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?

No annotations are provided, so the description carries the full burden. It transparently explains the mechanism (ask a model, get ranked shortlist by mention share), states the cost ($0.02 via x402), and notes it's live. It doesn't disclose potential side effects or permission requirements, but for a read-only query tool, 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 two sentences, front-loaded with the cost and core function, then differentiating context and use cases. Every clause adds value with no filler or repetition.

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

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

For a simple 3-parameter tool with no output schema, the description adequately conveys purpose, mechanism, output format (ranked shortlist by mention share), cost, and ideal user. It could mention what happens without a valid category or how the x402 payment is processed, but these are minor 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% with descriptions for 'category' and 'market', and the description reinforces the 'category' parameter by saying 'ANY category'. The 'x_payment' parameter lacks schema description and is not explained in the tool description, so the agent has no added meaning for it beyond the name.

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: it asks a current AI model for recommendations in any category and returns a ranked shortlist of brands by mention share. It also distinguishes itself from sibling tools like brand_ai_visibility_check by explicitly calling itself 'the inverse of a brand 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?

The description provides explicit usage context: 'For competitive-intel, market-research, GEO and sales agents.' It also names the key alternative ('a brand check') and explains this tool is the inverse, making it clear when to use this tool versus a single-brand check.

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 and payment method ('$0.04 via x402') and that the data is proprietary, which is valuable. However, it does not explicitly state whether the operation is read-only, describe side effects, rate limits, or the output format, leaving gaps for an agent relying on safety cues.

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, but the clause 'with competitors AI names instead' is grammatically awkward and unclear, undermining effective conciseness. It tries to convey output details but fails to do so clearly, so while short, it is not well-structured.

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

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

For a simple tool with no output schema, the description covers the purpose and payment but omits details about the return structure and the meaning of 'competitors AI names instead'. The category filter is only in the schema and not integrated into the description, making the tool less self-contained.

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 100% description coverage for both parameters. The description's mention of 'x402' aligns with the x_payment parameter, adding payment context, but it does not clarify the category parameter or add meaning beyond the schema. 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 states it provides 'proprietary AI-visibility scores for 25 major brands across 5 industries', which identifies the general resource and action. However, the phrase 'with competitors AI names instead' is ambiguous, and there is no explicit differentiation from sibling tools like brand_ai_visibility_check or ai_category_ranking.

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 obtaining AI-visibility scores in a specific brand set and mentions the x402 payment requirement, but it does not explicitly state when to use this tool versus alternatives. No exclusions or alternative tool names are provided, even though several sibling tools overlap in functionality.

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

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

With no annotations, the description does disclose the cost ($0.005) and payment mechanism (via x402), which is helpful behavioral context. However, it does not describe the output format, whether the feed is streaming or one-time, or any side effects, leaving room for uncertainty.

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 with no extraneous words. It front-loads the cost and immediately conveys the live feed purpose, making every word earn its place.

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

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

For a simple one-parameter tool with no output schema, the description covers cost and data source but omits response format and feed behavior (e.g., is it a one-time query or continuous stream?). These gaps prevent it from being fully complete, though the essential purpose is clear.

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% for the single x_payment parameter, but the description adds beyond it by specifying the exact cost and that x402 is used for payment. This provides concrete semantics not present in the schema, so the description enhances parameter understanding.

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

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

The description clearly states the tool provides a "live feed" of which brands/categories are being checked for AI-search visibility "right now," using a specific resource and real-time scope. This distinguishes it from siblings like ai_visibility_index or brand_ai_visibility_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?

The description implies usage for current/real-time visibility checks via the "live feed" and "right now" phrasing, but it does not explicitly mention when not to use it or how it compares to alternatives. No exclusions or alternative tool names are given, leaving guidance mostly implied.

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

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

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. It discloses the price ($0.09 via x402), parallel execution, max of ten reads, and per-read failure reporting with a partial flag, explicitly stating 'a batch never claims success it did not have.' This is rich behavioral context beyond the schema.

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

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

Three concise sentences, each adding value: cost/cap/parallelism, cost/latency comparison, and failure semantics. No filler or redundancy. The most important details are front-loaded.

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

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

Given moderate complexity and no output schema, the description covers the essential context: what operations are supported, how failures are handled, and the payment requirement. It does not explicitly describe the return format, but for standard on-chain reads this is largely self-explanatory. The absence of auth details is mitigated by the payment mention.

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

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

The input schema already covers 'chain' and 'reads' with formats, and the description reinforces those formats by enumerating the read types. The 'x_payment' parameter is not in the schema description, but the description mentions the $0.09 payment mechanism, which indirectly explains its purpose. This adds some 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 clearly states the tool performs batching of on-chain reads: 'up to TEN on-chain reads for ONE payment, run in parallel' and enumerates specific read types (balance, nonce, code, ERC-20, block number, gas price). This distinguishes it from sibling single-read tools like chain_native_balance or get_chain_nonce.

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 a clear use case: batch multiple reads to save cost and latency, stating 'normally costs one payment per read; this is the same data for a fraction of the calls and the latency.' It does not explicitly name alternatives or state when NOT to use it, but the comparison implies batch use is preferred for multiple reads.

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 price ($0.09 via x402), the output granularity (full header fields), and accepted input forms. It does not mention failure modes or rate limits, but for a read-only chain data endpoint, the disclosed details are solid.

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

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

The description is dense with useful information—price, payload fields, differentiation, accepted inputs, chains—without unnecessary words. The structure front-loads the value proposition and the contrast with the sibling tool is concise.

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

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

Given the lack of an output schema, the description compensates by enumerating the output fields. It also specifies supported chains and input formats. The only gap is not explaining the x_payment parameter, but the price mention partially covers its purpose.

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 chain and number, but the description adds meaningful semantics by explaining the conceptual relationship to block number and reinforcing accepted values. It does not address x_payment, which slightly lowers the score from a 5.

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 'the full header of any block' and lists the specific fields returned. It also distinguishes itself from the sibling chain_block_number tool by contrasting 'WHERE the chain is' with 'WHEN that block happened and how contested it was'.

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 contrasts this tool with get_chain_block_number, giving a clear when-to-use alternative. It also specifies accepted inputs (height or latest/finalized/safe) and supported chains, leaving no ambiguity about usage context.

