Riley Craig x402 Agent Store

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

No annotations provided, so description carries full burden. It discloses it provides a BotScore (0-100) and reputation from chain-verified receipts, implying read-only behavior. Does not mention auth or rate limits, but for a simple lookup tool, it is adequately transparent.

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

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

Single sentence, front-loaded with key elements, no extraneous information. Efficient and clear.

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, description explains return data (verified tasks, USDC volume, counterparties, BotScore). Lacks details on error cases or empty results, but sufficient for agent to understand expected output.

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 describes parameter 'address' adequately. Description adds meaning by detailing what the tool returns, which schema does not cover. Since schema coverage is 100%, baseline is 3; description adds value justifying 4.

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 tool returns agent passport and BotScore, listing specific data points (verified completed tasks, settled USDC volume, distinct counterparties) and source (chain-verified receipts). Distinguishes from siblings as no other tool provides this reputation 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 explicit guidance on when to use vs alternatives. However, purpose is clear, and context implies use for retrieving agent reputation. Missing when-not-to-use or alternative tool mentions.

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

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

No annotations are provided. The description mentions a cost of '$0.02 via x402' and states the tool uses 'a current model' for live ranking, but does not specify which model, update frequency, reliability, or whether the data is real-time. These gaps leave the agent with insufficient behavioral understanding.

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 compound sentence that packs key information (cost, purpose, output, use cases). It is front-loaded and efficient, though its density could be slightly improved by breaking into bullet points or clearer segments.

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

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

Given there is no output schema and only one required parameter, the description adequately defines the general purpose and output type (ranked shortlist by mention share) but lacks specifics about the output format (e.g., JSON structure, pagination, or confidence indicators). The undocumented 'x_payment' parameter also remains unclear.

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% (category and market have descriptions, x_payment does not). The description adds useful context for 'category' (examples) and 'market' (default value), but adds no meaning for 'x_payment' beyond the cost hint. The added value is moderate, compensating partly for the undocumented 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 action: live AI category ranking. It specifies the resource (AI model), the action (ask for ranking in any category), and the output (ranked shortlist by mention share). It distinguishes itself from siblings like brand_ai_visibility_check by calling itself 'the inverse of a brand check' and targeting competitive landscape analysis.

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

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

The description implies usage for competitive-intel, market-research, GEO, and sales agents, but does not explicitly state when to use this tool over siblings or when not to use it. It provides context but lacks exclusions or alternative tool references.

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

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

No annotations exist, so the description must fully disclose behavior. It mentions a payment mechanism ($0.005 via x402) but does not explain how x_payment affects output, or what happens if absent. No details on side effects or data access.

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 not informative. It front-loads pricing instead of clarifying functionality. Important information about the tool's operation is missing.

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

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

No output schema exists, yet the description fails to explain the return format or content. With only two optional parameters, the description should clarify what the tool provides, but it remains cryptic.

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% with descriptions for 'category' and 'x_payment'. The tool description adds minimal value beyond the schema, mentioning the payment amount but not clarifying usage. Baseline 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?

The description mentions 'proprietary AI-visibility scores for 25 major brands across 5 industries' but adds 'with competitors AI names instead,' which is confusing and does not clearly state what the tool returns. The purpose is vague and lacks specificity.

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

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

No guidance is provided on when to use this tool over alternatives like 'ai_category_ranking' or 'brand_ai_visibility_check'. The description does not mention any 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 present, so the description carries the full burden. It discloses that a payment via x402 is required and that it's a live feed, but it lacks details on data update frequency, response format, or whether it's a stream or snapshot. The behavioral transparency is minimal.

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, concise and front-loaded with the cost and purpose. However, it may be too brief, lacking structural elements that could improve clarity.

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

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

Given the tool's simplicity (one optional parameter, no output schema), the description provides the core purpose and payment requirement. However, it does not explain the return format or how the live feed works, leaving gaps for an agent.

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

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

The schema has 100% description coverage with one optional parameter (x_payment). The description adds context that the tool costs $0.005 via x402, clarifying the payment requirement and linking it to the parameter. This goes beyond the schema's generic 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 clearly states the tool provides a live feed of brands/categories being checked for AI-search visibility. The verb 'feed' and the resource are specific, and it distinguishes from siblings like brand_ai_visibility_check (point check) and ai_category_ranking (rankings).

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 real-time monitoring but provides no explicit guidance on when to use this tool versus alternatives like brand_ai_visibility_check or ai_category_ranking. No conditions or when-not-to-use are mentioned.

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, but description discloses cost, payment method, and detailed outputs (score, mention rate, competitor names, evidence). Does not explicitly state read-only nature, but no destructive actions implied. Good disclosure of what the tool does and what it returns.

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 is concise and packs key information (premium, method, outputs). Could be better structured with line breaks for readability, but no unnecessary 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 no output schema, description sufficiently explains return values (score, mention rate, competitor names, evidence). Also covers payment mechanism. Complete enough for a tool with 4 parameters and no output schema.

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 covers all 4 parameters with descriptions. The description adds context beyond schema: explains that the audit uses real buyer questions through an LLM, and the output includes evidence and competitor mentions. This adds meaningful semantic value.

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

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

Clearly states it performs a live brand AI-visibility audit with specific outputs (score 0-100, mention rate, competitor names, evidence). The verb 'audit' and resource 'brand AI visibility' are clear, but does not explicitly differentiate 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?

Implied usage from 'PREMIUM ($0.95 via x402)' suggests use when a deep, paid audit is needed. No explicit when-not or alternatives guidance given, though sibling tools exist (e.g., ai_visibility_index for free overview).

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 description carries full burden. It discloses 'Live ENS registry', 'one paid call', and 'x402' payment, but does not address behavior when both parameters are provided or omitted, potential errors, or the exact role of the x_payment parameter. Some behavioral aspects are unclear.

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?

Description is about four sentences, front-loaded with primary function, and adds use-case context efficiently. No redundant or unnecessary sentences.

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 3 parameters (one undocumented), description adequately explains bidirectional resolution but lacks details on output format, error handling, and interplay between parameters. Leaves gaps for a complete understanding.

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 covers name and address with descriptions; description adds examples and avatar detail for reverse resolution. The x_payment parameter is briefly mentioned as '$0.001 via x402' but not fully explained. Overall, description adds some context beyond schema but does not fully compensate for missing x_payment documentation.

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

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

Description explicitly states the tool resolves ENS in both directions (name to address and address to name) with examples, distinguishing it clearly. It also provides context on its use case for identity verification. No sibling tool overlaps, so purpose is unambiguous.

