-only. Behavior is minimally 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 very concise, packing cost, comparison scope, and output components into one sentence. However, it front-loads cost over functionality, which could be reordered for clarity.

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

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

With no output schema and a complex comparison tool, the description should explain return values (yields, T-bill rate, spread, verdict). It does not, leaving agents guessing about the output structure.

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

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

Schema coverage is 50% (min_tvl described, x_payment not). The description adds no additional meaning to either parameter, leaving x_payment unexplained with only its name visible.

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 compares 'top stablecoin DeFi yields vs official US T-bill rate' and provides 'spreads + verdict', distinguishing it from sibling tools like defi_yields or us_treasury_rates which focus on one side.

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 cross-comparison with 'TradFi x DeFi in one call' and mentions cost, but does not explicitly state when to use versus sibling tools or 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 data is live from DefiLlama and mentions a $0.01 cost via x402, which is a behavioral trait. However, it does not explain the payment mechanism, whether the operation has side effects, or any rate limits, leaving significant gaps.

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

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

The description is a single, front-loaded sentence that packs purpose, source, and cost. It is not bloated, though the cryptic '$0.01 via x402' could be clearer. Overall, it is concise and efficiently sized.

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 only 20% parameter description coverage, the description is insufficiently complete. It does not convey the shape of the returned data, how to provide payment via x402, or the meaning of most parameters, making it hard for an agent to invoke correctly without additional assumptions.

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 only 20% (only 'chain' has a description). The description mentions chain and TVL, helping map to 'chain' and 'min_tvl', but leaves 'top', 'stablecoin_only', and especially 'x_payment' unexplained. It does not adequately compensate for the low 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 current top DeFi pools filtered by chain and TVL, sourced live from DefiLlama. While it lacks an explicit verb like 'list' or 'get', the intent is unambiguous and distinct from sibling tools like crypto_prices or dex_token_data.

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

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

No guidance is given for when to use this tool versus alternatives, nor any exclusions or prerequisites. The description only states what data it returns, leaving the agent to infer appropriate usage contexts.

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 critical behavioral traits: the $0.01 via x402 payment requirement, liveness ('live'), and data source ('Live from Dexscreener'). It does not cover rate limits, error behavior, or response format, but the most important operational traits are 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: it opens with the cost, then the data payload, scope, and source. Each sentence earns its place; the 'For crypto trading, sniping, and research agents' line is brief and useful for agent routing.

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

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

For a two-parameter lookup with no output schema, the description covers the input type, expected output fields, scope, source, and cost. The main gap is the lack of clarity around how x_payment is supplied and what the raw response shape is, but overall the tool can be invoked correctly with the given information.

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

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

Schema description coverage is 50%, and the description largely restates q's semantics ('symbol, name, or contract') while adding output-context. It does add some meaning to the payment flow by mentioning '$0.01 via x402', but it still leaves the x_payment parameter's exact value and requirement ambiguous.

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: 'live decentralized-exchange data for any token (symbol, name, or contract)' and enumerates concrete outputs (USD price, 24h volume, liquidity, buy/sell counts, momentum). It clearly differentiates from siblings like chain_token_identity, crypto_prices, or token_launches_feed by emphasizing DEX-specific, cross-chain live data.

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

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

The description gives a clear context for when to use the tool: 'For crypto trading, sniping, and research agents' and 'for any token ... across every chain.' It does not explicitly name alternatives or when-not conditions, so it falls short of a 5, but the use-case framing provides solid selection 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 burden and does disclose key behavioral traits: the $0.09 cost via x402, live data, source (TED database), return fields, recent-first ordering, and total match count. It doesn't mention rate limits or error handling, but the core behavior is well covered.

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

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

The description is two sentences, front-loaded with cost and purpose, and every sentence adds value. No redundancy or filler.

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

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

Despite having no output schema, the description explains return values (title, country, publication date, notice link, match count) and ordering. It doesn't cover pagination or max result limits, but for a straightforward lookup tool with 3 parameters, it is largely complete.

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

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

Schema coverage is 67% (q and months have descriptions). The description adds meaning by clarifying q as 'keyword/sector' and mentions lookback months implicitly through 'recent-first', but doesn't add detail beyond the schema's existing parameter descriptions. This is adequate but not exceptional.