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

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

With no annotations provided, the description takes on full disclosure duty. It reveals cost ($0.09 via x402), return fields, chain-specific finality thresholds, and the critical distinction between 'no receipt yet' and 'failed'. It warns about double-spending risks, adding valuable behavioral context beyond simple 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 concise yet information-dense: it opens with the core purpose, lists the return fields, provides specific threshold examples, and closes with a critical safety warning. No wasted sentences; structure is logical and easy to scan.

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

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

Despite lacking output schema and annotations, the description provides a comprehensive picture: what it does, what it returns, how to interpret results, and why it matters (preventing double-spends). It covers edge cases and gives sufficient context for an agent to decide when and how to use 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 coverage is 67%, and the description adds contextual value by explaining the x402 payment cost (relevant to x_payment), listing chain-specific finality thresholds (relevant to chain), and implying the output meaning of hash. It does not exhaustively detail each parameter but compensates with semantic insight.

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

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

The description clearly states the tool's function: checking transaction confirmations, depth, and finality safety. It uses a specific verb ('land', 'buried') and resource ('transaction on this chain'), and distinguishes from generic status tools by focusing on finality thresholds and double-spend risk.

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 (to determine if a payment is final/settled) and gives interpretative guidance (e.g., two confirmations are not settled). However, it does not explicitly name alternative tools or state when not to use it, so it misses the 'exclusions/alternatives' level 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 live registry nature, bidirectional resolution, avatar return when set, and the payment model. However, it does not describe behavior for ENS-not-found cases or the exact return format, and there is no output schema to fill that 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 three sentences, front-loaded with price and functionality, then use case and positioning. It is dense but effective; every sentence contributes value, though the punctuation-heavy first sentence is slightly dense.

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

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

For a simple tool, it covers core functionality, use cases, live data, and cost. But because there is no output schema and no description of the x_payment parameter or error behavior, it is not fully complete.

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

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

Schema descriptions cover 67% of parameters (name and address); the description reinforces these with examples. However, the x_payment parameter is not explained in the description, only alluded to via '$0.005 via x402', leaving a gap for that 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 explicitly states the tool resolves ENS in either direction on Ethereum with concrete examples (vitalik.eth -> 0x address, 0x address -> primary ENS name). This is a specific verb+resource and clearly distinguishes it from 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?

It provides clear usage context for identity verification in wallet/payment/UX agents and displaying human-readable names. It also frames the tool as 'one paid call instead of running your own resolver', giving an explicit alternative, though it does not name a specific sibling 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?

No annotations are provided, so the description carries the full burden. It discloses the cost ('$0.09 via x402') and labels the operation as a 'pre-send read', implying no side effects. It lacks details on output format, error behavior, or rate limits. The mention of 'read' and cost adds some transparency, but it's not comprehensive.

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

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

The description is concise and packs essential info into two sentences, but the structure is slightly awkward: leading with the cost ('$0.09 via x402:') before the purpose, and the 'Pass to' phrase is cryptic. Still, every piece contributes and it's appropriately short.

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

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

For a tool with no output schema and no annotations, the description covers purpose, use case, cost, and basic invocation. It does not describe what the return value looks like (e.g., gas units in wei) or any edge cases. Given the tool's moderate complexity, this is adequate but leaves 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%, with descriptions for to, data, chain, and value but not from or x_payment. The description adds 'Pass to (+ optional from/value/data)', clarifying to as required and listing the main optional parameters, but it omits chain and x_payment. It does not provide extra meaning for the undocumented parameters, though the cost note hints at x_payment's role.

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 estimates gas usage for a transaction via eth_estimateGas across 6 chains. It uses a specific verb ('estimate'), resource ('gas a transaction will use'), and distinguishes from sibling tools like chain_gas_price or chain_transaction_status by focusing on pre-send estimation. The method name and chain scope are explicit.

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

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

The description gives clear context: it is the 'pre-send read tx-building, trading and settlement agents make to size gas and avoid out-of-gas reverts.' This implies when to use it (before sending a transaction) and that it is a read operation. However, it does not explicitly name alternatives or say when not to use it, though the context effectively differentiates it from sibling 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 provided, the description carries the full transparency burden. It discloses non-obvious behavior: default 25-block window, automatic narrowing when a node refuses on result size, and that all caps/narrowings are named in the response. It also mentions the cost ($0.09 via x402) and supported chains. This goes beyond a basic read operation description, though it does not explicitly state read-only semantics or return shape.

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

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

The description delivers a lot of information in two sentences without padding. However, it front-loads the cost before the main purpose, and the dense structure mixes cost, function, behavior, and chains into one run-on sentence. It is concise but could be better organized for quick scanning.

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 9 unannotated parameters, no output schema, and no annotations, the description covers the core purpose, defaults, narrowing behavior, response naming, cost, and chains. However, it does not explain the return value structure, x_payment, or provide explicit guidance on parameter combinations (e.g., required address/topic0 is only in the schema, not the description). It is useful but leaves gaps for a complex 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 only 33%, so the description must compensate. It adds meaning for the key parameters: 'by contract address and/or indexed topics over a block range' maps to address, topic0-3, and block range. It also explains the default block window. However, it does not clarify x_payment or the exact format/meaning of topic1-3, fromBlock, and toBlock beyond inference.

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 'raw event logs by contract address and/or indexed topics over a block range (eth_getLogs)' and identifies it as 'the indexing primitive.' This is a specific verb+resource that distinguishes it from sibling chain tools by naming the underlying method and its role.

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

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

The description implies usage as a low-level event log retrieval tool with a default block window and auto-narrowing, but it does not explicitly state when to use it versus other chain query tools or provide exclusion criteria. The phrase 'the indexing primitive' hints at its foundational nature but lacks direct alternative 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 full responsibility. It discloses the cost ($0.09 via x402), the output contents (base-fee trend, percentiles, utilization, recommended fees with reasoning), and supported chains. It does not mention error cases or side effects, but as a read-only data tool, none are expected. This is 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 three sentences, information-dense with no filler. It front-loads cost and main purpose, then details deliverables, and ends with a clear differentiator. Every sentence earns its place.

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

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

No output schema exists, but the description clearly enumerates the outputs: base-fee trend, percentiles, mean utilization, and recommended maxFeePerGas/maxPriorityFeePerGas with reasoning. It also lists supported chains. This is sufficient for an agent to understand what the tool returns and its scope, though it lacks error/edge-case details.

