Check x402 endpoints before paying: liveness, price history, farm detection. Plus RU web access.
Get agent balance in minor units (kopecks).
| Name | Required | Description | Default |
|---|---|---|---|
| agent_id | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided; description does not disclose behavioral traits like read-only, auth requirements, or side effects beyond the unit detail.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise (twelve words, one sentence) with no redundant information. Front-loaded purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Adequate for simple read operation but lacks output format details and error conditions. No output schema, so description should specify return structure more explicitly.
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 agent_id with 0% description coverage; tool description adds no meaning to the parameter, leaving agent_id entirely undefined.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the action (get) and resource (agent balance) with specific unit (kopecks). It distinguishes from siblings like topup_balance.
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 for checking balance but provides no explicit when-to-use, when-not, or alternatives. No guidance compared to topup_balance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Check if a domain is available (.com/.ru/.рф). Free, no balance needed.
| Name | Required | Description | Default |
|---|---|---|---|
| domain | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavioral traits. It only states it checks availability and is free, but does not disclose return format, side effects, rate limits, or what happens if the domain is unavailable. This is insufficient for a mutation-free tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that front-loads the main action. Every word serves a purpose 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?
Given the single parameter, no output schema, and no annotations, the description lacks detail on return values (e.g., boolean, response structure). For a check tool, this is insufficient for an AI agent to interpret results correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description adds some meaning by specifying allowed TLDs (.com/.ru/.рф). However, it does not clarify input format (e.g., with or without TLD, example) beyond that. Baseline 3 is appropriate as it partially compensates but not fully.
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 'Check' and the resource 'domain', with specific TLDs (.com/.ru/.рф). It differentiates itself from siblings like register_ru_domain (registration) and check_balance (balance inquiry).
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 'Free, no balance needed,' which implies it can be used without cost, suggesting it's safe to use anytime. However, it does not explicitly state when not to use it or compare to alternatives like register_ru_domain for registration.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Russia specialization of fetch_web (country='ru'): content of any Russian site/API through a Russian IP (Wildberries, Ozon, Yandex Market, hh.ru, Avito). residential=true for hard antibot.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | ||
| agent_id | Yes | ||
| residential | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description must carry behavioral information. It explains the residential flag for hard antibot but does not describe return format, error handling, or how it differs from fetch_web in practice. Some expected behavior is implicit but not fully disclosed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, using one sentence to convey the purpose and the key flag. No unnecessary wording or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the sibling tools, the context is fairly clear: it is the Russian-specific fetch tool. However, it does not mention edge cases like non-Russian sites or fallback behavior, but the specialization is sufficient for most use cases.
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 no parameter descriptions (0% coverage). The description only explains residential=true; url and agent_id are left undefined. Since the schema does not clarify these, the description fails to compensate for the missing 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 the tool fetches content from Russian sites through a Russian IP, with a specific use case for hard antibot via residential=true. It distinguishes itself from sibling tools like fetch_web (general) and get_ru_proxy (proxy provisioning).
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 Russian sites and mentions when residential=true is needed, but it does not explicitly state when to choose this over fetch_web or get_ru_proxy. Still, the specialization is evident from the country parameter and Russian IP mention.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Give a URL of ANY website or API — get its content (HTML/JSON) fetched through an IP of the chosen country (country='ru','us','de','gb',...). Flagship tool — URL in, content out, no proxy setup. Specialty: country='ru' unlocks Russia-only sites that block foreign IPs (Wildberries, Ozon, Yandex Market, hh.ru, Avito). Set residential=true for sites that block datacenter IPs. Set render=true to render JS in a real headless Chromium (SPA / JS-heavy / JS-challenge sites). Charged from agent balance; returns payment_required if insufficient (then topup_balance and retry).
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | ||
| render | No | ||
| country | No | ru | |
| agent_id | Yes | ||
| residential | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden, and it discloses key behavioral traits: it is charged from the agent balance, returns payment_required on insufficient funds, and suggests a recovery path. It also explains country-based IP behavior and the effect of residential/render flags. It does not mention other failure modes or rate limits, but the most important side effect, billing, is clearly stated.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact yet information-dense. Core functionality is front-loaded, followed by specialty conditions, flag guidance, and billing behavior. Every sentence contributes useful decision-making or invocation detail without fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a paid fetching tool with no annotations and no output schema, the description covers the critical invocation details: target URL, country selection, residential/render flags, and billing failure handling. It does not specify the exact success response structure or non-payment errors, but these are not essential for an agent to select and call the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description must compensate, and it does for most parameters: url, country (with examples and the Russia-only unlock behavior), residential, and render. The only gap is agent_id, a required parameter whose purpose is not explained, though its role is somewhat inferable from the billing context.
