Official evidence for OFAC, FDA, USAspending, Federal Register, counterparty and batch checks.
Average 3.1/5 across 10 of 10 tools scored.
Several tools have heavily overlapping roles: 'quote' and 'machine_quote' both appear to offer free preflight quotes and x402 pricing, while 'coverage' and 'coverage_status' both relate to observation/watch coverage. 'catalog' and 'machine_sources' also blur the line between listing products and listing source adapters. An agent would likely struggle to pick the correct tool without deeper context.
All tool names use lowercase snake_case and mostly follow a noun/status pattern. The 'machine_' prefix creates a recognizable subgroup, and quote-related names are clearly grouped. Minor inconsistency exists because some names are action-oriented (batch_quote, catalog) while others are status-oriented (coverage_status, discovery_status), but the overall style is coherent.
Ten tools is a reasonable, well-scoped count for a specialized evidence/quote/status service. Each tool addresses a distinct operational concern: quotes, coverage, status, catalog, sources, and telemetry. The count does not feel inflated or too thin.
The server covers preflight quoting, coverage checks, catalog listing, status, sources, and sales telemetry, but conspicuously lacks any tool for purchasing, paying, or retrieving completed evidence/proofs. The quote descriptions repeatedly reference x402 payment and payable batches, yet there is no obvious order or fulfillment endpoint. This creates a dead end for agents trying to complete a transaction.
batch_quoteCInspectFree preflight for 2-10 quick checks; batch is payable only when every item is conclusive
| Name | Required | Description | Default |
|---|---|---|---|
| items | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden and does contribute one meaningful behavioral trait: the free preflight versus payable batch distinction, including the 'only when every item is conclusive' condition. However, it does not disclose what the tool returns, whether it has side effects, auth requirements, or what happens when items are inconclusive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single compact sentence with no filler, and the most distinctive constraints—size and payment condition—are front-loaded. It loses a point because the wording is slightly awkward and relies on jargon like 'preflight' without elaboration, but structurally it 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?
Given no annotations, no output schema, 0% parameter coverage, and nine sibling tools, a brief pricing statement is insufficient. An agent needs to know what operation is performed, what the response contains, and how this tool differs from quote and counterparty_quote; the description omits all of that.
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 undocumented items parameter, but it mentions nothing about items, sources, from/to, or terms. The input schema alone provides the parameter structure, and the description adds no meaning to help an agent construct a valid 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 conveys a batch preflight service constrained to 2-10 items, but it never explicitly states the core operation such as 'get a price quote for a batch' or 'run batch checks.' It is distinguishable from siblings only by the batch-size and payment condition, not by a clear verb and resource.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'for 2-10 quick checks' provides an implied usage condition, but the description does not say when to prefer batch_quote over quote, counterparty_quote, or machine_quote. No alternatives or exclusions are named, so an agent must infer selection from the batch-size hint alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
catalogAInspectList free preflight and paid Federal Register evidence products
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden. The verb 'List' conveys a read-only retrieval operation, but the description does not disclose output format, pagination, or whether any costs/limits apply to the paid products. Basic behavior is clear, details are not.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single compact sentence that states the operation and scope without wasted words. The key qualifiers ('free preflight and paid') are included.
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 an empty-parameter list tool, the description is largely complete: it names the subject and scope. However, with no output schema, it would be stronger if it mentioned the shape of the returned product list or any pagination.
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 zero parameters and 100% schema coverage, so there are no parameter semantics to document. The description adds useful context by defining what the catalog contains, meeting the baseline for a no-parameter tool.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'List' with a precise resource: free preflight and paid Federal Register evidence products. This distinguishes the catalog tool from sibling quote/status tools, 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?
The phrase 'List ... products' implies the tool is for browsing available evidence products, but it does not explicitly state when to use it over alternatives or mention any exclusions. Usage context is left to inference.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
counterparty_quoteCInspectFree preflight for a signed counterparty dossier across OFAC, FDA, USAspending, and Federal Register
| Name | Required | Description | Default |
|---|---|---|---|
| to | Yes | ||
| from | Yes | ||
| term | No | ||
| entity | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden for behavioral disclosure. It adds some context by saying the operation is 'free' and a 'preflight,' implying a non-final or non-destructive check, but it does not disclose side effects, authentication needs, rate limits, required dossier state, or what action is actually performed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no filler, and the key qualifiers ('Free preflight', 'signed counterparty dossier', and the target sources) are placed early. It is concise, though some terminology is jargon-heavy and would benefit from clarification.