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

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

Schema coverage is 67%: chain and blocks are described. The description reinforces these by mentioning 'N blocks' and listing chain values, but adds little beyond the schema for these. The x_payment parameter is undocumented in schema; the description provides context by stating the price and x402, giving a partial hint. However, it does not fully explain how to use the parameter, so it does not fully compensate for the coverage gap.

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

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

The description clearly states the tool's function: providing EIP-1559 fee history with base-fee trend, priority-fee percentiles, utilization, and recommended fee parameters. It distinguishes itself from a simple gas-price tool by explicitly contrasting with a single gas number: 'A single gas number cannot tell you whether fees are rising; this can.' This precise resource and purpose differentiation earns full marks.

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

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

The description implies when to use it: when fee trends are needed rather than a one-off gas price. It also lists supported chains, which helps with selection. However, it does not explicitly name alternative tools or provide exclusion criteria, so it is clear context but not explicit 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 full burden. It discloses the data source (Blockscout), the cost ($0.02 via x402), and the output shape (slow/average/fast in gwei). Minor ambiguity remains with 'for any chain' vs. the explicit list of six chains, and it doesn't mention rate limits or error behavior, but it provides meaningful context beyond the schema.

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

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

The description is a single, information-dense sentence with good front-loading of the core function and cost. It's slightly run-on but every clause earns its place, making it efficient without being bloated.

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 gas-price lookup, the description covers the return values, supported chains, data source, cost, and use case. It is somewhat incomplete because it doesn't specify how x_payment should be provided or handle the 'any chain' overstatement, but given the lack of output schema and the simple nature, it's 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 description adds meaning to the 'chain' parameter by listing supported networks and framing it as 'any chain' (though the list contradicts that). However, it doesn't explain the 'x_payment' parameter at all beyond the cost hint, and schema coverage is only 50% because x_payment has no description. This leaves a gap for an important 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 'live network gas prices (slow/average/fast, in gwei) for any chain' and identifies the tool as 'the pre-transaction read' for sizing fees. This specifies the resource and verb (get gas prices) and differentiates it from sibling chain tools like chain_fee_history or chain_estimate_gas.

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

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

It explicitly explains when to use: 'the pre-transaction read every trading, sniping and settlement agent makes before sending a tx to size the fee.' It also positions itself as an alternative to running your own RPC. However, it doesn't mention exclusions or when other chain tools might be better suited, so it stops short of full guidance.

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

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

No annotations are provided, so the description carries the full burden. It discloses the $0.09 x402 pricing, single round trip, supported chains, and verdict output. However, it does not clarify whether x_payment is required, what happens without it, or any error/edge-case behavior.

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

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

The description is two sentences, dense with actionable information: cost, functional replacement, performance advantage, supported chains, and output type. There is no wasted words; 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?

With no output schema, the description should clarify the return payload. It names the verdict and implies it includes chain-id, block-tip, gas, fee-history, etc., but doesn't specify output format, which chains are defaulted, or payment requirements. It's adequate for a simple understanding but leaves gaps for an agent to 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?

The schema describes the chain parameter with enum-like values and default, but x_payment has no description. With 50% schema coverage, the description does not compensate; it mentions 'via x402' in passing but never maps that to the x_payment parameter or explains its format or necessity.

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 identity-checked HEALTHY/CONGESTED/STALE verdict across supported chains. It uses the specific verb 'Returns' and explicitly lists the individual chain calls it replaces, distinguishing it from 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 positions this as a 'pre-action heartbeat' and highlights the cost/round-trip benefits over calling chain-id, gas, fee-history, etc. separately. This effectively implies when to use it, though it doesn't explicitly state when not to use it or name alternative tools for narrow use cases.

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

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

With no annotations, the description carries the burden. It discloses the cost ($0.03 via x402) and the scope (6 chains), and implies a read-only lookup. But it does not explain the return format, possible errors, or whether any side effects exist, leaving some behavioral transparency 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 but contains redundancy: 'OneSource's Ethereum-only (Ethereum-only)' repeats 'Ethereum-only' and the semicolon structure is awkward. It is relatively short but not polished.

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

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

For a simple lookup tool, the description covers the core purpose and cost, but with no output schema it does not specify the exact return shape (e.g., decimal vs hex) nor explain the x_payment parameter. The mention of 6 chains is useful, yet the absence of payment parameter details leaves a notable gap.

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

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

Schema coverage is only 50% (chain described, x_payment not). The description adds no parameter-level details; it only mentions the cost mechanism (x402) without explaining the x_payment parameter. The chain parameter is well-documented in the schema, but the description does not compensate for the undocumented x_payment.

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 returns the EIP-155 chain ID (eth_chainId) for any of 6 chains, and explicitly distinguishes itself from an Ethereum-only alternative. The verb 'confirm' plus the specific resource ('chain ID') makes the purpose unambiguous.

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

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

It gives a concrete use case: 'confirm which chain an RPC is on before signing.' It also compares itself to 'OneSource's Ethereum-only' option, implying when multi-chain support is needed. However, it does not mention when to avoid this tool or reference sibling chain_* tools directly.

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 that it uses the chain's GasPriceOracle.getL1Fee rather than a reimplemented formula and remains correct across forks. However, it does not state read-only/idempotent behavior, auth needs, or output units, leaving notable gaps.

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

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

Two dense sentences front-load the core fee concept and chain scope. Every clause adds context, with no filler.

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

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

The description covers purpose, usage, key parameters, behavioral source, and limitations. It does not specify the output format/units or behavior when both data and bytes are supplied, but for a low-complexity tool with no output schema it is largely complete.

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

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

Schema coverage is 75%, with data/bytes/chain already well described. The description reinforces exact data pricing and chain scope but adds little over the schema. The x_payment parameter is left undescribed in both the schema and the description.

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 specific resource: the L1 data-availability fee for an OP-stack transaction, contrasting it with ordinary gas estimators. This clearly distinguishes it from sibling tools like chain_gas_price and chain_estimate_gas.

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 says to use this when you need the L1 DA fee component that ordinary gas estimators omit, and instructs passing data=0x for exact pricing. It also states Base and Optimism are the only supported chains. It does not name sibling alternatives explicitly, but the context is sufficient.