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 core function: give any URL and receive HTML/JSON fetched through a chosen country IP. It also highlights the flagship, general-purpose nature and country-specific specialty, which helps distinguish it from sibling proxy tools. However, it does not explicitly differentiate itself from the similarly named fetch_ru sibling, so it falls just short of a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear decision rules: set residential=true for sites blocking datacenter IPs, set render=true for JS-heavy or SPA sites, and use topup_balance and retry after payment_required. It does not explicitly name alternatives or say when not to use this tool, but the parameter guidance is actionable and context-rich.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Get a Russian IP proxy to access RU-only sites (Wildberries, Ozon, Yandex, hh.ru, Avito) that block foreign IPs. Charged from agent balance; returns payment_required if insufficient (then call topup_balance and retry). Idempotent per agent.
| Name | Required | Description | Default |
|---|---|---|---|
| count | No | ||
| agent_id | Yes | ||
| period_days | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses key behavioral traits: it charges from the agent balance, can return a payment_required error, and is idempotent per agent. Since no annotations are provided, this description carries the full burden and covers the essential side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is exceptionally concise, using three sentences to convey purpose, pricing, error handling, and idempotency. It contains no redundant words or unnecessary 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?
The description covers the tool's purpose and error handling, but omits what the actual return value looks like (e.g., proxy address, credentials) and the meaning of `count` and `period_days`. Given there is no output schema, these gaps are noticeable and could hinder correct usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The parameters `count` and `period_days` have defaults but their meaning is entirely absent. The description does not explain what these parameters do, leaving the agent to guess (e.g., number of proxies, lease duration). Only `agent_id` is inferable from the description text.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool obtains a Russian IP proxy to access RU-only sites, listing concrete examples (Wildberries, Ozon, Yandex, hh.ru, Avito). It distinguishes itself from sibling tools like fetch_ru or fetch_web by focusing on the proxy acquisition rather than direct fetching.
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 specifies the use case (accessing RU-only sites) and provides a conditional instruction: if payment_required is returned, call topup_balance and retry. It does not explicitly mention when not to use it, but the context is clear enough.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Register a .ru/.рф domain (secondary service). Charged from balance.
| Name | Required | Description | Default |
|---|---|---|---|
| domain | Yes | ||
| agent_id | Yes | ||
| idempotency_key | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided. The description discloses that the service is charged from balance, which is a key behavioral trait. However, it lacks details on destructive effects, rate limits, or responses.
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 front-loading the action and domain. It is efficient but omits important details that would justify slightly more length.
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 output schema, zero param descriptions, and limited context signals, the description fails to provide enough information about prerequisites, response format, or idempotency behavior, making it incomplete for the 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?
With 0% schema coverage and no parameter descriptions in the tool definition, the description adds no meaning beyond the schema. Parameters like agent_id and idempotency_key are unexplained.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool registers a .ru/.рф domain and mentions it is a secondary service charged from balance. It implies the specific TLDs and financial aspect, but does not explicitly differentiate from sibling tools like check_domain or fetch_ru.
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 it's a secondary service, but gives no explicit guidance on when to use this tool versus siblings (e.g., check_domain for checking availability) or prerequisites like having sufficient balance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Run agent code (python / javascript / bash) in an isolated sandbox (no network, CPU/RAM/time limits) and get stdout/stderr/exit_code back. Charged from agent balance; returns payment_required if insufficient (then topup_balance and retry).
| Name | Required | Description | Default |
|---|---|---|---|
| code | No | ||
| timeout | No | ||
| agent_id | Yes | ||
| language | No | python |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Since no annotations are provided, the description carries full burden. It discloses that execution happens in an isolated sandbox with no network, CPU/RAM/time limits, and that charges apply. This gives the agent a good understanding of important behavioral traits such as resource constraints and billing.
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, with the first sentence clearly stating the action and output, and the second addressing billing. Every word adds value. It is front-loaded with the core functionality.
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 (4 parameters, no output schema, no annotations), the description covers essential aspects: purpose, sandbox constraints, return values, and billing. It lacks details on parameter formats or default values, but the overall information is sufficient for using the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema coverage is 0% (no parameter descriptions), so the description must add meaning. It mentions supported languages ('python / javascript / bash'), which relates to the 'language' parameter, and implies that 'code' is executed and 'timeout' affects runtime. However, it does not explicitly describe each parameter's format or constraints, leaving some gaps.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states what the tool does: run agent code in a sandboxed environment. It specifies supported languages (python, javascript, bash) and what is returned (stdout, stderr, exit_code). This distinguishes it from sibling tools like fetch_web or check_balance, which have 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?