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 ('live public procurement tenders') with a clear resource ('official EU TED database') and scope ('all 27 EU member states'). It distinguishes itself from sibling tools by emphasizing EU-specific public-sector tenders and European opportunity targeting.

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

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

It provides clear context: 'The overseas opportunity layer for sales, BD & research agents targeting European public-sector spend.' This tells when to use it, though it doesn't explicitly name alternative tools 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?

No annotations are provided, so the description bears the full burden of behavioral disclosure. It does explain the payment requirement (x402 USDC on Base or Solana) and the 24-hour publication window, which is useful. However, it doesn't disclose side effects beyond the payment charge, what happens to the published data after 24 hours, or whether the payment is reversible. For a tool that initiates a financial transaction, the behavioral transparency is 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 dense, information-rich paragraph. It packs significant detail (payment mechanism, time window, what's published, what's returned, chain support) into a compact space. It's slightly long but every clause adds meaningful information. No filler or redundancy.

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

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

For a tool with a single parameter and no output schema, the description covers most of what an agent needs: the payment gate, the publish action, the return value categories (roster, counterparties, Agent Planets access, membership receipt). The main gap is the absence of an output schema combined with a non-trivial return structure (roster, counterparties, receipt) that isn't formally defined, leaving the agent to infer the response shape from prose 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?

Schema coverage is 100% and there is only one parameter. The schema describes x_payment adequately as a 'Signed x402 payment payload'. The description adds context about payment being a one-time admission credential on Base or Solana, which enhances understanding of the parameter's purpose. The baseline of 3 is appropriate since schema already covers the single parameter.

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: a wallet-gated check-in that publishes agent metadata and returns roster/counterparty/access information. It uses specific verbs (publishes, returns) with a clear resource (machine room for agents). It distinguishes itself from siblings by noting the payment-gated, x402 USDC admission model, which none of the sibling tools share.

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 the mechanics of the tool (check-in process, 24h window, admission credential) but provides no guidance on WHEN to use this tool versus alternatives. There are no explicit exclusions or alternative tools mentioned, and the context in which an agent would want this functionality vs sibling tools like agent_passport or agentforce_proxy is not clarified.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It reveals key behaviors: the tool is a GET that requires a payment payload, it settles on Base via x402, and it returns an 'ak_live_...' key upon paid request. It also implies mutating behavior (purchase) and payment handling. However, it omits what happens on failed payment or how retries work exactly, but the info provided is substantial.

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

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

The description is extremely concise, packed with essential information in two short paragraphs. Every sentence adds value: the offer, the settlement, the retry mechanism, and the return format. No wasted words.

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

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

For a simple purchase tool with one parameter and no output schema, the description is quite complete: it specifies the price, credits, settlement method, payment mechanism, and response format. It doesn't explain failure modes or payment validation details, but given the simplicity and lack of annotations, it's reasonably thorough.

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

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

The description mentions 'Retry this GET with X-PAYMENT; a paid request returns ak_live_....', which explains the purpose of the x_payment parameter. However, the schema description for x_payment already provides info ('Signed x402 payment payload'), and the description doesn't add much beyond that. Since schema coverage is 100% and there's only one parameter, a baseline of 3 is appropriate.

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

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

The description clearly states the tool's purpose: a one-time purchase of a 1,000-call API key for $19 USDC, settling to store payTo on Base. It uses a specific verb (purchase) and resource (API key), and distinguishes itself from sibling tools like 'store_catalog' and 'market_post_task' by specifying the payment method and settlement details.

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

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

The description explicitly explains when to use this tool: for a one-time purchase of a 1,000-call API key. It also provides clear guidance on the retry mechanism with X-PAYMENT header, and mentions that no Stripe or new wallet is needed, which sets expectations for usage. It effectively guides the agent on the process, distinguishing this from other purchase or payment 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 that the tool uses a 'live public RPC' and is a 'one paid call,' which is useful context. However, it does not mention return format, error conditions, or that it is a pure read operation beyond the word 'read.'

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

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

The description is two sentences with no unnecessary fluff, packing in purpose, networks, use case, and cost. Minor grammatical awkwardness ('The approval read') prevents a 5, but it is still highly concise.