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

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

No annotations are provided, so the description carries the burden. It discloses the $0.09 cost via x402, live data from Blockscout, and the read-only nature, but omits details like rate limits or error handling. Still, it provides valuable behavioral context beyond the schema.

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

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

The description is three sentences, each with distinct value: cost, function, use case, and chain comparison. The phrasing 'high-frequency balance check wallet-tracking...' is slightly dense but economical and front-loaded with the cost and purpose.

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

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

Given no output schema, the description covers what, where, cost, and use case. It leaves out return structure specifics and edge cases, but it is sufficient for selecting the tool and making a basic invocation call with the required address and optional chain.

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 adds meaning by explaining x402 payment context for x_payment and clarifying the native coin mapping (ETH/POL/xDAI), which complements the schema's chain list. It helps the agent understand the optional x_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 uses 'core on-chain RPC read' and lists native coin balance, USD value, and transaction count across 6 chains, making the tool's function explicit and distinct from siblings like get_chain_erc20_balance. It names the resource (native coin balance) and the verb (read) clearly.

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 identifies high-frequency polling use cases (wallet-tracking, settlement, trading agents) and contrasts with onesource's Ethereum-only scope, implying when to use this multi-chain tool. However, it doesn't explicitly state when not to use it or name an alternative directly.

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 behavioral burden. It discloses that the tool reads from the contract (read-only), returns classified tokenURI types (ipfs/on-chain/http), and includes pricing ($0.09 via x402). It does not detail error handling or response format, but the core behavior is well communicated.

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 yet information-dense, front-loading the core purpose and cost, then explaining the on-chain advantage and supported chains. Every clause serves a purpose, and it is easy to scan.

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

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

For a read-only NFT lookup with no output schema, the description covers the key aspects: what data is returned, the source (contract), the freshness benefit, and supported chains. It stops short of describing the exact response shape or error cases, but overall it is complete enough 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 75%, with chain, contract, and token_id already described. The description adds some value by listing supported chains and emphasizing token ID flexibility (decimal/hex), but x_payment remains undefined and no further parameter detail is provided. The baseline of 3 is appropriate given high schema coverage.

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

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

The description clearly states what the tool does: determines NFT ownership and metadata (ownerOf, tokenURI, collection name/symbol) in one call. It specifies the resource (NFT on a given contract) and distinguishes itself from sibling chain tools by focusing on NFT-specific data.

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

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

The description implies when to use this tool: when you need current on-chain data, 'correct for tokens minted seconds ago and collections no marketplace has indexed.' It does not explicitly name alternatives or exclusions, but the freshness angle provides clear context for selection.

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

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

No annotations are provided, so the description carries the full burden. It discloses read-only behavior, cost ($0.09 via x402), and multi-chain support. However, it does not mention error handling, response format, or potential edge cases, leaving room for improvement.

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 with no fluff. It conveys purpose, cost, chains, use cases, and required parameters efficiently, earning every word's place.

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

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

For a simple read tool, the description covers essentials: what it does, cost, chains, and use cases. Without an output schema, it could mention the return format, but the description is sufficient for an agent to select and 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?

Schema description coverage is 75% (address, slot, chain described; x_payment not). The description adds 'Pass address + slot' and cost context for x_payment, but does not enrich the core parameter semantics 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 reads a raw contract storage slot via eth_getStorageAt, with specific use cases (audit, proxy resolution, advanced trading). This distinguishes it from sibling chain_* tools like chain_native_balance or chain_batch_reads by naming the exact resource and method.

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 by naming target use cases ('for audit, proxy-resolution and advanced trading agents'), implying when to use it. However, it does not explicitly state when not to use it or name alternatives, so it lacks full 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 burden of behavioral disclosure. It reveals that reads come straight from the contract, that legacy bytes32 name/symbol are decoded, that a missing decimals() is flagged rather than silently assumed, and that an existence check is included. It also discloses the $0.09 via x402 pricing, which is useful behavioral context.

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

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

The description is four concise sentences, each earning its place. The first sentence states the core function, the second explains the key advantage, the third covers edge-case handling, and the fourth gives positioning advice. There is no fluff or repetition, and it is well 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 there is no output schema, the description clearly enumerates the returned fields (name, symbol, decimals, total supply, existence check). It also covers edge cases, the freshness advantage, and even pricing. This is complete for a tool of this complexity, leaving no critical information 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?

The schema already well describes the two main parameters (chain with allowed values/default, token as ERC-20 contract address), and coverage is 67%. The description only indirectly references the token and payment via x402, without adding detailed semantics for the x_payment parameter. Thus, the description adds marginal value beyond what the schema provides, warranting the baseline score.

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

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

The description clearly states the tool reads ERC-20 name, symbol, decimals, and total supply directly from the contract, plus an existence check. It also distinguishes itself from indexer-backed lookups and positions it as the 'first read to make on an unknown contract,' which differentiates it from siblings like chain_token_supply.

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

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

The description provides explicit context for when to use this tool: for tokens minted minutes ago or on chains without explorer coverage, where indexer-backed lookups fail. It also recommends it as the first read on an unknown contract. However, it doesn't 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?

With no annotations, the description carries the full burden. It discloses that the call is live from Blockscout, costs $0.01 via x402, and is a one-call alternative to self-hosted RPC. The 'supply read' phrasing implies read-only behavior, though it does not explicitly rule out side effects. This is adequate behavioral context for a simple read 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?

Three sentences, each serving a purpose: the first lists outputs and supported chains, the second provides the use case, and the third covers data source and cost. No filler or redundant content; information is front-loaded.

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

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

Despite no output schema, the description conveys what will be returned (metrics), the input constraints (chains, token type), the use case, the data source (Blockscout), and the cost model. This is sufficient for an agent to decide when to call and what to expect, especially compared to typical tool descriptions.

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 and address documented). The description adds meaning by clarifying address accepts 'any ERC-20/721 token contract' and enumerating the supported chains. It also hints at the x_payment parameter through the '$0.01 via x402' pricing note, though it does not explicitly describe 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 clearly specifies the tool's function: retrieving total supply, holder count, decimals, and live USD price/market cap for ERC-20/721 tokens across six chains. It distinguishes itself from sibling chain_* tools by emphasizing supply-focused metrics and positioning as a 'supply read' for trading and risk agents.