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

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

Description implies usage for ENS resolution needs and mentions it's a paid call replacing a self-run resolver. However, it does not explicitly state when not to use or list alternatives. Context about identity verification helps agents understand when to invoke.

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, but description discloses cost ($0.001 via x402), read-only nature (pre-send read), and multi-chain support. Does not mention return format or potential errors.

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: purpose and cost in first, parameter hint in second. Front-loaded, no fluff.

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

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

Explains behavior and cost but lacks output format details, parameter explanations for partially documented fields, and any prerequisites or error conditions.

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% (4/6 parameters have descriptions). Description adds that 'to' is required and 'from/value/data' are optional, but omits x_payment and from meaning. Provides marginal extra value beyond schema.

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

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

Clearly states the tool estimates gas for a transaction across 6 chains using eth_estimateGas. Distinguishes from siblings like chain_gas_price by focusing on per-transaction estimation.

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 usage before sending a transaction to avoid out-of-gas reverts. Provides context for tx-building and trading agents. Lacks explicit exclusions or alternative tool mentions.

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. The description discloses it is a paid call ($0.001 via x402), live from Blockscout, and returns three speeds in gwei. It implies read-only behavior ('pre-transaction read') but lacks details on authentication, rate limits, 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?

Two sentences contain all essential information: cost, output, supported chains, data source, use case, without any unnecessary words.

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

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

For a simple read tool with 2 parameters and no output schema, the description covers the return values (slow/average/fast in gwei) and source (Blockscout). It lacks explicit mention of response format but is sufficient for an agent to understand what it receives.

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 2 parameters with 50% description coverage. The description adds context for the 'chain' parameter (default ethereum, lists options) and hints at payment via '$0.001 via x402', but the 'x_payment' parameter is not explained. Some added value but incomplete.

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 network gas prices (slow/average/fast in gwei) for multiple specified chains, explicitly distinguishing it as a pre-transaction read for fee sizing. No sibling tool overlaps this 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?

The description explicitly states when to use this tool: 'the pre-transaction read every trading, sniping and settlement agent makes before sending a tx to size the fee.' It does not explicitly mention when not to use it or provide direct alternatives, but the use case is clear.

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

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

With no annotations, the description carries full burden. It discloses the cost ($0.001 via x402) and that it's a read-only operation (no side effects). However, it does not mention rate limits, authentication needs, or other behavioral details. The description adequately conveys the basic behavior but lacks depth.

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 key information and cost. No wasted words. The inclusion of pricing is relevant but could be considered extra; still, structure is efficient.

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

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

No output schema, so description should explain return value. It states 'EIP-155 chain ID' but does not specify format or what the numeric result represents. Also, no mention of default behavior for chain or error cases. Moderately complete for a simple 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 50% (chain parameter has description, x_payment does not). The description adds value by listing the enum values for chain in prose, but does not explain x_payment. This marginally improves parameter meaning but does not fully compensate for the undocumented 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 retrieves the EIP-155 chain ID for any of six specified chains, using a specific verb 'confirm' and resource 'chain ID'. It distinguishes itself from siblings like OneSource by noting its multi-chain support.

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

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

The description provides explicit usage context: 'confirm which chain an RPC is on before signing'. It differentiates from OneSource (Ethereum-only) by highlighting multi-chain capability. However, it does not explicitly state when not to use this tool.

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

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

No annotations provided; description carries full burden. Describes it as a read operation returning live data from Blockscout with cost details. Lacks details on rate limits, authentication, or idempotency.

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 key info. First sentence packs details but slightly messy; second sentence is somewhat redundant. Could be more structured but overall 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 no output schema and many sibling tools, description provides sufficient context: unique selling point (cheapest), supported chains, return payload elements, and use cases. Covers all essential aspects.

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 covers 67% of parameters with descriptions; description adds meaning by listing supported chain values and indicating that the balance is native coin. Also explains return values (USD value, tx count) not in 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?

Clearly states it returns native coin balance, USD value, and outgoing transaction count for any address across multiple chains. Uses specific verb (returns balance) and identifies the resource (address's native coin). Distinguishes from siblings like chain_gas_price and wallet_portfolio by emphasizing cheap cost and multi-chain support.

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

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

States it is for high-frequency balance checks by wallet-tracking, settlement, and trading agents, indicating when to use. However, no explicit exclusion of alternatives or comparison to siblings like chain_token_supply.

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 it is a read operation and the cost ($0.001 via x402), but with no annotations provided, it lacks details on error behavior, rate limits, or return format. This is adequate 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 concise sentence followed by a short fragment, front-loading the cost and action. Every word earns its place with no fluff.

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

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

Given no output schema, the description should mention the return format (e.g., raw hex). It omits this and does not explain the x_payment parameter. The tool's simplicity keeps it from being worse, but completeness is moderate.

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 descriptions for address, slot, and chain. The description only adds 'Pass address + slot', which is redundant. The x_payment parameter is undocumented in both schema and description, missing an opportunity to add value.

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

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

The description clearly states it reads a raw storage slot across 6 chains, with specific use cases (audit, proxy-resolution, advanced trading). The verb 'read' and resource are explicit, distinguishing it from sibling tools like chain_native_balance or 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 mentions suitable use cases ('for audit, proxy-resolution and advanced trading agents'), providing context on when to use. However, it does not explicitly state when not to use or offer alternatives among the many 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?

No annotations are provided, so the description carries the full burden. It discloses that data is 'Live from Blockscout' and that it is a 'one paid call' costing '$0.001 via x402'. This gives useful insight into data source and pricing, though it doesn't detail error handling or rate 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?

The description is two sentences, front-loaded with the primary function in the first sentence. Every word adds value, with no fluff or repetition of schema details.

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

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

Given the tool has 3 parameters, no output schema, and no annotations, the description covers purpose, supported chains, data fields, pricing, and use case. It does not detail return format or error handling, but is reasonably complete for a simple read operation.

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

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

Schema coverage is 67% (chain and address described, x_payment not). The description adds meaning by listing supported chains explicitly and mentioning the data fields returned (total supply, holder count, etc.), which is not in the schema. It also hints at the x_payment cost mechanism.

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 retrieves total supply, holder count, decimals, and live USD price/market cap for any ERC-20/721 token across multiple chains. Specific verbs like 'read' and 'size' are used, and it distinguishes itself from sibling tools by focusing on supply and basic token info.

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 states the use case: 'The supply read trading, valuation and risk agents make to size circulating supply, dilution and holder distribution before pricing or trading a token.' This provides clear context, though it does not mention when not to use or name alternative tools.