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

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

For a single-parameter read tool with no output schema, the description covers what, where, when, and cost, which is fairly complete. It omits how the payment payload is used and the response structure, but these are partially covered by the schema and context.

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

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

The schema description for x_payment is already clear ('Signed x402 payment payload'), and the parameter description coverage is 100%. The tool description adds no additional parameter semantics, so the baseline of 3 is appropriate.

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

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

The description clearly defines the tool as reading ERC-20 token allowance across multiple networks, specifying the owner and spender roles. It uses a specific verb ('how much... is approved to move') and directly distinguishes itself from sibling chain read tools like balance or call.

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 explicit context: 'The approval read every DeFi, swap and trading agent makes before (and after) a transaction to know if an approve is needed.' This tells the agent when to use it, but it does not explicitly name alternative tools 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 and does disclose that this is a live public RPC reachable with 'one paid call' (x402), which is genuinely useful behavioral context for a paid endpoint. It says nothing about rate limits, failure behavior, or what the response looks like, and the trailing listing advertisement adds no behavioral value.

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 operational content is front-loaded and tight, but the final sentence ('List your own x402 service on bazaar... 1 USD, 30 days...') is unrelated self-promotion that does not help an agent call this tool and dilutes the definition.

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?

No output schema and no annotations, so the description needs to stand alone; it covers the chains served, the underlying RPC method, the payment model, and the semantic meaning of the returned value (chain tip/height). The main gap is that no chain selector appears among the parameters despite the multi-chain claim, leaving the agent unsure how a target chain is chosen.

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 is a single parameter and the schema already documents it at 100% coverage ('Signed x402 payment payload'). The description's only contribution is 'one paid call', which loosely implies the payment payload is consumed per invocation but adds no format or semantics detail. Baseline 3 applies.

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

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

States a specific verb+resource: 'The current chain tip (latest block height) via eth_blockNumber', plus an explicit chain list. That is clearly distinguishable from siblings like chain_block_header, chain_gas_price or chain_id.

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 implies usage through 'The freshness read settlement, indexing and trading agents poll to know where the chain is', which tells an agent this is the freshness/liveness read. But no alternatives are named and no when-not conditions are given, so an agent must infer whether chain_block_header or chain_heartbeat is the better pick.

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 read-only behavior, 'Live public RPC', and 'one paid call,' which is useful context. However, it does not mention error behavior (e.g., reverts) or response formatting beyond 'raw return value,' leaving some gaps.

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

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

Three sentences, each earning its place: the first defines the operation, the second clarifies use case, the third covers RPC and payment. Information is front-loaded, with no filler or redundancy.

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

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

The description covers scope, chains, and payment, but the missing schema parameters and absence of an output schema leave critical gaps. The agent cannot determine how to input the actual call parameters, so the description is not yet complete for a tool of this complexity.

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

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

The description mentions passing a contract address and encoded calldata, but the input schema only defines x_payment. The agent is not told how or where to supply these essential inputs, nor what encoding is expected for calldata. The schema mismatch makes the parameter semantics incomplete and confusing.

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 verb ('Simulate') and names the exact resource ('read-only Ethereum contract call via eth_call'), then lists supported chains. It distinguishes itself from siblings by framing it as the 'universal contract-read primitive' for view functions without a dedicated 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?

Explicitly gives when-to-use guidance: use when a view function is 'not covered by a dedicated endpoint.' It also enumerates supported networks (Base, Ethereum, Optimism, etc.) and notes the paid nature, helping agents decide between this and more specialized 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 full burden of behavioral disclosure. It mentions the underlying method (eth_getCode), the networks supported, and the payment aspect ('Live public RPC; one paid call'). This adds meaningful context about cost and external dependency. It does not describe error handling or rate limits, but for a simple read tool, the disclosed behaviors are sufficient.

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

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

The description is two sentences plus a short question, front-loaded with the purpose. Every sentence adds value with no fluff or redundancy. It is appropriately sized for the tool's simplicity.

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 meant to check an address, but the input schema only contains x_payment, with no parameter for the address. The description does not explain how the target address is specified, making the tool difficult to invoke correctly. Despite the clear purpose and low complexity, this missing critical input is a significant gap that prevents the description from being 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 has 100% description coverage for the single parameter x_payment, which is described as 'Signed x402 payment payload'. The description adds only a vague reference to 'one paid call', which does not provide additional semantic meaning beyond the schema. The baseline score is 3 because the schema already fully documents the parameter.

