Agents Get Paid Kit — x402 MCP + Unlock ($49)

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

With no annotations, the description carries the transparency burden. It discloses the financial nature, exact cost, network, and important pricing exceptions. The warning 'Not auto-income' is particularly useful because it prevents an agent from misrepresenting the kit as a source of automatic income. It stops short of describing post-payment effects or irreversibility, but the core monetary behavior is explicit.

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

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

Three short sentences, each earning its place: the action/price, the price parity confirmation, and the critical exceptions. It is front-loaded with the most important information and contains no filler.

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

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

The description covers price, network, and pricing exclusions well, and the schema fills in some parameter semantics. However, there is no mention of the return value/receipt, no clear required parameter guidance despite required being zero, and no explicit instruction to obtain a quoteId from get_quote before calling. These gaps make it adequate but not fully complete.

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

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

Only half of the parameters have schema descriptions, and the tool description provides no additional meaning for any parameter. It never clarifies what 'note' or 'tenantId' are for, nor does it explain the relationship between the 49 USDC price and the quoteId. The schema's mention of quoteId and agentName helps, but the undocumented parameters remain ambiguous.

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

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

The description states a specific action ('Pay 49 USDC on Base') against a specific resource ('the Agents Get Paid Kit'), with an exact price and network. This clearly differentiates it from siblings like get_quote and get_spend_status, which are quote and status tools.

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

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

The description gives clear exclusion cases: 'Not auto-income' and 'SPIRAL / in-fleet = $0 (do not charge)'. However, it does not explicitly state when to use this tool versus siblings such as get_quote or get_spend_status, beyond implying that a paid kit purchase is the goal.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It does disclose that the quote is free, subject to caps/AUP, and not auto-income, which is some useful context. However, it does not explain side effects, whether human verification is required, what happens after the quote, rate limits, or the meaning of 'SPIRAL $0' and 'Humans #pay.'

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, which is good for brevity, but it sacrifices clarity with hashtag-style fragments like '#pay' and 'SPIRAL $0.' The front-loaded 'Free quote, then buy_kit' is useful, but the remaining phrases do not clearly earn their place because their meaning is ambiguous.

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 annotations and no output schema, the description should fully explain the tool's behavior and constraints to support correct invocation and selection. It leaves many gaps: what the quote contains, how 'kind' affects the request, what 'Caps + AUP' concretely mean, and why 'Not auto-income' matters. An agent would likely need external knowledge to use this tool confidently.

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

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

Schema coverage is 100% for the single optional parameter 'kind,' so the schema already documents the captcha kinds well. The description adds no real parameter-level meaning beyond the schema; 'Humans #pay' may allude to captcha or human verification, but this is too vague to count as added semantic value.

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

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

The phrase 'Free quote, then buy_kit' indicates the tool provides a quote before a purchase and references a 49 USDC payment on Base x402, giving some sense of purpose. However, it never explicitly states what the quote is for, what it returns, or how it relates to the sibling tools beyond buy_kit. The cryptic slogans like 'Humans #pay' and 'SPIRAL $0' obscure rather than clarify.

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 only usage signal is the sequence 'then buy_kit,' which implies get_quote should be called before buying, but there is no explicit statement of when to use this tool versus alternatives. No exclusions, prerequisites, or conditions are given. Mentions of 'Caps + AUP' and 'Not auto-income' hint at constraints but do not provide actionable guidance.

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

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

With no annotations, the description carries the full behavioral disclosure burden. It adds useful context beyond the name: data is 'in-memory' (not persisted), the tool is an 'MVP' (likely early-stage), and it is 'Free' (no billing impact). It does not explicitly say it is read-only, but 'Show' strongly implies no mutation.

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 the main action front-loaded and only two short clauses. Every word adds value: 'in-memory' clarifies behavior, 'for this isolate' defines scope, 'MVP' sets expectations, and 'Free' is a key operational trait.

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

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

For a simple one-optional-parameter tool, the description covers the core purpose and a few behavioral caveats. However, there is no output schema and the description does not describe what the response will contain (e.g., values, units, format), and 'this isolate' is not fully explained.

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

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

The single parameter tenantId is fully described in the input schema with its optionality and default value, so schema coverage is 100%. The tool description does not add extra meaning about this parameter, but the baseline of 3 applies because the schema already documents it adequately.

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

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

The description clearly states the tool's function with a specific verb ('Show') and resource ('in-memory spend / rate usage for this isolate'), and the 'Free' note adds a distinguishing characteristic. It is easily differentiated from the unrelated sibling tools, none of which concern spend or rate monitoring.

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

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

The description implies when to use this tool: when you need to check current spend or rate usage, and the 'Free' note suggests it is safe/cost-free to call. However, it does not explicitly state when not to use it or mention any alternative tools, though the siblings appear unrelated.