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

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

No annotations are provided, so the description must cover behavioral traits. It discloses the tool is a paid call ($0.002 via x402), explains what is returned (actors, asset changes, status, fee, decoded method), and compares to running an own indexer. While it omits rate limits or auth details, the key behavioral aspects 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 a single paragraph with dense information. It is front-loaded with the core action and use cases. While a more structured format (e.g., bullet points) could improve readability, every sentence contributes value without redundancy. Slightly long but not excessive.

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

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

Given the complexity (multiple chains, detailed output) and no output schema, the description adequately explains return values (asset changes, actors, etc.) and the value proposition. It lacks details on error handling and the x_payment parameter, but overall it provides sufficient context for an agent to determine when to use it.

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% (hash and chain described, x_payment not). The description adds a default chain (base) and context about hash format, but does not explain the x_payment parameter or provide further semantic details beyond the schema. Baseline is 3 due to high coverage; minor additions keep it at 3.

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

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

The description clearly states the tool decodes a transaction hash into a plain-English explanation, listing specific actions (swap, transfer, approval, mint, contract call) and supported chains. It distinguishes itself from a simple status check by emphasizing understanding over confirmation, making the purpose highly specific and differentiating.

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 mentions use cases (wallet UX, accounting, risk, dispute, trading agents) and implies when not to use (not just for confirmation). It does not directly name alternative sibling tools like chain_transaction_status, but the context of understanding vs. confirmation provides sufficient 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 cost ($0.001 via x402), that it is a read operation, that it uses live data from Blockscout, and that it is a paid call. It does not cover rate limits, error behavior, or idempotency, but for a simple lookup tool the disclosure 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 long and packs essential information: purpose, return fields, use case, supported chains, cost, and data source. Every sentence adds value, and there is no redundancy. It is concise and well-structured for quick comprehension.

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

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

Given no output schema, the description lists all key return fields (confirmation status, block number, value, etc.). It also covers the use case, supported chains, and cost. For a transaction status lookup tool, this provides sufficient context for an agent to understand what to expect. Minor omission: no mention of error handling or format of the output.

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%: hash and chain are described in the schema with format and options. The description restates the chains but adds no new meaning beyond the schema. The x_payment parameter lacks both schema description and any mention in the description, leaving its purpose ambiguous. The description does not sufficiently compensate for the low coverage of 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 the tool's purpose: 'look up any transaction by hash' and lists specific return fields (confirmation status, block number, value, etc.). It also specifies the intended use case: 'The read every settlement, trading and payment agent polls after sending a tx to confirm it landed.' However, it does not explicitly distinguish from sibling tools like chain_transaction_explain, so it is not a perfect 5.

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

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

The description provides context for when to use the tool: after sending a transaction, and it lists supported chains (Base, Ethereum, Optimism, etc.). However, it does not mention when not to use it or suggest alternative tools like chain_transaction_explain for transaction explanation. No explicit exclusions or comparisons 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 exist, so the description must disclose behaviors. It mentions it's a read operation and costs $0.003, but lacks details on rate limits, error handling, response structure, or security/authorization needs. Partial transparency meets a baseline but leaves 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 concise, front-loading cost and purpose in a single sentence plus a fragment. It avoids verbosity, though the structure could be improved by separating components (e.g., input, behavior, cost) for 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?

No output schema is provided, and the description does not specify return values or error conditions. For a tool with moderate complexity and two parameters (one undocumented), the description is incomplete for fully guiding invocation.

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

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

Schema coverage is 50% (only 'domain' described). The description mentions cost but does not explain the 'x_payment' parameter or how payment works, leaving a critical parameter undocumented. The domain parameter's description in schema is minimal ('e.g. stripe.com'), and the description adds no further semantics.

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

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

The description clearly states it's a 'Company/Domain Enrichment Connector' that fuses RDAP, DNS, and Wikipedia data. This distinguishes it from sibling tools like wikipedia_lookup and web_search, though the verb 'connect' is vague and the action is better described as enriching or retrieving intelligence.

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

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

The description implies use for 'sales, research and qualification agents' but does not explicitly state when to use this tool over alternatives like wikipedia_lookup or sales_qualify_lead. No exclusions or when-not guidance is 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?

No annotations are provided. The description includes cost information ($0.005 via x402) and mentions fusing two sources, but does not disclose error handling, rate limits, or what happens if data is unavailable. The description adds some behavioral context but is 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 two sentences long and directly conveys the core value proposition without unnecessary details. It is well-structured with a cost/purpose lead, but could be slightly more organized.

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

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

No output schema is provided. The description mentions the output recommendation types (GO/CAUTION/AVOID) but lacks details on the full response format, error cases, or how the two data sources are combined. For a tool that fuses multiple data sources, more completeness would be beneficial.

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

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

Schema has 3 parameters with 67% description coverage. The description adds overall function context but does not explain the x_payment parameter or provide additional meaning beyond the schema descriptions for chain and address. The semantic contribution is moderate.

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 fuses GoPlus rug-check and Dexscreener market data into a single recommendation (GO/CAUTION/AVOID). It identifies the specific verb 'fuses' and resource 'token intelligence', and distinguishes it from sibling tools like dex_token_data and token_security_check by emphasizing it is an aggregator.

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 says it's the aggregator call that trading and sniping agents use instead of chaining rug-check and dex separately. This provides a clear use case, but does not explicitly mention when not to use or list alternative tools for specific needs.

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

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

No annotations are provided, so the description carries full burden. It discloses cost ($0.005 via x402), live data nature, and official public-domain source, but lacks details on data freshness, rate limits, error handling, or authentication requirements.

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

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

The description is a single, well-structured sentence that front-loads cost and purpose. Every word adds value, with no redundancy or filler.

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

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

For a tool with no output schema and two parameters, the description adequately explains the returned data (list of indicators with years) and source. It is sufficiently complete for selecting and invoking the tool, though it could mention output format or error scenarios.

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

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

Schema description coverage is 50% (country described, x_payment not). The description adds context by specifying country code format (ISO2/ISO3) and mentioning x402 payment, but does not fully explain the x_payment parameter structure or provide examples.

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

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

The description clearly states it provides live macro/economic indicators for 200+ countries, lists specific metrics (GDP, GDP growth, inflation, unemployment, GDP per capita, population), and identifies the source (World Bank). This distinguishes it well from sibling tools which focus on crypto, chain data, or market tasks.