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 as checking whether an address is a smart contract or EOA by verifying bytecode existence and size via eth_getCode. It distinguishes itself from sibling tools by focusing on bytecode, which is unique among the chain-related tools. The question format immediately conveys the core 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 provides clear context on when to use this tool: 'The safety/identity read wallet, payment and trading agents make before interacting with an address.' This implies the pre-interaction safety check use case. However, it does not explicitly mention alternatives or exclusions (e.g., when NOT to use it), so it falls short of a 5.

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

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

With no annotations, the description states it is a 'live public RPC' and a read operation via balanceOf, which conveys basic behavioral traits. Yet it does not mention potential rate limits, error behavior, or response format. The addition of 'live public RPC' is useful but the disclosure is 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 three sentences and front-loads the core purpose. It efficiently covers scope, use cases, and a comparison, but includes promotional language like 'most-called RPC read after native balance' that adds little functional value.

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

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

While the description explains the chains and token types, it omits essential details: how to specify the target wallet/token (especially given the minimal schema) and what the call returns (no output schema). Without these, the agent cannot reliably invoke or interpret the 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 only includes x_payment ('Signed x402 payment payload') with no explanation of how the wallet address and token contract are specified. The description says 'any wallet' and 'any ERC-20 token' but gives no guidance on how to map those to the only parameter. This is a critical gap because the agent cannot infer the correct input structure.

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

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

The description clearly identifies the tool's function: retrieving any ERC-20 token balance for any wallet via balanceOf across six chains. It distinguishes itself from alternatives like onesource by emphasizing multi-chain coverage, and even names example tokens.

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

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

It provides clear use-case context (wallet-tracking, copy-trading, treasury agents) and notes it is the most-called RPC read after native balance. It also implicitly contrasts with onesource's Ethereum-only coverage, suggesting when this tool is preferred. However, it does not explicitly name sibling tools or exclusion scenarios.

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

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

With no annotations, the description carries the full burden. It discloses that the call is a read operation, uses 'Live public RPC', and requires 'one paid call' (cost). It also explains what the return value represents. It does not discuss failure modes, but for a simple read with payment, this is adequate.

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

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

The description is three sentences, each with a distinct purpose: what the tool returns, how it fits into agent workflows, and operational details (RPC, cost). No wasted words.

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

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

Given the simple one-parameter schema and no output schema, the description covers the core aspects: purpose, networks, use case, and payment requirement. It omits explicit return format and error handling, but those are not critical for this type of read tool given the schema and context.

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

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

Schema description coverage is 100% for the single parameter x_payment, which is already described as 'Signed x402 payment payload'. The description adds no further meaning beyond the schema, so the baseline of 3 applies.

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

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

The description clearly states the tool returns an address's transaction count (nonce) via eth_getTransactionCount, and distinguishes it from siblings by specifying the exact resource and network coverage (Base, Ethereum, etc.). It also clarifies the semantic meaning: 'the next nonce to use and total outgoing 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?

It gives clear context for when to use this tool: 'The read settlement and trading agents make to build and sequence transactions.' This implies specific use cases but does not explicitly exclude alternatives or name sibling tools, so it falls short of a 5.

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

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

With no annotations, the description carries the full burden of disclosing behavior. It does so well: it lists detailed risk flags, the three-level verdict, supported blockchains, cost per call, and authentication method (no API key, USDC over x402). It omits potential latency or failure modes, but the disclosed behavior is substantial and beyond just the tool's action.

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

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

The description is front-loaded with the main purpose, followed by the use case and operational details. It is moderately detailed but not bloated. The second sentence is somewhat promotional ('should make before transacting') but still adds usage guidance. Overall, every sentence contributes value, though it could be trimmed slightly.

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 must at least hint at the return value. It does so by stating the verdict types and listing risk flags. It also provides network coverage, cost, and payment method. It stops short of describing the exact response structure or error handling, but for a single-parameter tool, this is reasonably complete.