The description explains that running code costs agent balance and returns 'payment_required' if insufficient, with a suggestion to top up and retry. This provides clear context for when to use the tool and what to do if balance is low. It does not explicitly state scenarios where the tool should not be used, but the context implies it's for executing code.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Help improve this service: tell us what you need. question is one of: need_data (which Russian data sources you need), why_no_pay (if you didn't pay: price/payment_friction/ just_exploring/not_now), missing_service (what's missing), country_need (which country IP). Short answer.
| Name | Required | Description | Default |
|---|---|---|---|
| answer | Yes | ||
| agent_id | Yes | ||
| question | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden. It states that the answer should be 'short,' but does not disclose behavioral traits such as whether the tool is read-only or destructive, side effects, or authentication requirements. This is a significant gap for a submission tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: two sentences with no unnecessary words. It front-loads the purpose and then lists the specific options efficiently.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple 3-parameter tool with no output schema and no annotations, the description adequately explains the question parameter and answer style. However, it omits context like what happens after submission (e.g., confirmation, storage) and any prerequisites. It is minimally 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?
With 0% schema description coverage, the description compensates partially. It explains the 'question' parameter with valid values and their meanings, and hints that 'answer' should be short. However, it does not explain 'agent_id', leaving one parameter completely undocumented.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Help improve this service: tell us what you need.' It explicitly lists the survey questions, making the action (submitting feedback) unambiguous. The sibling tools are unrelated (check_balance, fetch_web, etc.), so there is no confusion.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context by enumerating the valid question options (need_data, why_no_pay, etc.), which guides when to use each. It does not explicitly state when not to use the tool or compare to alternatives, but the sibling tools serve different purposes, making guidance sufficient.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Top up agent balance. rail: usdc (x402) or rub (YooKassa). Returns pay_url to complete payment.
| Name | Required | Description | Default |
|---|---|---|---|
| rail | No | usdc | |
| No | agent@domains-for-ai.app | ||
| agent_id | Yes | ||
| amount_minor | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. Description discloses return value (pay_url) and payment rails, but lacks details on authorization, side effects, or failure modes.
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, front-loaded with the core action and then key details. 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?
Adequate for a simple operation, explains purpose and return value, but lacks parameter details for email and amount_minor, 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 coverage is 0%. Description only adds meaning to 'rail' (usdc or rub), ignoring email, agent_id, and amount_minor 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?
Description clearly states 'Top up agent balance' using a specific verb and resource. It distinguishes from sibling tools like check_balance which is read-only.
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, no exclusions or prerequisites mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Find an x402 service by task and price across the whole catalog (27k+ listings). The x402 ecosystem has no unified search across facilitators — this is that discovery layer.
| Name | Required | Description | Default |
|---|---|---|---|
| q | No | ||
| limit | No | ||
| agent_id | Yes | ||
| max_price_usd | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavior disclosure. It mentions catalog size and that it spans facilitators, which is useful, but it doesn't disclose search semantics (e.g., partial/fuzzy matching), result ordering, pagination behavior, or whether the agent_id parameter is required for authentication vs filtering. The 'whole catalog' claim is a behavioral trait 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, both purposeful: the first states the core function and scope, the second provides ecosystem context. The information is front-loaded, and there is no filler. Slightly more detail on agent_id could be added, but as written it is tight and readable.
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 0% schema coverage, no annotations, no output schema, and four parameters including a required one, the description is far from complete. It explains the search scope but not how to form a valid request, what the response looks like, or what agent_id is for. An agent would need to guess at parameter semantics and result behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate for the four undocumented parameters. It explains q conceptually ('task') and max_price_usd ('price') via the phrase 'by task and price', but it leaves agent_id completely unexplained (despite being the only required parameter) and doesn't clarify limit semantics. This is a material gap for a tool whose schema offers zero descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb ('Find') and resource ('an x402 service by task and price across the whole catalog'), and differentiates itself from siblings by noting it is a discovery layer over the entire x402 ecosystem with 27k+ listings. It doesn't explicitly name alternatives, but 'no unified search across facilitators' conveys its unique role 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 when to use it: when searching for a service by task and price, and it positions itself as the cross-facilitator discovery layer. However, it doesn't explicitly say when not to use it or point to alternatives (e.g., x402_service_check for verifying a specific service). No exclusions or routing conditions are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Reputation of an x402 payment recipient: weekly revenue, unique buyers, average ticket, what they sell, and our organic-vs-farm verdict. Few unique buyers against sizeable revenue is the signature of volume washing — six addresses with exactly 5 buyers each accounted for 45% of the top-100 revenue in our last measurement.