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 it is for macro, finance, research, and trading agents, implying appropriate use cases. However, it does not explicitly state when to avoid using this tool or suggest 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 full burden. It discloses the cost structure ('$0.05 via x402') and clarifies the output (score, mention rate, projects). However, it does not mention rate limits, error handling, or whether the data is updated in real-time.

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 paragraph with key information first (cost, AI sources, output). It is efficient but includes a marketing claim ('The only AI-recommendation data') that could be trimmed without losing clarity.

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

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

With no output schema, the description explains return values (score, mention rate, projects). However, it omits details on error responses, pagination, rate limits, and how the x402 payment works, leaving some gaps for an agent 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?

Schema coverage is 67% with two parameters described (project and category). The description adds little beyond the schema, only giving example tokens (Aave, Arbitrum, etc.) but not explaining the x_payment parameter or how to use the category field.

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

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

The description clearly states the tool checks if major AI models recommend a crypto project, outputs a score (0-100), mention rate, and alternative projects. It explicitly claims to be 'the only AI-recommendation data for crypto projects,' effectively distinguishing it from siblings like ai_visibility_index and 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?

The description provides context ('A narrative/attention signal for crypto trading and research agents') but lacks explicit guidance on when to use this tool versus alternatives. No mention of when not to use it or direct comparisons to sibling tools.

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

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

No annotations are provided, so the description carries the full burden. It discloses the cost ('$0.001 via x402'), which is a key behavioral trait. However, it does not mention rate limits, response format, or other behavioral aspects.

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 of 12 words, highly concise. It front-loads the cost, which is important. However, the phrase '$0.001 via x402' might be cryptic to some agents, slightly reducing clarity.

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

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

Given the tool has 2 parameters, no output schema, and no annotations, the description is relatively sparse. It explains the input but not the output format, error conditions, or pagination. For a simple price lookup, it might suffice, but lacks fullness.

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

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

The schema provides a description for 'ids' ('e.g. bitcoin,ethereum') and no description for 'x_payment'. The description adds 'comma-separated' and 'by CoinGecko id' context for 'ids', and 'via x402' hints at the purpose of 'x_payment'. This adds value beyond the schema.

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

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

The description clearly states the resource ('current USD prices') and the action ('get prices by CoinGecko id'). It specifies the input format (comma-separated ids) and distinguishes from sibling tools like 'crypto_ai_visibility' and 'chain_gas_price'.

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 via the mention of 'via x402' and 'CoinGecko id', but does not explicitly state when to use this tool versus alternatives (e.g., for other crypto data). There is no guidance on prerequisites 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 provided, so description carries the burden. It discloses the monetary cost ($0.005 via x402) and the outcome (spreads + verdict), but lacks disclosure of other behavioral traits such as destructive potential, authorization needs, or rate limits. Since it's likely a read-only operation, the cost disclosure is helpful.

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 efficiently communicates purpose, cost, and output. Front-loaded with cost and comparison target, no filler words. Every element 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?

Description provides a good overview but lacks details on output format, what 'verdict' entails, calculation methodology, data sources, and update frequency. With no output schema and moderate complexity, more context would be beneficial. Adequate but with clear gaps.

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

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

Schema coverage is 50% with 'min_tvl' described in schema (minimum pool TVL), but 'x_payment' lacks description. The overall description mentions the cost mechanism but does not connect it to the parameter 'x_payment', leaving its role unclear. The description adds no additional semantic value beyond the schema for either 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?

Description clearly states the tool compares top stablecoin DeFi yields with US T-bill rate, computing spreads and providing a verdict. The verb 'compare' is implied and the resource is well-defined, distinguishing it from siblings like 'defi_yields' and 'us_treasury_rates'.

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?

Description implies usage for comparing DeFi yields with T-bill rates, but does not explicitly state when to use this tool versus alternatives like 'defi_yields' or 'us_treasury_rates'. No when-not guidance or mention of prerequisites.

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

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

With no annotations, the description carries full burden. It mentions a cost ($0.003 via x402) and live data source, but does not disclose rate limits, data freshness, or what 'x402' means. The cost is a notable behavioral trait.

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, concise but includes cryptically ambiguous '$0.003 via x402' which may confuse. Front-loaded with key info but could be clearer.

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, so description should explain return values but only says 'top DeFi pools'. With 5 parameters and no detail on most, the description is insufficient for full 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 coverage is only 20% (only 'chain' has a default description). The description hints at filtering by chain and TVL but does not explain 'top', 'min_tvl', 'x_payment', or 'stablecoin_only'. Very little added value beyond schema.

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

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

The description clearly states it provides current top DeFi pools by chain and TVL from DefiLlama, distinguishing it from sibling tools like crypto_prices or chain_gas_price which cover different crypto 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 on when to use this tool vs alternatives, no prerequisites or exclusions mentioned. The description implies usage for fetching DeFi yields but lacks context on selection 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?

No annotations are provided, so the description carries the full burden. It discloses the cost ($0.002 via x402) and live source (Dexscreener), which is useful. However, it does not mention authentication, rate limits, or whether the tool is destructive/read-only.

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

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

Two sentences front-load key information. The first sentence is relatively long but packs many details without redundancy. Could be slightly shortened, but overall efficient.

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

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

Given no output schema, the description provides sufficient context on returned data fields (price, volume, etc.) and source, enabling the agent to understand what to expect. Missing response format details reduce completeness slightly.

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% (q described, x_payment not). The description adds value by specifying q input types (symbol, name, contract) but does not explain x_payment beyond the cost mention, leaving its structure unclear.

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

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

The description clearly states the tool provides live DEX data for any token (symbol, name, or contract) with specific metrics like USD price, volume, liquidity, etc. This distinguishes it from sibling tools like crypto_prices or defi_yields which focus on CEX or yield data respectively.

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 agents (trading, sniping, research) but lacks explicit guidance on when to use this tool versus alternatives. Given many sibling tools, mentioning exclusions or comparisons would improve clarity.

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 read-only nature, payment requirement ($0.01 via x402), real-time data ('live'), and output behavior (recent-first ordering, match count). It does not mention rate limits or error conditions, but for a search 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 key purpose ('live public procurement tenders'), and provides essential details without extraneous words. Every sentence earns its place.

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

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

The description covers purpose, input (keyword, months), output fields, and business use. It lacks details on pagination, error handling, or explicit parameter constraints beyond the schema, but for a straightforward search tool it is mostly 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 beyond the schema: 'by keyword/sector' clarifies the 'q' parameter, 'lookback months' is implied for 'months', and '$0.01 via x402' explains the 'x_payment' parameter which otherwise lacks schema description. This compensates for the 67% schema coverage.