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

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

The input schema covers the only parameter, x_payment, with a description of 'Signed x402 payment payload.' The tool description does not add any new meaning about this parameter beyond mentioning 'USDC over x402' which relates to payment but not the parameter's structure or usage. Since schema coverage is 100%, the baseline of 3 applies.

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

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

The description states a clear, specific verb and resource: 'Screen any wallet address for compliance and security risk in one call.' It enumerates the exact risk categories (sanctions/OFAC, money-laundering, phishing, etc.) and the output verdict (CLEAR / CAUTION / HIGH_RISK). This distinguishes it from general wallet or portfolio tools by focusing on compliance and security.

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

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

The description provides clear usage context: 'every payment, settlement, compliance, and trading agent should make before transacting with a counterparty.' This tells the agent when to use it, but it does not explicitly name alternatives or state when not to use it. The context is strong, so it earns a 4.

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 compensates by disclosing sources (Hyperliquid and OKX), composition logic (funding, premium, OI, long/short ratio), output format (regime, pressure score, evidence), and access requirements ('Free public upstreams, no exchange key'). It stops short of mentioning update frequency or failure behavior, but covers the key behavioral aspects for safe invocation.

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

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

The description is compact and front-loaded, opening with the user-relevant question and then specifying outputs and positioning. Every sentence adds value: data sources, composition, output, and use case; no redundant metadata.

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, the description enumerates the main return elements (named regime, pressure score, evidence) and the data sources, making the tool's behavior sufficiently specified. It does not detail the exact structure of the evidence, but that is minor for tool 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 single parameter x_payment already has a schema description ('Signed x402 payment payload'), giving 100% schema coverage. The tool description adds no additional parameter meaning, and the baseline for full schema coverage is 3.

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

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

Description clearly states the tool's function: it assesses which side of the perp market is over-leveraged and composes data into a named regime and pressure score. Phrases like 'not a raw feed' and 'pre-position read' explicitly distinguish it from sibling tools such as crypto_prices or crypto_market_metrics.

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

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

The description identifies a clear intended use case ('The pre-position read for a leveraged agent') and excludes one class of use ('not a raw feed'). However, it does not name specific alternative tools or provide detailed when-not-to-use conditions beyond the raw-feed exclusion.

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 usefully explains the verification mechanism (an unpaid call answering with payment terms means alive) and lists return fields, but it omits permission, rate-limit, authentication, and payment-payload behavior, and its mention of 'host' conflicts with the schema's x_payment parameter.

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

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

The description is front-loaded with the core question and verification logic, then lists returned fields. It is somewhat dense but mostly earns its space; the census statistic adds motivation rather than 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, so the description's return-field summary is useful. However, for a verification tool with no annotations, it should clarify the x_payment parameter and payment/auth behavior rather than naming an inconsistent 'host' parameter.

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 would be 3. However, the description says 'Params: host' while the schema contains only x_payment, a signed payment payload. This actively misleads an agent about how to invoke the tool and adds no correct 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 states a specific action and target: verify whether an x402 seller is live right now by checking its agent web. It is clear enough to distinguish this from general web scraping or payment tools, though it does not explicitly name a sibling 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?

It gives a clear trigger: use before paying any seller, supported by the census statistic that only 8.8% of declared endpoints are live. It does not state when not to use it or name an alternative tool, so it falls short of a 5.

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

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

With no annotations, the description carries the burden of behavioral disclosure. It adds useful context (cost via x402, live source, time windows) but does not mention rate limits, pagination, or output format. For a simple read tool, this is adequate but not rich.

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

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

Two sentences, front-loaded with the core purpose, cost, and data source. Every word earns its place; no fluff or redundancy.

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

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

Given no output schema and no annotations, the description covers the main purpose and parameters but omits details about the response format and the x_payment parameter. It's a compact, all-in-one description but leaves the agent guessing about return structure and payment mechanics.

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

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

Schema coverage is 50%, with 'top' and 'since' described in the schema. The description adds meaning for 'language' ('optional language filter') but leaves 'x_payment' entirely unexplained. It partially compensates for the coverage gap but does not fully clarify the payment parameter.

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 top trending GitHub repositories by stars over day/week/month with optional language filtering. It uses a specific verb ('top trending') and resource ('GitHub repositories'), and clearly distinguishes from sibling tools like hn_top_stories or web_search by focusing on GitHub trending data.