| Name | Required | Description | Default |
|---|---|---|---|
| address | Yes | ||
| agent_id | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description implies a read-only lookup of reputation data, but it does not explicitly state that the tool has no side effects. The absence of any warning about modifications or sensitive data suggests it is safe, but this is inferred rather than declared.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is relatively brief and to the point, covering the main purpose and a relevant insight about volume washing. It avoids unnecessary fluff, though the additional context about specific addresses could be seen as slightly verbose. Overall, it is well-structured and efficiently communicates the core functionality.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description lacks an output schema and does not mention expected return format or any prerequisites. It gives a high-level overview but omits details about how the reputation is calculated or what exactly the verdict means. While not critical for basic use, the absence of output structure and additional context leaves gaps for an agent expecting precise data.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The parameters 'address' and 'agent_id' are only listed in the schema without any descriptions. The tool description mentions 'x402 payment recipient', which implies 'address' is the recipient's wallet, but 'agent_id' remains unexplained. The schema coverage is 0%, so the description does not compensate for the lack of parameter details.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool provides reputation information for an x402 payment recipient, listing specific data points like weekly revenue, unique buyers, average ticket, and a verdict. It distinguishes itself from sibling tools by focusing on reputation metrics rather than balances or domain checks, though it does not explicitly name a verb like 'get' or 'retrieve'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not provide explicit guidance on when to use this tool versus alternatives. It mentions a heuristic for detecting volume washing, but this is more informative than actionable. No direct comparison to sibling tools or clear conditions for selection are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Check ANY x402 endpoint BEFORE paying it. Payments in x402 are irreversible — there is no dispute button — and by our measurement 1 in 6 listed services is dead while 76% of Base volume comes from wash-trading farms. Returns: liveness verdict from our probes, current and historical price, the receiving address, and an organic-vs-farm verdict on that seller. Built on our own daily snapshots since 2026-06-16; no public source has this history.
| Name | Required | Description | Default |
|---|---|---|---|
| agent_id | Yes | ||
| resource | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the transparency burden and mostly meets it by disclosing return fields and data provenance (own daily snapshots since 2026-06-16, no public source). It does not explicitly state that the check is read-only or cannot trigger a payment, though 'BEFORE paying it' strongly implies it.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the action, uses the middle sentences to justify the tool's necessity, and ends with a compact returns list and provenance. Every sentence contributes either behavioral or usage information, 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 decision context, return contents, and data provenance, which is strong for a moderate-complexity tool. However, with no output schema and no parameter descriptions, the missing agent_id/resource mapping leaves a critical gap for constructing a correct call.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description never maps the two required parameters. It mentions 'endpoint,' 'seller,' and 'receiving address,' but does not clarify whether resource is the endpoint and agent_id is the seller, leaving an agent unable to reliably construct arguments.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The first sentence states a specific verb-resource pair ('Check ANY x402 endpoint') and adds a clear operational trigger ('BEFORE paying it'). The returns list—liveness, price, receiving address, and organic-vs-farm verdict—makes the tool's scope concrete and distinguishes it from generic checks like check_balance and check_domain.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives an explicit when-to-use instruction: run this check before paying any x402 endpoint, supported by concrete rationale (irreversible payments, 1-in-6 dead services, wash-trading farms). It does not name sibling alternatives such as x402_seller_reputation or state when not to use the tool, so it lacks full when/when-not guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
x402_discoveryx402_seller_reputationx402_service_checkfetch_web1 field changedInput schema / properties / renderAdded value: +{
+ "default": false,
+ "title": "Render",
+ "type": "boolean"
+}run_codesubmit_surveycheck_balancecheck_domainfetch_rufetch_webget_ru_proxyregister_ru_domaintopup_balanceClaiming proves that you control a remote MCP connector. It does not move, proxy, or interrupt the server.
Open the connector listing, choose Claim ownership, and sign in to Glama.