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

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

The description clearly states the tool provides live EU public procurement tenders from the official TED database, specifying output fields (title, country, publication date, notice link, match count) and distinguishing it from possible siblings like gov_contract_intelligence by focusing on EU member states and European public-sector spend.

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

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

The description gives clear context for when to use the tool (for European public-sector opportunities targeting sales, BD, research) and mentions 'overseas opportunity layer' which implies it is for non-EU agents. However, it does not explicitly exclude alternatives or mention 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 the real-time nature ('Live from the GitHub Search API') and a cost mechanism ('$0.001 via x402'), but does not cover rate limits, destructive behavior, or required authentication. The transparency is moderate.

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 front-loads key purpose and scope. Every part adds value, with no wasted words.

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

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

Given no output schema and 4 parameters (50% described), the description adequately covers purpose, time range, optional filter, source, and cost. However, it lacks details on the x_payment parameter and language format, leaving some gaps for a complete understanding.

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

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

Schema coverage is 50% (only top and since have descriptions). The description adds 'optional language filter' which maps to the language parameter but provides no details on accepted formats or values for language or x_payment. It does not compensate for the missing schema descriptions.

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

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

The description clearly states the verb 'top trending GitHub repositories by stars' and specifies the time range (day/week/month) and optional language filter. It distinctly separates this tool from siblings like hn_top_stories by mentioning GitHub and trending by stars.

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 fetching trending repos but does not explicitly state when to use this tool versus alternatives like search tools. No exclusions or prerequisites are mentioned.

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; description only hints it's a read operation ('read sales') and mentions live data source. Does not disclose rate limits, pagination, response size, or other behavioral traits.

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?

Description includes non-essential pricing info ('$0.01 via x402') upfront. Main purpose is clear but could be more concise without the sales pitch.

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?

Lists key outputs (recipients, amounts, agencies, score) but lacks details on response format, pagination, or error handling. No output schema to compensate.

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%; description does not add meaning beyond schema for 'q' and 'months'. The 'x_payment' parameter is undocumented in both schema and description. 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?

Clearly states the tool searches US federal contract awards by keyword/sector, listing specific outputs (top recipients, award amounts, agencies, sector activity score). Distinguishes from siblings by specifying 'US federal' and mentioning USAspending.gov as source.

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

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

Provides use cases ('market-intelligence read sales, research, competitive-intel and prospecting agents'), but lacks explicit guidance on when to use this tool versus siblings (e.g., eu_tender_intelligence). No when-not-to-use conditions.

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

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

No annotations are provided, so the description carries full burden. It mentions a cost ($0.001 via x402) and liveness, but does not disclose other behavioral traits such as rate limits, authentication needs, error handling, or data freshness intervals. The 'x_payment' parameter is unexplained.

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 mechanism and then states the purpose. It is concise with no wasted words, though a more structured breakdown could improve clarity.

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

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

No output schema exists, so the description must explain return values. It mentions some fields but lacks details on format, ordering, error responses, and pagination. The 'top' parameter hint suggests 1-20 results, but completeness 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?

The input schema has 50% description coverage (only 'top' has a minimal range description). The tool description does not add meaning to the parameters; 'x_payment' is entirely undocumented. The description instead focuses on output fields, not 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 states it returns Hacker News top stories with specific fields (score, author, comment count, links) and indicates it is live data. It is a specific verb-resource combination, and no sibling tool overlaps with this functionality.

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

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

The description implies usage for fetching top HN stories, but does not explicitly state when to use this tool versus alternatives, nor does it provide exclusions or prerequisites. Usage is clear by context, but lacks explicit 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 provided, so description carries full burden. It discloses the x402 payment mechanism, cost, direct settlement, and return of payment details. This is a good level of transparency for a payment 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?

Two concise sentences that front-load the action and cost. Every word adds value; no fluff.

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

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

With 3 parameters and no output schema, the description adequately covers purpose and payment mechanics. Could mention error cases or constraints, but for a simple transaction tool, 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 33% (only x_payment described). Description adds that task_id and bid_id identify the winning bid and task, but does not elaborate on formats or constraints. Barely meets baseline for moderate 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?

Description clearly states the verb 'award' and resource 'task', and distinguishes from sibling tools like market_bid, market_post_task. It specifies the payment method and output, making the tool's role unambiguous.

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

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

Description implies usage after bidding, but does not explicitly state when to use versus alternatives like market_bid or market_publish_receipt. No guidance on when not to use or prerequisites.

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 convey behavioral traits. It discloses that bidding is free and winners are paid, but lacks details on bid retraction, multiple bids, or auth requirements. Adds some value beyond schema 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 sentence, concise and front-loaded. It could be slightly expanded to cover required parameters or return behavior, but it is well-structured and to the point.

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

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

With no output schema, the description should hint at return values or confirmation. It does not. There are 7 parameters (4 required) and no mention of what happens after bidding (e.g., confirmation, error cases). Prerequisites like having a USDC wallet are implied but not stated.

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 29% (2 of 7 parameters described). The description adds context only for 'pay_to' (payment wallet). Other parameters like 'pitch', 'eta_hours', 'price_usdc' are not explained, leaving their meaning unclear.

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

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

The description clearly states the action ('Bid'), the resource ('open task'), and adds useful context ('free', payment via x402/USDC on Base). It distinguishes itself from sibling tools like 'market_post_task' (posting tasks) and 'market_award' (awarding tasks).

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 bidding on tasks, but does not explicitly state when to use this tool versus alternatives (e.g., 'market_post_task' for creating tasks, 'market_award' for awarding). No exclusions or prerequisites are mentioned.

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?

Description says 'Browse' implying read-only, but lacks details on behavior, return format, or constraints. No annotations to supplement.

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 with no wasted words, directly stating purpose and filter capability.

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, no annotations, and description omits return structure or any additional behavioral context needed for effective use.

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

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

Schema covers the single 'status' parameter with 100% description coverage; description simply restates the enum values without adding deeper meaning.

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

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

States 'Browse open agent-to-agent tasks' with a specific verb and resource, distinguishing it from siblings like market_award, market_bid, market_post_task.

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 alternatives; no exclusions or when-not statements 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 provided, the description must disclose behavioral traits. It lists actions like 'settle wallet-to-wallet' and 'publish receipts,' which are ambiguous whether this tool performs them or just provides information about them. Since there are no parameters, it likely is a read-only overview, but this is not explicitly stated. No mention of side effects, authentication needs, or data freshness.