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

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

The description provides clear context: time periods (day/week/month), optional language filter, and that it's live from GitHub Search API. While it doesn't explicitly name alternatives or exclusions, the context is sufficient for an agent to understand when to use this tool versus a general web search.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It does add useful information about the cost ($0.09 via x402) and the live nature of the data, but it omits details such as response structure, pagination, error handling, or authentication requirements beyond payment.

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 sentence that packs key information: pricing, payment method, content delivered, and data freshness. Every word contributes to the core purpose, with no redundancy or fluff.

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

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

The tool is simple (2 params, no output schema), and the description largely explains the core function and output fields. However, it doesn't describe the response format, how many stories are returned (the 'top' parameter), or what x_payment entails, leaving gaps for an agent to invoke 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 covers only 'top' (1-20) and leaves 'x_payment' undocumented. The description mentions 'via x402' but never explicitly connects this to the x_payment parameter, nor does it explain how to provide it. With 50% schema coverage, the description should compensate but fails to clarify the payment parameter semantics.

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

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

The description clearly indicates the resource (Hacker News top stories) and output contents (score, author, comment count, links), making the tool's function easy to identify. However, it lacks an explicit verb like 'get' or 'list', so it doesn't fully meet the 'specific verb+resource' criterion; it is still distinguishable from all sibling tools.

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

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

Usage context is only implied by the resource name and description; there is no explicit guidance on when to use this tool versus alternatives. Since there are no closely related sibling tools, the lack of explicit alternatives isn't a major issue, but the description still doesn't state scenarios or exclusions.

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

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

Annotations only declare readOnlyHint and openWorldHint, which means the description must carry the rest of the behavioral load, and it does: it discloses the pay-per-call model (0.003 USDC via x402 on Base), the exact first-call/second-call payment protocol, and that all three values come from a consistent, stated block. That is meaningful behavioral detail the annotations do not cover.

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

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

The description is front-loaded with the core capability, followed by differentiation, exclusions, input shape, and the payment flow. The raw HTTP URL and repeated 0.003 USDC figure add a little redundancy, but the overall structure remains dense and usable.

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?

Because there is no output schema, the description must state the return values, and it names all three: balance, block number, and gas price, anchored to a block. It does not specify the units or the encoding of the returned gas price or block number, which is a minor gap for a paid call whose output must be parsed.

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 still adds value by showing the shape of the q payload ({"address":"0x..."}) and, more importantly, by explaining the lifecycle of x_payment: the first call without it returns payment terms, and the second call with the signed payment returns the result. This goes slightly beyond the schema text.

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 verb and resource: it returns the live USDC (ERC-20) balance of any Base address, plus the latest block number and gas price, all read at a single stated block. It also scopes itself explicitly against similar reads by saying it is 'cheaper than chaining an ETH-balance read and a gas read' and that it returns no tx receipts, which is enough to separate it from the many chain_* siblings.

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

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

The description gives a clear context for use (a single combined read instead of two calls) and an explicit exclusion ('No tx receipts'), plus the exact two-step procedure for the x402 payment handshake. It does not name specific sibling tools that an agent should choose instead for balance-only or gas-only needs, so the guidance is strong but not fully explicit about 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?

Annotations only declare readOnlyHint and openWorldHint; the description adds the material facts an agent cannot infer: a 0.001 USDC per-call charge via x402 on Base, the mandatory two-call payment handshake, live external data sources, and a 'rule-based, not financial advice' caveat. Pricing and auth prerequisites are exactly the behavioral context annotations cannot carry.

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

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

Front-loads cost and scope, then capabilities, then the call protocol — a sensible order with no filler sentences. It repeats the 0.001 USDC figure twice and includes the raw HTTP endpoint, which is marginally useful for an MCP caller but slightly redundant.

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?

No output schema exists, and the description compensates by enumerating the return payload (RSI14, SMA7, SMA20, 7-day change, score, reasons, exact source). Combined with the payment flow and input example, an agent has everything needed to invoke and interpret this tool.

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

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

Schema coverage is 100%, so baseline is 3, but the description goes further by showing the literal input shape {"coin":"BTC"} and explaining that x_payment must be the signed payload derived from the terms returned on the first call. That causal relationship between the two parameters is meaning the schema alone does not convey.