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

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

With no annotations, the description carries the full burden of behavioral disclosure. It does disclose a key side effect: the report is logged server-side. 'Free' also adds cost-related transparency. However, it does not explain whether authentication is required, whether the report is acted upon, how long the log persists, or what the response looks like.

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

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

The description is very short and front-loaded with the main action. Every phrase adds meaning: 'Report' gives the operation, 'product or policy issue' defines scope, 'logged server-side' reveals persistence, and 'Free' communicates cost. There is no repetition 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?

The tool has three parameters, no annotations, and no output schema, yet the description explains none of the parameters and gives no usage context or return expectations. It is minimally adequate for identifying the tool's purpose but incomplete for confident invocation.

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

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

The schema has 0% description coverage, so the prose description must compensate by explaining the parameters. It does not mention summary, detail, or toolName at all. An agent has no guidance about what to put in the required summary field or how to use the optional detail and toolName fields.

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

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

The description states a clear action and object: report a product or policy issue. It is specific enough to distinguish the tool from siblings like buy_kit or solve_captcha, though it does not explicitly contrast itself with any sibling. The phrase 'logged server-side' adds a small amount of scope but does not fully define what qualifies as an issue.

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

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

There is no guidance about when to use this tool versus the alternatives, no exclusions, and no mention of prerequisites or expected context. The word 'Free' is a cost signal, not a usage guideline. An agent is left to infer that the tool should be used when a user reports a problem.

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

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

With no annotations, the description carries the full burden of behavioral disclosure. It usefully reveals that the tool is paid, subject to spend caps and AUP, restricted to allowlisted purposes, and refuses certain abusive uses. However, it does not mention whether the solve is synchronous or asynchronous, what the response contains, or other side effects beyond the cost.

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

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

The description is compact and front-loaded, beginning with the most important facts: it is paid and solves CAPTCHAs. Every clause adds value, and there is no redundant filler 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?

For a tool with 7 parameters, 3 required, no output schema, and significant behavioral context (payment, restrictions), the description is too thin. It does not explain what inputs are required, how the CAPTCHA is submitted, what the tool returns, or how spend caps are enforced. An agent would need to inspect the schema or rely on trial and error.

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 43%, and the description does not compensate for the undocumented parameters like websiteKey, websiteURL, imageBase64, or tenantId. It adds some semantic color around 'purpose' via the allowlist/refusal language, but it fails to explain how the required CAPTCHA inputs map to the solve request.

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 paid x402 USDC CAPTCHA solve service for agents. It uses a specific resource (CAPTCHA) and implies the solve action, which distinguishes it from sibling tools like buy_kit, get_quote, or unlock_page. The phrase 'for agents mid-task' further narrows its purpose.

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

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

The description gives clear usage context: it is intended for agents mid-task and is a paid service. It also states explicit exclusions by refusing login/signup/payment abuse and mentions allowlisted purposes, though it does not name alternative tools or provide when-not-to-use guidance relative to siblings.

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

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

With no annotations, the description carries the burden and meaningfully discloses that this is a paid operation using USDC, subject to spend caps and an AUP. The HTTP 402 mention also hints at an important failure/payment-required signal. It could add failure modes like insufficient funds or blocked pages, but the core behavioral traits are visible.

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

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

The description is appropriately terse and front-loaded with the most important fact: 'Paid x402 USDC web-unlock'. Each fragment adds distinct value—payment, use case, constraints, and protocol. The final fragment is cryptic but not redundant.

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

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

There is no output schema and no annotations, so the description must cover return behavior and side effects itself. It covers cost and AUP but not what the tool returns, how errors are surfaced, the meaning of tenantId, or how to check spend/quote via sibling tools. An agent can start a call but cannot fully predict the outcome.

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 documents purpose's allowed values but only 33% of properties have descriptions; url and tenantId are otherwise unexplained. The description only loosely maps to parameters ('Fetch pages' implies url, 'research/indexing' implies purpose) and does not clarify tenantId or how to choose purpose values beyond the schema's own list.

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

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

The description states a specific operation ('web-unlock for agents') and resource ('Fetch pages') with a clear payment mechanism ('x402 USDC'). The 'HTTP 402 payment-required MCP' phrasing helps distinguish it from siblings like solve_captcha or buy_kit, though it does not name the alternative explicitly.

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

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

It identifies appropriate contexts ('legitimate research/indexing') and constraints ('Spend caps + AUP'), giving an agent a sense of when the tool is intended to be used. However, it does not explain when to prefer get_quote, get_spend_status, or buy_kit, nor any preconditions like sufficient balance.

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