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

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

The description front-loads the key concept 'front door' but then becomes a long, run-on list of capabilities. It could be more concise by focusing on what the tool actually provides (overview stats) rather than enumerating all marketplace actions. It is not excessively long, but loses clarity through verbosity.

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

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

Given no output schema, the description should explain the return value. It mentions 'fees, flow, live stats' and 'chain-verified receipts, BotScore passport' but does not specify the format or scope of the overview. For a tool with zero parameters and no output schema, more detail on what the user gets is needed for 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 has no parameters, so schema description coverage is 100%. The description adds no parameter details, which is appropriate. Baseline is 4 for zero-parameter tools as there is nothing to add beyond schema.

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

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

The description clearly identifies the tool as a market overview ('front door') providing fees, flow, and live stats. It distinguishes itself from sibling action-oriented tools (e.g., market_bid, market_post_task) by being an informational entry point. However, the description also lists many actions that are likely performed by other tools, slightly muddying the 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 phrase 'front door' implies using this tool first to get an overview before performing specific actions like bidding or posting. However, there is no explicit guidance on when to use this tool vs. alternatives, nor exclusions for specific contexts. The sibling tools are action-specific, so usage is implied but not directly 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?

No annotations are provided, so the description carries the full burden. It discloses that payment is non-custodial and wallet-to-wallet, but lacks details on post-submission behavior (e.g., visibility, expiration, response format). Behavioral transparency is partial.

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

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

Two concise sentences that front-load the main action. Every sentence adds value, though the second sentence could be structured more clearly as separate workflow steps.

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 8 parameters and no output schema, the description is insufficient. It does not explain the purpose of each parameter, the expected workflow after posting, or what the tool returns. Missing context for effective use.

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

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

Schema description coverage is only 25% (2 of 8 parameters described), and the tool description adds no explanation of parameters. The description does not compensate for the low coverage, leaving the meaning of most parameters unclear.

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

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

The description clearly states the action: 'Post a task to the agent market (free).' It specifies the resource and verb, and distinguishes from sibling tools like market_bid and market_award by focusing on task creation. However, it could better differentiate from market_list_tasks or other posting-related tools.

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

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

The description outlines the basic workflow (agents bid, you award, pay directly) and mentions it's free, but does not explicitly state when to use this tool versus alternatives like market_award or market_bid. Usage guidelines are implied but not explicitly 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?

Description discloses cost ($0.02), verification on Base RPC, and passport update side effect. However, with no annotations, it omits details like idempotency, failure modes, or whether the operation is destructive. Adequate 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?

Two tightly written sentences convey purpose, cost, verification, and side effects without redundancy. Every word adds value.

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

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

Given 7 unannotated parameters, no output schema, and no usage guidelines, the description fails to provide enough context for correct invocation. The purpose is clear, but parameter details and behavioral nuances are lacking.

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 has 7 parameters (4 required) with 0% description coverage. The description only mentions tx_hash verification, leaving payer, payee, amount_usdc, network, task_id, and x_payment unexplained. Agents have insufficient information to populate fields correctly.

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

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

Description clearly states the tool publishes a public receipt for a settled task, using a specific verb ('publish') and resource ('receipt'). It distinguishes from siblings like market_bid or market_list_tasks by focusing on post-settlement receipt creation.

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

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

No explicit guidance on when to use this tool versus alternatives (e.g., market_award, market_list_tasks). The phrase 'for a settled task' implies context but lacks clear conditions 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 are provided, so the description must fully disclose behavior. It mentions liveliness from the npm registry API and a cost, but does not explain payment mechanics, error handling for missing packages, or response format. This leaves gaps in transparency.

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

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

One concise sentence that front-loads cost, resource, timeframes, and source. Every word is informative 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 the core functionality and source but lacks details on response structure, payment flow, and error scenarios. For a paid tool with 3 parameters and no output schema, more completeness is needed.

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% (only 'period' has a description). The description adds context for 'period' by listing the timeframes and hints at 'x_payment' via the cost mention, but 'package' is not elaborated, and 'x_payment' remains unclear. Partial but insufficient compensation 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?

Description clearly states the tool provides download counts for npm packages over specific time periods, mentioning the data source. It is specific about the resource and action but does not explicitly distinguish from siblings like github_trending, though the context suggests it is unique.

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

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

The description implies usage for retrieving npm download stats but provides no explicit guidance on when to use this tool versus alternatives. The mention of a payment cost ('$0.001 via x402') is useful but not a full usage guideline.

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

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

With no annotations, the description carries the full burden. It mentions a cost ($0.01 via x402) and that it is an 'intelligence layer,' hinting at read-only behavior. However, it does not explicitly state whether it modifies data, defines rate limits, or explains authentication requirements. The x_payment parameter suggests payment but is not elaborated.

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, efficiently conveying the tool's purpose, filtering capability, and nature. However, the first sentence is dense and could be slightly clearer on the payment aspect.

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

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

Given the tool's complexity (paid, filtered intelligence, no output schema), the description adequately covers purpose and filtering but lacks details on return format, pagination, rate limits, and full behavioral traits. It is sufficient for basic understanding but incomplete for advanced usage.

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

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

Schema coverage is high (75%) with descriptions for state, months, and sector. The description mentions filtering by sector and US state but does not add new meaning beyond the schema. It does not explain the x_payment parameter. Baseline is 3 due to 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 the tool provides 'scored, agent-actionable signals from US federal spending' with specific attributes (value, urgency, why_it_matters, recommended_action). It distinguishes itself from a 'raw feed' and from sibling tools (like eu_tender_intelligence and gov_contract_intelligence) by explicitly mentioning US federal spending and USAspending.gov.

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 US federal spending opportunities (filterable by sector and US state) but does not explicitly state when to use this tool versus alternatives like gov_contract_intelligence. No exclusions or when-not-to-use guidance is 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 full burden. It discloses the cost model ($0.01 via x402), the data sources, and the filtering by volumes. It does not discuss rate limits or failure modes, but the behavioral traits are reasonably conveyed.

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 long, front-loading the core value proposition, then detailing capabilities and use cases. Every sentence adds value with no redundancy.

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

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

For a tool with moderate complexity and no output schema, the description covers source, data points, search, and use cases. It lacks mention of pagination or response format, but overall is sufficient for agents to understand usage.

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

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

Schema coverage is 100%, so baseline is 3. The description adds context for 'q' and 'sort' (e.g., 'top markets by 24h volume') but does not significantly enhance understanding beyond the schema descriptions for 'top' and '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 the tool returns live real-money prediction-market odds from Polymarket, specifying metrics like implied probabilities and volume. It is distinctly different from sibling tools (e.g., crypto_prices, market_overview) by focusing on prediction markets.