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 states when to use the tool: 'The supply read trading, valuation and risk agents make to size circulating supply, dilution and holder distribution before pricing or trading a token.' It also provides a clear alternative to running one's own RPC. However, it does not explicitly mention when not to use or name alternative sibling tools.

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

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

With no annotations provided, the description carries the burden and does a solid job: it discloses the cost ($0.09 via x402), the live data source (Blockscout), and the read-only nature ('read agents'). It does not explicitly say 'does not modify state' or mention auth/error behavior, but the intent is clear and 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?

The description is dense but uses every clause for useful information. The first sentence is a long run-on but front-loads the core purpose. Subsequent sentences add use cases, chains, and value proposition. It is slightly overloaded but well-structured for an AI agent that needs rich context.

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, the description fully explains what the tool returns: plain-English explanation, list of asset changes, status, fee, and decoded method. It also covers supported chains and the use case rationale, making it complete for a complex tool with no structured output definition.

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 have good descriptions, but x_payment is undocumented. The description adds context by mentioning the cost and 'via x402,' which implies the payment parameter's purpose, but it doesn't explicitly tie this to x_payment. Overall, it adds some meaning beyond the schema but not completely.

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 and resource: 'decode any transaction by hash into a plain-English explanation,' then enumerates concrete outputs (swap, transfer, approval, asset changes, status, fee). It also differentiates from sibling tools by saying 'not just confirm it landed,' explicitly contrasting with chain_transaction_status.

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 states exactly when to use this tool: 'The read agents make to UNDERSTAND a tx, not just confirm it landed: for wallet UX, accounting, risk, dispute and trading agents.' It also names the alternative (chain_transaction_status) by implication and lists supported chains, providing clear context without ambiguity.

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

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

With no annotations provided, the description carries the full burden. It discloses the data source ('Live from Blockscout'), the cost model ('one paid call'), and that it is a read operation ('look up'). It does not detail error handling or rate limits, but the key behavioral traits are 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 information-dense but not overly verbose. It front-loads the purpose, then provides use case, supported chains, and source/cost. Each sentence contributes value, though it could be slightly more streamlined.

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 returned data fields. It also covers supported chains and data source. Missing error behavior or prerequisites, but for a simple lookup tool with 3 parameters, this is fairly 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% (hash and chain described). The description adds meaning by explaining that hash is used for lookup, chain is a choice among six named networks, and the phrase '$0.09 via x402' gives context to the otherwise undocumented x_payment parameter. This goes beyond the schema.

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

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

The description starts with a clear verb+resource: 'look up any transaction by hash' and lists specific returned fields (confirmation status, block number, confirmations, value, etc.). This distinguishes it from siblings like chain_confirmations and chain_transaction_explain by focusing on full status 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 provides a clear use case: 'The read every settlement, trading and payment agent polls after sending a tx to confirm it landed.' It implies when to use (after sending a transaction) but does not explicitly mention alternative tools or when not to use, so it loses one point.

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

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

With no annotations provided, the description must carry the disclosure burden. It explicitly notes the tool is a 'read' operation and discloses the cost ('$0.03 via x402'), which is helpful. However, it does not describe response format, error behavior, or any payment prerequisites beyond the cost, leaving transparency incomplete.

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

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

The description is a single sentence that front-loads the cost and core value. It is succinct, though the final clause 'The free-data company-intelligence read sales, research and qualification agents make' is grammatically awkward and slightly obscures the intended 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?

Given no output schema or annotations, the description should clarify what the tool returns. It lists the data sources but does not indicate the shape of the response, any prerequisites, or behavior on invalid domains. For a tool that fuses multiple data sources, this leaves significant contextual gaps.

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

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

The schema describes 'domain' with an example, but 'x_payment' has no description, and schema coverage is only 50%. The description mentions the cost via 'x402' but does not explain the x_payment parameter's format or semantics, failing 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 clearly states the tool's function as a 'Company/Domain Enrichment Connector' and enumerates the specific data sources: RDAP domain age, registrar, DNS email provider, and Wikipedia company profile. This is a specific verb+resource, and the fusion of these distinct data types distinguishes it from sibling tools like wikipedia_lookup or b2b_lead_enrichment.

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 target users ('sales, research and qualification agents') and implies a use case, but does not explicitly state when to use this tool versus alternatives or when not to use it. There are no exclusions or comparisons to sibling tools, so usage guidance is partially 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 disclosure burden. It transparently reveals the cost ($0.01 via x402) and the output format (a single GO/CAUTION/AVOID recommendation). However, it does not mention what happens on failure, rate limits, or whether raw data is also returned beyond the recommendation.

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

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

The description is dense and packed with relevant information in two sentences. The phrase 'ONE call' and 'instead of chaining...' are purposeful. There is slight promotional tone ('Token Intelligence Connector', 'trading & sniping agents make') but every clause contributes to understanding the tool's 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?

The tool has no output schema, but the description explains the return concept (GO/CAUTION/AVOID) and the data sources. It mentions the cost and the fact it is a single call. It does not describe exact response fields or error handling, but given the tool's slim parameter set and clear purpose, it is largely contextually 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 already documents chain and address (67% coverage). The description adds context about the x402 payment mechanism and that the call costs $0.01, but does not explicitly explain the x_payment parameter. Overall, it adds marginal value beyond the schema without fully covering all parameters.

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

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

The description clearly states it is a token intelligence connector that fuses GoPlus rug-check and Dexscreener market data into a single GO/CAUTION/AVOID recommendation. It uses specific verbs like 'fuses' and names the exact data sources, distinguishing it from siblings like token_security_check and 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?

Explicitly says this is the aggregator call trading & sniping agents make 'instead of chaining rug-check + dex separately.' This provides clear when-to-use guidance and names the alternative of using two separate tools, fully satisfying usage differentiation.

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. It clearly discloses the behavior: it queries multiple AI models for recommendations and outputs a score, mention rate, and alternative names. It also transparently notes the cost ($0.09 via x402). It lacks details on data freshness, methodology, or prerequisites, but the core behavioral traits are 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 three sentences, front-loaded with price and the core question, then outputs, then use case and uniqueness. Every sentence adds value, with no repetition or fluff. It is efficiently structured and easy to scan.