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+resource (a long/short/neutral signal) with the exact asset universe (BTC, ETH, SOL, XRP, DOGE, ADA, LTC, AVAX, LINK, DOT and other USD pairs) and the data provenance (Kraken daily closes, Coinbase backup). This clearly distinguishes it from sibling price/market tools such as crypto_prices or crypto_market_metrics, which report data rather than a scored rule-based verdict.

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 two-step x402 flow is spelled out precisely: call once without x_payment to obtain payment terms, then call again with the signed payment to get the result. What is missing is explicit routing guidance against siblings (e.g. why use this over crypto_market_metrics for raw indicators), but the invocation context is unambiguous.

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

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

Annotations declare readOnly=true and openWorld=true; the description adds important context beyond that: it is a paid endpoint (0.009 USDC on Base), requires a two-call payment handshake, and is a pure computation. The only weak spot is the marketing line about pricing rather than functional detail.

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?

Purpose and invocation flow are front-loaded and functional, but 'Priced under the 0.01 market leader' is pure marketing waste and the input example is duplicated between description and schema. Tighter without those two elements.

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?

No output schema exists, yet the description names the return fields (payoff months, total interest, ordering), so return expectations are covered. Payment and input semantics are fully explained; only the exact result shape (e.g. per-debt schedule) is left implicit.

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% and the description reinforces it by rendering the exact q payload (debts array with name/balance/apr/min plus budget). It also explains x_payment beyond the schema by tying it to the first call's returned terms, which meaningfully clarifies a non-obvious parameter.

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 (computes payoff) plus concrete outputs: payoff months, total interest, and avalanche vs snowball ordering for a list of debts. That is precise enough that an agent knows exactly what it gets back, and no sibling tool overlaps this debt-specific computation.

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?

Gives clear procedural guidance on the two-step x402 flow (call without x_payment to get terms, then again with the signed payment) and includes a concrete input example. It doesn't discuss when to prefer this over alternatives, but there are no real sibling alternatives for debt payoff math.

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?

Annotations only say readOnly=true and openWorld=true; the description adds the material behavior the annotations cannot convey: a 0.005 USDC x402 charge on Base, a required two-call payment handshake, and a real limitation that DKIM is only probed at 10 common selectors so custom selectors may be missed. It also discloses output shape (score, issues, next record) and that sp/ruf/fo are preserved in the suggested record.

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

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

Front-loaded with vendor, price, and the core capability, then input, then transport, then payment flow. Dense but nearly every clause carries load; the bracketed pricing prefix and raw endpoint URL add some clutter at the front, though both are operationally relevant.

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 the description compensates by naming what comes back (0-100 score, issues, exact next DMARC record). Combined with the payment protocol and the known DKIM limitation, an agent has everything needed to invoke it correctly and interpret the result.

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 goes further by showing the literal q payload shape ({"domain":"example.com"}) and by explaining the ordering semantics of x_payment, which the schema alone does not (it only says it is 'the terms returned on the first call'). The HTTP GET URL with the q parameter reinforces how q is passed.

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 chain: a live DNS check covering DMARC policy, SPF recursion depth, DKIM selector probing, and MX, returning a 0-100 score plus a suggested next record. The scope (audit + remediation record generation) is unambiguous and cannot be confused with any sibling tool in the 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?

Explicitly names the target caller ('For agents that send mail as a domain') and outlines the two-step payment protocol: call once without x_payment for terms, call again with x_payment for the result. No competing DMARC/SPF sibling exists to route against, and no explicit when-not-to-use case is given, which keeps it just below 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?

Annotations already declare readOnlyHint and openWorldHint, so the safety profile is covered; the description adds genuinely non-obvious behavior — a per-call price (0.02 USDC on Base), an x402 payment handshake requiring two invocations, and live DNS resolution at call time. It stops short of describing failure modes (e.g., unresolvable domain, insufficient payment) or whether results are cached.

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?

Information-dense but crammed into a semicolon-joined run-on; the vendor/price prefix, the HTTP GET URL, and the payment handshake compete with the actual capability statement. The raw endpoint URL and duplicated input example are largely redundant for an agent that invokes through MCP, and the payload is not front-loaded on what the tool returns.