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 (trading, forecasting, news, event-resolution agents) and highlights the tool as a shortcut to avoid direct API integration. It does not explicitly state when not to use it, but the context is clear.

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

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

With no annotations, the description carries full behavioral burden. It discloses that the tool performs a 'live audit' and 'Sends nothing itself,' indicating a read-only operation. It also outlines the output structure. However, missing details about failure modes (e.g., if payment fails) slightly reduce transparency.

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

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

The description is three sentences, front-loaded with key information (premium, purpose, outputs, intended users, non-sending note). Every sentence adds value without redundancy, achieving high conciseness.

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

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

Despite no output schema, the description details all return elements (lead tier, score, recommendation, opener, plan). For a tool with 5 parameters (2 required) and no nested objects, it provides sufficient context. Minor gap: no mention of error handling or prerequisites like brand validity.

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%, providing baseline 3. The description adds interpretative value by explaining how parameters like 'category' and 'seller_service' shape the output angle, e.g., 'shapes the angle.' It also describes the overall purpose of qualifying by AI-visibility gap, enhancing schema meaning.

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 qualifies a sales prospect by AI-visibility gap, returns HOT/WARM/COLD lead tier, score 0-100, AI recommendation, outreach opener, and follow-up plan. It distinguishes from siblings like brand_ai_visibility_check by focusing on sales-specific outputs and intended users (SDR/sales 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 specifies target users ('For SDR/sales agents and agencies selling GEO/SEO/marketing services') and mentions cost, but lacks explicit guidance on when not to use it or alternatives. It does not clarify whether this tool should be chosen over related tools like brand_ai_visibility_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?

Without annotations, the description should cover behavioral traits. It only says 'Free' which implies no cost, but fails to disclose any side effects, auth requirements, or rate limits. The tool is a listing operation, but safety context is minimal.

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

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

The description is extremely concise with a single sentence plus 'Free.' It is front-loaded and contains no verbose or redundant information, efficiently communicating the core function.

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

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

Given the tool has no parameters and no output schema, the description adequately covers what the tool does. It mentions the specific details listed (endpoints, prices, payments), which is sufficient for a simple catalog retrieval tool.

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

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

The input schema has no parameters (0 params, 100% coverage). The description adds value by specifying the content of the listing (endpoints, prices, payments), which contextualizes the output. Baseline for 0 params is 4.

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

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

The description clearly states the tool's purpose: listing endpoints, prices, and payment details of the x402 store. It uses a specific verb ('List') and identifies the resource ('x402 store'), distinguishing it from sibling tools like 'store_samples'.

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

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

The description provides no guidance on when to use this tool versus alternatives. It simply states what it does without mentioning any context or exclusions, leaving the agent to infer usage.

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

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

No annotations are provided, so the description must disclose behavioral traits. It only mentions 'FREE samples' and 'x402 call to upgrade', but does not state if the operation is read-only, has side effects, or requires authentication. The return format is also unspecified.

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

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

The description is a single sentence that front-loads the key benefit ('FREE samples') and is highly efficient with no wasted words.

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

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

For a zero-parameter tool, the description covers the core purpose. However, it lacks details about the output format (e.g., list of product names, sample data) and does not specify whether the tool is idempotent or safe. This is adequate but incomplete given the absence of annotations and output schema.

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

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

The input schema is empty (no parameters), so the schema coverage is trivially 100%. The description adds no param info, which is acceptable since there are none. Baseline 4 for zero 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 provides free samples of every paid product, with a mention of x402 calls for upgrades. This is specific and actionable. However, it does not explicitly differentiate from sibling tools like 'store_catalog', which could also list products without samples.

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 alternatives. The phrase 'Try before you pay' implies a testing scenario, but no explicit when-not or comparison to 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 full burden. It discloses the cost ($0.003 via x402), that it is a feed for polling, and describes what each item includes (chain, contract address, socials, etc.). It does not mention rate limits or destructive potential, but its read-only nature is clear from 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 moderately compact and front-loaded with the cost. Every sentence provides valuable information: cost, purpose, supported chains, item contents, workflow, and data source. It could potentially be tightened but remains efficient.

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

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

Given the lack of an output schema, the description adequately explains the return values by listing what each item includes (chain, contract address, socials, boost amount, Dexscreener link, next_calls). It also covers the tool's purpose and usage pattern. One minor gap is no explicit mention of pagination, but the limit parameter suggests a single-page feed.

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% (chain and limit described, x_payment not described). The description adds default values and explains the chain filter options, but it does not add meaning beyond the schema for the parameters. The x_payment parameter is not explained, though the cost mention may relate to it.

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

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

The description clearly states it is a discovery feed for token launches and boosted tokens across multiple chains. It distinguishes itself from sibling tools by explicitly mentioning next_calls that chain into token_security_check and dex_token_data, showing it is for initial discovery rather than in-depth analysis.

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

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

The description advises to 'Poll this on a loop to find candidates, then verify and price them.' This gives clear usage context and implies a workflow. It does not explicitly state when not to use, but the mention of next_calls and the overall purpose sufficiently differentiates it from 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, description carries full burden. Discloses cost ($0.001), data source (GoPlus Security), supported chains, checks performed (honeypot, tax, etc.), and verdict flags. Adds behavioral context beyond basic purpose.

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?

Description is a single sentence with embedded list of checks, packing much information efficiently. It is front-loaded with cost and purpose. Slightly dense but no redundancy.

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

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

Given no output schema, description mentions verdict (DANGER/HIGH_RISK/CAUTION/OK) and risk flags but lacks full output structure details. Also does not cover error handling or invalid addresses. Adequate but not 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 describes 'chain' and 'address' with coverage 67%. Description adds value by listing supported chains explicitly and confirming address is contract address. However, does not explain 'x_payment' parameter, leaving a gap.

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

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

Description uses specific verb 'check' and resource 'token safety/rug check', explicitly stating it's a pre-trade security tool. It clearly distinguishes from siblings like 'dex_token_data' or 'token_launches_feed' which serve different purposes.

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?

States 'The call every trading and sniping agent should make BEFORE buying a token', giving clear context for when to use. Does not explicitly state when not to use or mention alternatives, but the context is strong.

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

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

No annotations are provided, so the description must fully disclose behavior. It only mentions 'itemized' and 'minimum profitable rate' but lacks details on side effects, authorization needs, rate limits, or output structure.