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

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

Since there is no output schema, the description compensates by explaining the return values: AI-visibility score 0-100, mention rate, and alternative projects. It also covers the input context, use case, and cost. Missing details like x_payment behavior or request flow are minor given 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 description coverage is 67% (project and category have descriptions, x_payment does not). The description adds context to the category parameter by framing it as 'the best in its category' and clarifying that project refers to token/protocol/chain. However, it does not explain the x_payment parameter, and the added semantics are modest 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 explicitly states what the tool does: it checks whether ChatGPT/Perplexity/Google AI recommend a given token, protocol, or chain for a category, and returns a visibility score, mention rate, and alternative projects. This is a specific verb+resource+output and differentiates from sibling tools by claiming to be 'The only AI-recommendation data for crypto projects.'

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

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

The description implies the tool is a 'narrative/attention signal for crypto trading and research agents,' suggesting when it should be used. However, it does not explicitly state when to use this tool versus sibling alternatives like ai_visibility_index or ai_visibility_signal, nor does it mention exclusions or preferred scenarios beyond that use case.

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

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

With no annotations, the description carries the 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?

There are no annotations provided, so the description carries the full burden of behavioral disclosure. The description reveals it's a read operation (fetching prices) and mentions the x402 payment cost, but doesn't disclose undefined behavior for invalid CoinGecko IDs, rate limiting, latency, or whether stale/cached data may be returned. For a tool without annotation coverage, more behavioral context would be expected.

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 purpose, data source, format, and pricing into minimal text. Every element earns its place, and there is zero waste. The pricing prefix '$0.01 via x402' is front-loaded and 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 simple price-fetching tool with no output schema and no annotations, the description covers the essentials: what it returns (current USD prices), how to specify coins (comma-separated CoinGecko IDs). Gaps include the undocumented x_payment parameter and lack of explicit description that it returns a mapping of id to price (though inferable). Given low complexity, the description is reasonably complete but leans on inference.

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

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

Schema description coverage is 50%, meaning the 'ids' parameter is documented ('e.g. bitcoin,ethereum') but 'x_payment' is not described in either the schema or the tool description. The example in the schema demonstrates the comma-separated format clearly for the main parameter. The description implies the CoinGecko ID requirement, which adds value. However, x_payment semantics are entirely undocumented.

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

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

The description states a specific verb+resource: 'current USD prices by CoinGecko id', which clearly conveys the tool fetches cryptocurrency prices. It distinguishes itself from price-adjacent siblings like crypto_market_metrics and get_crypto_liquidations by being focused on simple spot USD prices by CoinGecko ID. The '$0.01 via x402' pricing info adds practical context.

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

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

The description implies when to use this tool (to get simple current USD prices for specific coins by CoinGecko ID), and the comma-separated format hints at supporting multiple ids. However, it doesn't explicitly state when NOT to use it or name alternatives like crypto_market_metrics for broader market data, nor does it clarify the distinction between this and similar crypto pricing tools among 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 provided, the description partially carries the transparency burden. It discloses the comparison nature, pricing ($0.09 via x402), and output type ('spreads + verdict'), but omits details like data sources, update frequency, or how 'top' is determined. This is useful but not comprehensive.

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

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

The description is a single, compact sentence that packs in purpose, pricing, and outcome. It is front-loaded and free of fluff, though the 'TradFi x DeFi' tagline is mildly jargon-heavy. Still, it earns its place.

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

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

Despite no output schema and no annotations, the description provides only a high-level overview. It does not explain what a 'verdict' looks like, how to interpret the spread, or how to use the parameters effectively. For a tool that likely returns a complex comparison, this is insufficient.

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% (min_tvl described, x_payment not). The description adds no parameter-level explanation, leaving x_payment completely ambiguous. It does not compensate for the uncovered parameter, and even for min_tvl it repeats the schema's default rather than explaining impact on results.

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: comparing top stablecoin DeFi yields to the official US T-bill rate, with spreads and a verdict. This specific verb+resource structure distinguishes it from sibling tools like defi_yields or us_treasury_rates, which cover only 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 the use case (comparing TradFi vs DeFi returns) but does not explicitly state when to use this tool over alternatives. No mention of exclusions or sibling tools, though the value proposition is clear enough to infer a primary scenario.

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?

No annotations are provided, so the description carries the full burden. It discloses the live nature, source, cost, and output metrics, but lacks details on response format, error handling, rate limits, or authentication beyond the payment note.

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

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

The description is a single compact sentence that efficiently packs cost, input types, output metrics, timeframes, chain coverage, source, and intended users. Every clause adds value, and it is front-loaded with the most important 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?

Despite lacking an output schema, the description enumerates the returned data categories and timeframes, giving agents a clear expectation. It could be more complete by describing the response structure or potential limitations, but it covers the essential information for invoking 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 already describes q as 'Token symbol, name, or contract address', and the description reinforces this. The x_payment parameter is undocumented in the schema, and the description only mentions '$0.01 via x402' without explaining how to set or use it, leaving a significant gap.

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

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

The description clearly states the tool provides 'live decentralized-exchange data for any token' and lists specific metrics (USD price, 24h volume, liquidity, buy/sell counts, momentum) across timeframes and chains. It distinguishes itself from sibling tools like crypto_prices by emphasizing DEX-specific, cross-chain data, and names the source (Dexscreener).

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 mentions target use cases ('crypto trading, sniping, and research agents') and the cost, implying it is an on-demand DEX data tool. However, it does not explicitly compare with alternatives or state when not to use it, leaving some ambiguity among sibling tools like crypto_prices.

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?

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 provided, the description carries the burden. It discloses that this is a 'Live public RPC' and a 'paid call,' which are behavioral traits. It also frames it as a 'freshness read,' implying a read-only operation. However, it doesn't detail error behavior, rate limits, or response format.

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

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

Three concise sentences, front-loaded with the core function, then use case, then cost/RPC details. Every sentence earns its place.

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

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

For a simple read tool with one documented parameter, the description provides the method, supported chains, use case, and cost. It lacks an explicit response format, but the standard eth_blockNumber method implies a hex block number; still, given no output schema, a bit more detail could help.

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

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

The input schema already documents the single parameter (x_payment) with 100% coverage. The description adds no additional parameter semantics, so baseline 3 applies.

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

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

The description clearly states the tool returns the current chain tip (latest block height) via eth_blockNumber across multiple chains, distinguishing it from sibling tools like chain_block_header or chain_confirmations.