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

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

For a read-only DNS analysis with no output schema, the description does a solid job telling the agent what comes back: current MX/SPF/DMARC state, DKIM selector classifications, and exact per-stage DNS records plus Zoho/Google/Microsoft console steps. The remaining ambiguity is the shape of the response (single object vs. staged list) and how multi-domain or subdomain cases are handled.

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 both `q` and `x_payment` are already documented in the schema, including the base64 x402 payload and the 0.02 USDC terms returned on the first call. The description restates the same JSON input example and payment purpose without adding format rules, validation constraints, or defaults, so it sits at the baseline.

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

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

The description names a specific deliverable — a staged DMARC remediation plan that ends at p=reject — and enumerates the inputs it inspects (MX, SPF, DMARC, per-selector DKIM status, null-MX parked domains). That is far more specific than the title alone. The one gap is that a sibling `kyreos_dmarc_audit_tool` exists and the description never says how this plan differs from that audit, so the agent must infer the boundary.

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 real procedural guidance for the two-step paid call: first call without x_payment to obtain the x402 terms, second call with the signed payment to get the result. However, there is no guidance on when to choose this over the sibling audit tool, no prerequisites (e.g., that the domain must already exist / be resolvable), and no statement of what happens if payment terms expire.

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?

Annotations only say readOnly and open-world; the description contributes the cost (0.001 USDC per call on Base), the two-step payment handshake required before data is returned, and the response shape (records, resolver agreement, DNSSEC validation). Those are material behaviors an agent cannot derive from the annotations.

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

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

Front-loaded with the capability and record types, then the response, then the payment mechanics; nearly every clause carries information. The pricing appears twice (bracketed header and again in the call flow), which is mild redundancy.

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

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

No output schema exists, so the description compensates by naming what comes back (records, agreement between resolvers, DNSSEC status) alongside the cost and the payment protocol. Enough is present to invoke it correctly on the first attempt.

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 the schema already documents both q and x_payment. The description's example input {"name":"example.com","type":"MX"} illustrates the JSON-string encoding of q, which is mildly useful, but it does not add constraints or formats beyond what the schema states.

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 ('DNS lookup for agents') and enumerates the covered record types (A, AAAA, MX, TXT, NS, CNAME, SOA, CAA, SRV, PTR) plus the dual-resolver scope. That scope cleanly separates it from siblings like kyreos_dmarc_audit_tool or kyreos_mcp_liveness_probe.

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?

Gives explicit procedural guidance: call once without x_payment to obtain the x402 terms, then call again with the signed payment to get the result. It does not name alternative tools or state when a different DNS/audit tool should be preferred, so it falls short of full when-not/alternatives coverage.

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?

Beyond readOnlyHint/openWorldHint, the description discloses the paid x402 handshake, the exact price (0.003 USDC on Base), that data is read live from a specific on-chain registry, and the categorical verdict scale. The read-only GET is consistent with readOnlyHint, so there is no contradiction.

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

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

Front-loaded with provider, price and scope, then the return list, then the input example and the payment sequence. Every element is relevant, though the raw HTTP endpoint adds little for an agent already invoking the tool and the sentence is dense enough to read as one long 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?

With no output schema, the description carries the return contract itself: found/UNREGISTERED, owner wallet, owner_is_contract, owner_tx_count, USDC balance, agentURI, registration metadata, risk flags and verdict. It also fully documents the two-step payment flow an agent must perform to get a result.

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

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

Schema coverage is 100%, so both fields are already documented, but the description adds real meaning: q is a JSON-encoded agentId payload and x_payment is only to be supplied on the second call with the terms from the first. That sequencing context is not derivable from the schema alone.

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 concrete verb and resource: give an ERC-8004 agentId on Base and get a trust verdict. It names the source of truth (the official Identity Registry at 0x8004A169...a432) and the exact return vocabulary (found/UNREGISTERED, risk flags, LOW/MEDIUM/HIGH), which separates it from neighboring tools like get_crypto_address_risk or token_security_check.

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?

Gives explicit procedural guidance: call once without x_payment to receive the x402 terms, then call again with the signed payment to get the result. It also shows the exact input shape {"agentId": 1}. It does not say when to prefer this over sibling trust/risk tools, so it stops short of full when-versus-alternative routing.

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