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 includes cryptic phrasing ('$0.001 via x402') that may confuse rather than inform. While concise, it sacrifices clarity.

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

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

With 9 parameters, no output schema, and no annotations, the description is grossly inadequate. It fails to explain the calculation, return values, or parameter usage.

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

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

Schema description coverage is 0%, and the description adds no meaning beyond the parameter names. It does not explain what each parameter represents or how they affect the calculation.

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 calculates 'itemized trucking cost-per-mile + minimum profitable rate,' which is a specific verb+resource. However, it is somewhat cryptic with '$0.001 via x402' and does not clearly differentiate from the sibling 'truck_load_profit'.

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 alternatives like 'truck_load_profit'. The description does not provide context for appropriate usage 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 are provided, so the description carries full burden. It mentions a cost ($0.001 via x402) which is a behavioral trait, but does not disclose whether the tool is read-only, the nature of x402, or any other side effects. Lacks transparency about required permissions or state changes.

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 (one sentence), but it omits crucial information about parameters and usage. Conciseness at the expense of completeness is not effective; every sentence should earn its place, and here the single sentence does not provide enough utility.

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 8 parameters, no output schema, and zero parameter documentation, the description is severely incomplete. It does not explain input requirements, output format, or how to use results. The mention of x402 is cryptic and lacks explanation.

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

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

Schema description coverage is 0%, meaning no parameter descriptions in the schema. The description does not mention any parameters or their meanings, failing to compensate for the lack of schema documentation. With 8 parameters and only 2 required, the agent has no guidance on how to use them.

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 mentions the tool computes profit, true CPM, break-even rate, and ACCEPT/REJECT verdict for freight load profitability, which is a specific verb+resource. However, it does not clearly explain what the tool does beyond listing outputs, and it lacks differentiation from closely related sibling 'truck_cost_per_mile'.

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

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

No explicit guidance on when to use this tool versus alternatives like 'truck_cost_per_mile'. The context is implied from the name but not stated, and there are no exclusion criteria or alternative mentions.

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 mentions a cost mechanism ('$0.002 via x402'), which adds behavioral context beyond the name. However, with no annotations provided, the description carries the full burden, and it does not disclose other aspects like rate limits, caching, or data freshness beyond mentioning the source.

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, which is concise and front-loaded with the cost. However, it sacrifices clarity on parameter usage. Every sentence should earn its place, and this one is fairly efficient but incomplete.

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 optional parameter, no output schema), the description adequately states what data is returned. However, it does not explain how the 'x_payment' parameter affects usage, which is a gap. The description is minimally complete but not fully informative.

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 one parameter 'x_payment' with 0% schema description coverage. The description only hints at a payment via 'x402' but does not explicitly link it to the parameter or explain its purpose. The description fails to compensate for the lack of schema documentation.

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

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

The description clearly states the tool returns 'latest official US Treasury average interest rates + total public debt' from a specific source. The verb is implicit (get/retrieve), but the resource is well-defined. However, it does not differentiate from siblings, but the sibling list is diverse enough that confusion is unlikely.

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 alternatives (e.g., other finance-related tools). Given the context of many sibling tools, some usage context would help an AI agent decide when to invoke this tool.

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

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

With no annotations provided, the description bears full transparency burden. It discloses cost ($0.003 via x402), supported chains, data source (Blockscout), and spam/unpriced filtering. It does not mention rate limits or prerequisites, but overall it is transparent about behavior.

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

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

The description is well-structured with main action first, then details, use cases, chains, and source. It is not overly verbose but could be slightly more concise; however, it earns its length by packing useful information.

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

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

Given the complexity of output (multiple data fields per token), the description provides a thorough overview of what the tool returns: amounts, prices, values, percentages, concentration, and filtering. Without an output schema, this is complete enough for an agent to understand the output structure.

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

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

Schema description coverage is 67% (chain and wallet have descriptions, x_payment lacks one). The tool description does not add significant meaning beyond the schema; it mentions chain list but that is already in the schema. Baseline score of 3 is appropriate as schema already provides adequate semantics.

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

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

The description clearly states the tool retrieves any wallet's token portfolio with specific data points (amount, live USD price and value, portfolio %, etc.). It distinguishes itself from sibling tools by explicitly targeting 'bagcheck' for copy-trading, whale-watching, risk, and research agents, which is unique among siblings.

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

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

The description implies usage contexts (copy-trading, whale-watching, etc.) but does not explicitly state when not to use this tool or compare it to alternatives like dex_token_data or crypto_prices. There is no guidance on exclusion 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?

No annotations are provided, so the description carries full burden. It discloses the output format (titles, URLs, scores/stars, snippets) and mentions pricing, but does not address rate limits, error handling, or authorization requirements. Behavioral transparency is adequate but 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 concise, using two sentences to convey purpose and use case. It front-loads the key action and includes relevant details without unnecessary verbosity.

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

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

Given the tool's complexity as a multi-source search aggregator, the description covers the input, output format, and sources. It lacks details on ranking logic and error handling, but is fairly complete for a search tool with no output schema.

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 descriptions for 'q', 'limit', and 'sources'. The description adds context by mentioning 'by keyword' for 'q' and listing the sources, but adds no additional meaning for 'x_payment'. The baseline of 3 is appropriate as schema does the heavy lifting.

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 multi-source web and developer search (Hacker News, GitHub, Stack Overflow, Wikipedia) in one call, returning a unified ranked result set. This distinguishes it from sibling tools that target single sources.

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 research/read agents to ground answers, find code, and gather context, but lacks explicit guidance on when to use this tool versus individual source tools or alternatives. No exclusions or when-not-to-use 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?

No annotations present, so description carries full burden. It mentions the tool is a read operation and costs $0.001 via x402, but does not discuss rate limits, failure modes, or authentication requirements.

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

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

Two sentences, front-loaded with purpose and additional context. No unnecessary words, every sentence earns its place.

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

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

Given no output schema and 3 parameters, the description covers basic function and return types but lacks details on error handling, x_payment parameter, and exact output format. Adequate for a simple lookup 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% (q and limit have descriptions). Description does not add extra meaning beyond schema: it does not explain the x_payment parameter or provide additional details on q or limit. 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 it is a Wikipedia knowledge lookup returning article titles, snippets, and canonical URLs. It positions the tool as a cheap fact-grounding read to reduce hallucination, and distinguishes it from the sibling web_search tool.

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

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

Provides clear context: use for cheap fact-grounding on Wikipedia to reduce hallucination. Implies it's for factual queries, but does not explicitly state when not to use it or mention alternatives like web_search.

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