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 identifies the usage context: 'The freshness read settlement, indexing and trading agents poll to know where the chain is.' This implies when to use it, but it doesn't explicitly exclude alternatives or name sibling tools.

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

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

With no annotations, the description carries the 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 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 burden of behavioral disclosure. It does state it is a 'read' operation, built live from USAspending.gov, and mentions a cost ($0.09 via x402). However, it does not disclose potential rate limits, failure modes, or nuances like data freshness windows beyond 'recent.' This is moderate transparency for a non-destructive read 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 compact and front-loaded with the core purpose, then adds cost, data source, and use case. Each sentence earns its place: the first defines the tool, the second provides provenance, the third signals intended beneficiaries. 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?

There is no output schema, so the description compensates by naming the return fields: top recipients, award amounts, awarding agencies, and sector activity score. It also covers context like data source and pricing. It lacks detail on edge cases or response shape, but for a search tool with three simple parameters, it is sufficiently complete.

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

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

Schema description coverage is 67% (q and months documented, x_payment not). The description adds minimal meaning beyond the schema—it reiterates 'keyword/sector' which maps to q and implies 'recent' relates to months, but offers no additional semantics for x_payment. Since coverage is not high enough to reach baseline 4 but not low enough to require heavy compensation, a baseline 3 is appropriate.

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

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

The description clearly states the tool's function: 'search recent US federal contract awards by keyword/sector and get the top recipients, award amounts, awarding agencies, and a sector activity score.' It also explicitly ties it to USAspending.gov, distinguishing it from sibling tools like eu_tender_intelligence. This is a specific verb+resource+output description that fully differentiates it in the tool ecosystem.

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 intended usage: 'The market-intelligence read sales, research, competitive-intel and prospecting agents make to see who's winning government money in a space.' This gives context on when to use the tool but stops short of explicitly stating exclusions or naming alternative tools. It is clear enough for an agent to understand its niche without explicit 'when-not-to-use' guidance.

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

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

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?

No annotations exist, so the description carries the full burden. It mentions the $0.09 cost and x402 payment, alluding to payment requirements, but does not disclose behavior on failures, rate limits, auth requirements beyond payment, or response format. Minimal transparency.

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

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

The description is a single terse sentence, which is concise but under-specified. It is not structured with clear sections or examples, making it efficient in length but lacking 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?

With no output schema, the description should explain what the tool returns, but it does not. It also omits error handling, prerequisites, and usage examples. The tool is simple enough that some context is inferred from 'OpenAI-Compatible,' but completeness is still inadequate.

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% (x_payment has a description). The description does not explain 'model' or 'messages,' though 'OpenAI-Compatible' hints at standard chat format. It adds no detail on how to structure messages or what models are available, failing to compensate for 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 identifies the tool as a 'Premium OpenAI-Compatible Proxy' with 'fallback routing for autonomous LLM crawlers,' which clearly implies it serves chat completion requests. It distinguishes itself via pricing and fallback routing, though the exact verb is implied 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?

The description gives a hint of intended use (fallback for LLM crawlers) but does not specify when to use this tool over the many sibling proxies (e.g., bedrock_proxy, vertex_proxy). No exclusions or alternative recommendations 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?

The description discloses cost ($0.09 via x402) and fallback routing, adding some behavioral context beyond the schema. However, with no annotations provided, it fails to explain key behaviors such as how fallback works, whether responses match Anthropic's format, 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 a single sentence, making it highly concise with no filler. However, it trades substance for brevity; while it earns its place by adding cost and use-case information, it is under-specified for a tool with this complexity.

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

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

Given no annotations, no output schema, and only partial schema coverage, the one-sentence description is severely incomplete. It omits return format, request/response behavior, and how the proxy handles the messages array, making it inadequate for reliable 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 input schema only describes x_payment; the description does not explain `messages` or `model`. With only 33% schema coverage, the absence of parameter semantics in the description leaves the most important parameters completely ambiguous, and no effort is made to compensate.

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

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

The description frames the tool as a 'premium Anthropic-compatible proxy' with 'fallback routing,' but it lacks an explicit verb or functional statement clarifying what the tool actually does (e.g., send messages to an LLM). It vaguely distinguishes from sibling proxies via the x402 cost and fallback routing, but the core purpose remains ambiguous.

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

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

The description mentions 'fallback routing for autonomous LLM crawlers,' implying a niche use case, but it does not specify when to choose this over alternatives like llm_chat_completions or other proxy tools. No exclusions, prerequisites, or alternative tool references are given.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It discloses the cost ($0.09 via x402) and the output format (Markdown), which are useful traits. However, it does not mention any potential limitations, such as handling of dynamic content, rate limits, or error behavior, leaving significant gaps for a scraping 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 sentence that front-loads the cost and purpose, immediately conveying the most critical information. It is free of filler and every word contributes to understanding what the tool does.

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 schema (2 params, no output schema) and the context of many sibling tools, the description is adequate but not complete. It specifies the output format (Markdown) and the cost, but lacks information about edge cases, usage examples, or how it differs from the closely related 'web_scrape' tool. More guidance would improve completeness.

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

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

The input schema already provides 100% coverage with descriptions for both 'url' and 'x_payment'. The description adds minimal extra meaning by framing the tool for 'autonomous web research', but it does not elaborate on parameter formats or constraints beyond what the schema states, so the baseline of 3 is appropriate.

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

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

The description clearly states the tool converts any URL into clean Markdown, with a specific verb ('converts') and resource ('URL'). It is distinct from siblings by emphasizing 'LLM-Optimized' and Markdown output, but it does not explicitly differentiate itself from similar tools like web_scrape or web_crawl.

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 mentions 'for autonomous web research', which gives a clear context for use, but it does not provide explicit guidance on when to use this tool versus alternatives, nor does it mention any exclusions or prerequisites. The intended use case is implied rather than explicitly stated.

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

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

With no annotations, the description carries the full burden. It discloses the cost, the wallet-to-wallet settlement model, and that the house never holds funds, which is non-obvious and valuable. It does not mention irreversibility or failure behavior, but the given details are substantive.

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

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

The description is two concise sentences that front-load the purpose and cost. Every clause adds value (settlement model, return value), with no filler or repetition of schema fields.