Complete one verification method:
GitHub identity — fastest for official registry listings. For a namespace such as io.github.alice/server, link the matching GitHub user, then choose Claim with GitHub. An organization namespace such as io.github.acme/server also needs that organization to have installed the Glama AI GitHub App and approved its permissions, because GitHub discloses organization membership only to apps it has installed. Use HTTP or DNS when it has not.
HTTP challenge — works when you can deploy a public file. Generate a token, publish the exact JSON Glama shows at /.well-known/glama.json on the same origin as the connector, then choose Check HTTP challenge.
DNS challenge — works when you control DNS but cannot change the server. Generate a token, create the exact TXT record Glama shows, wait for it to propagate, then choose Check DNS challenge.
After verification, Glama sends a confirmation email and gives you access to listing details, thumbnails, health checks, and analytics. Keep the HTTP file or DNS record in place: Glama periodically checks it and ownership remains verified while the token is discoverable.
The HTTP ownership file has this structure:
{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"claim": "glama_claim_..."
}Claim tokens are opaque, stable, and bound to the signed-in Glama account. They contain no email address or other personal information. If Glama can no longer discover a verified HTTP or DNS token, it starts a seven-day grace period before removing claim-based access. Restore the same token during that period to keep ownership verified. Never publish an email address, Glama session token, GitHub token, or connector credential as ownership proof.
If verification fails, confirm that you copied the current token exactly. The HTTP file must be public, return valid JSON with a successful HTTP response, and stay on the connector's origin. DNS changes may need more time to propagate. A claim cannot transfer to a different origin or hostname: if the connector target changes, Glama starts the grace period and the new target must be claimed separately after the previous claim is released.
For a connector linked to the official MCP Registry, registry updates continue to replace its name, description, and URL by default. After claiming, open Manage connector and enable Use Glama listing details as the source of truth if edits made on Glama should be preserved. Categories and thumbnails are always managed on Glama; registry linkage and technical connection settings continue to sync.
Control your server's listing on Glama, including description and metadata
Access analytics and receive server usage reports
Get monitoring and health status updates for your server
Feature your server to boost visibility and reach more users
To improve your MCP server's ranking:
Claim ownership of the server listing
Complete the server profile with an accurate description and thumbnail
Provide a test profile so Glama can connect to and evaluate the server
Keep tool definitions clear and complete to earn a high Tool Definition Quality Score (TDQS)
Route real usage through the Glama Gateway; more recorded successful server uses also improve the ranking
For users:
Full audit trail – every tool call is logged with inputs and outputs for compliance and debugging
Granular tool control – enable or disable individual tools per connector to limit what your AI agents can do
Centralized credential management – store and rotate API keys and OAuth tokens in one place
Change alerts – get notified when a connector changes its schema, adds or removes tools, or updates tool definitions, so nothing breaks silently
For server owners:
Proven adoption – public usage metrics on your listing show real-world traction and build trust with prospective users
Tool-level analytics – see which tools are being used most, helping you prioritize development and documentation
Direct user feedback – users can report issues and suggest improvements through the listing, giving you a channel you would not have otherwise
The connector status is unhealthy when Glama is unable to successfully connect to the server. This can happen for several reasons:
The server is experiencing an outage
The URL of the server is wrong
Credentials required to access the server are missing or invalid
If you are the owner of this MCP connector and would like to make modifications to the listing, including providing test credentials for accessing the server, please contact support@glama.ai.
No comments yet. Be the first to start the discussion!
Live x402 endpoint trust/diligence check before you pay it. $0.02/call via x402.
Measured x402 ecosystem data, facilitator reliability, and live endpoint checks.
We buy from x402 endpoints with real USDC and publish delivery outcomes. Check before you spend.
Find and vet x402 payment APIs before your agent pays one: uptime, price, on-chain volume.
Add one secure layer between your agents and this server.
Tools are largely distinct, but fetch_ru and fetch_web overlap as the former is a specialization of the latter; descriptions clarify the difference, so agents should select correctly. Other tools (check_domain vs register_ru_domain, x402_*) have clear boundaries.
Most tools follow a verb_noun snake_case pattern (check_balance, fetch_web, topup_balance), but the x402_* group uses a domain prefix rather than a verb. This is consistent within its subgroup but deviates from the overall pattern.
12 tools cover a broad but well-scoped set of capabilities (fetching, RU-specific access, domains, code execution, balance, x402 services). Each tool has a distinct role and the count is within the ideal range.
The tool surface covers the main workflows: fetching with country/JS options, RU proxy/domain services, balance management, code execution, and x402 discovery/verification. Minor gaps like domain deletion or a generic service list are not critical for the stated purpose.