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, but the description covers purpose, return value, and settlement. However, parameter semantics and explicit usage guidance are missing, leaving gaps for an agent to understand how to construct a valid 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 only 33% (x_payment has a description, task_id and bid_id do not). The description does not explain task_id, bid_id, or how x_payment should be supplied beyond the 'via x402' mention, which is insufficient to 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 states a specific verb ('award') and resource ('a task to a winning bid'), clearly distinguishing it from siblings like market_bid and market_post_task. It also describes the key return value (winner's direct payment details) and the cost 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?

The context of 'winning bid' and 'award' implies this is the post-bidding payment step, and the settlement details clarify the payment flow. However, it does not explicitly mention alternatives or when not to use the tool, nor does it reference sibling tools for comparison.

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

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

With no annotations, the description adds behavioral context: bidding is free, and payment goes to pay_to via x402/USDC on Base. Discloses a key side effect (payment direction) but does not detail outcome or constraints like bid limits.

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?

Single sentence, no wasted words, front-loaded with core action. Perfectly concise.

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

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

Adequately covers the main purpose and payment, but given 7 parameters and no output schema, it leaves many details unspecified (constraints, bid outcome, task requirements). Completeness is acceptable but not thorough.

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

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

Schema description coverage is low (29%); only pay_to and agent_url have descriptions. The description reinforces pay_to's purpose but does not explain pitch, eta_hours, task_id, agent_name, price_usdc. Fails to compensate for missing 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?

Clearly states the tool bids on an open task and mentions payment mechanism. Verb 'bid' and resource 'open task' are specific, and it distinguishes from siblings like market_post_task (posting) and market_award (awarding).

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?

Implies when to use ('Bid on an open task'), but does not provide explicit guidance on when not to use or suggest alternative tools. Could mention siblings like market_post_task or market_list_tasks for context.

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

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

No annotations are provided, so the description must disclose behavioral traits. It only states 'Free' and fails to mention default behavior when status is omitted, rate limits, or required permissions. The minimal disclosure is insufficient.

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

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

The description is a single, clear sentence with no unnecessary words. It directly conveys the tool's purpose and available filter.

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 listing tool with one optional parameter and no output schema, the description adequately states the purpose and filter options. It lacks detail on default behavior, but overall is complete enough for 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% for the single parameter. The description adds 'filter by status=open|awarded|settled' which clarifies acceptable values but does not explain default behavior or provide additional context 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 explicitly states the action 'Browse' and resource 'open agent-to-agent tasks on the Clearing House', with a filter option. It clearly distinguishes from siblings like 'market_award' or 'market_bid' which handle different actions.

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 mentions filtering by status with specific values, indicating usage scenarios. While it does not explicitly state when not to use or provide alternatives, sibling names imply different purposes, making the intended use reasonably 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 provided, so description must carry the burden of behavioral disclosure. Description implies it shows fees/flow/stats, but also mentions actions like 'post tasks, bid, award, settle' without clarifying if this tool performs them or just describes the market. It does not indicate whether the tool is read-only or has side effects.

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 but is overloaded with information: fees, flow, live stats, and a laundry list of market actions. It could be clearer by separating the overview function from the description of the market. While relatively short, it lacks focus.

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

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

Given the tool has no parameters, no output schema, and many sibling tools, the description should clarify exactly what information or capability the tool provides. It mentions 'fees, flow, live stats' but does not specify how these are presented or what exactly the agent receives upon calling. The mention of actions like posting tasks and bidding further confuses the scope, making the description incomplete for effective agent use.

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

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

No parameters exist (schema coverage 100%), so description does not need to explain parameters. It adds context about the kind of data (fees, flow, live stats) beyond the empty schema, which helps the agent understand what the tool returns.

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 calls it a 'front door' but then lists a series of actions (post tasks, bid, award, etc.) that are likely performed by sibling tools like 'market_post_task' and 'market_bid'. It does not clearly distinguish whether this tool provides an overview/aggregate data or actually performs those actions. The verb 'Agent Clearing House front door' is vague and does not specify what the tool does beyond showing 'fees, flow, live stats'.

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 on when to use this tool versus the many sibling tools like market_list_tasks, market_post_task, market_bid, etc. An agent has no context to decide when to call market_overview instead of these more specific 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?

Describes the core behavior: posting is free, agents bid, payment is non-custodial. Without annotations, this provides reasonable transparency about the process, though it omits potential side effects or prerequisites.

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?

Extremely concise and well-structured: two sentences that immediately convey the purpose and key behavioral notes. No redundant 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?

Lacks explanation of output (e.g., task ID or confirmation) and does not cover optional parameters. With no output schema, the description should address what the agent can expect after posting, but it does not.

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 25%. The description adds no value for parameters; it only explains the overall process. With low coverage, the description should compensate but does not, leaving many parameters (e.g., category, budget_usdc) 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?

Clearly states the action ('Post a task to the agent market') and explains the flow (free posting, bidding, direct payment). Differentiates from siblings like market_bid and market_award.

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?

Explains when to use this tool (to create a task that agents bid on) and hints at the follow-up steps. Does not explicitly mention alternatives or when not to use, but the context is clear enough.

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

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

The description discloses several important behaviors beyond what annotations would provide: the cost ('$0.09 via x402'), the verification mechanism ('Tx hash is verified on Base RPC'), and side effects ('both agents' passports (BotScore) update on verification'). It does not mention failure modes or reversibility, but the disclosed details are substantive and carry a meaningful transparency burden in the absence of 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?

The description is a single, dense sentence that packs cost, action, condition, verification, and side effects without any filler. Every word carries meaning, making it both concise and well-structured for quick agent consumption.

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, yet the description omits return values, potential errors, and detailed parameter requirements. While it provides core behavioral context (cost, verification, side effects), it is incomplete for safely invoking a 7-parameter tool with undocumented parameters and no defined response format. Significant information is left to inference.

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

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

With schema description coverage at 0%, the description must compensate, but it only indirectly hints at tx_hash ('Tx hash is verified') and payer/payee ('both agents' passports'). It does not explain other parameters like task_id, network, amount_usdc, or x_payment, and their roles remain unclear. This is a significant gap for a 7-parameter tool.

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

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

The description clearly states the tool's function: 'publish a public receipt for a settled task.' The verb 'publish' and resource 'receipt' are specific, and the condition of 'settled task' differentiates it from sibling market tools like market_bid, market_award, and market_post_task. No other sibling tool performs receipt publication.

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