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 four parameters with zero schema descriptions, no annotations, no output schema, and no usage guidance, this one-line description is far from sufficient for an agent to reliably select and invoke the tool. It omits parameter meanings, return value shape, prerequisites, and distinctions from sibling quote tools.
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 does not explain any of the four parameters (entity, from, to, term). While 'entity' might be inferred as the counterparty dossier, the date-range parameters and optional term are completely unexplained, leaving the agent without the information needed to construct a correct call.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description communicates a clear resource ('signed counterparty dossier') and scope (OFAC, FDA, USAspending, Federal Register), and 'preflight' implies an assessment or preliminary check. It does not use an explicit verb like 'run' or 'get,' and sibling differentiation is only implicit through the word 'counterparty' rather than stated directly.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'for a signed counterparty dossier' implies a prerequisite and gives context for when the tool applies, and the listed sources clarify the use case. However, it does not name alternative tools such as quote, machine_quote, or batch_quote, nor does it state when not to use this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
coverageBInspectCheck observation coverage before buying a NOT_OBSERVED proof
| Name | Required | Description | Default |
|---|---|---|---|
| to | Yes | ||
| from | Yes |
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. The verb 'Check' implies a read-only operation, but the description does not explicitly state that there are no side effects, what data is examined, or what the response represents. This is a significant gap for a tool with no annotation support.
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 is direct and front-loaded with the core action. Every word contributes to the purpose, and there is no fluff or redundant 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?
With no output schema and no annotations, the description must explain enough for correct invocation and interpretation. It does not describe what output to expect, what 'coverage' means in quantitative terms, or how to use the parameters. The sibling ambiguity with 'coverage_status' further reduces 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?
Schema description coverage is 0%, and the description does not explain the 'from' and 'to' parameters. The names suggest a range, but there is no mention of expected format (dates, timestamps, coordinates) or how they relate to observation coverage. The description fails to compensate for the schema gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific action ('Check observation coverage') and the context (before buying a NOT_OBSERVED proof). It is not a tautology of the name and implies a verification workflow. However, it does not explicitly differentiate from the sibling 'coverage_status', so some ambiguity remains.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives a clear trigger: use this before purchasing a NOT_OBSERVED proof. This communicates when the tool is appropriate. It does not provide exclusions or mention alternative tools, but the stated use case is a practical guideline in itself.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
coverage_statusBInspectInspect persistent autonomous observation continuity and source failures
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of behavioral disclosure. 'Inspect' signals a read-only operation and the description names the dimensions inspected (continuity and source failures), but it does not disclose output format, failure semantics, or any 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?
The description is a single concise sentence with no filler or redundant phrasing. It is front-loaded with the action verb, though the jargon-heavy phrase 'persistent autonomous observation continuity' 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?
For a zero-parameter tool, the description provides a reasonable starting point, but it omits any explanation of return values or how this status differs from sibling tools. Given no output schema and no annotations, a bit more context about expected results would make it more 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 tool has zero parameters and the schema description coverage is 100%, so the schema fully captures parameter semantics. The description adds no parameter-level meaning, but none is needed.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Inspect') and names the subject matter: persistent autonomous observation continuity and source failures. It is clear about what the tool covers, though it does not explicitly differentiate itself from siblings like 'coverage' or 'discovery_status'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided about when to use this tool versus coverage_status's siblings. The description names no alternatives, conditions, or exclusions, leaving an agent to infer usage from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
discovery_statusCInspectReturn public autonomous discovery status
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations present, the description carries the full burden, and it only discloses that the status is 'public' (a weak hint that no special access is needed). It says nothing about what status values can appear, whether the data is live or cached, or how failures surface. For a status endpoint this is thin behavioral disclosure.
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?
Six words, no fluff, and the verb is front-loaded, so the prose is structurally disciplined. However, the description crosses from concise into under-specified, providing too little substance for a tool whose schema and annotations are both empty.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
This is a simple tool (0 params, no annotations, no output schema), so the description is the sole source for predicting the response, yet it never says what the returned status looks like, what its possible values are, or how 'autonomous discovery' relates to the sibling 'coverage_status'. An agent cannot forecast output shape or semantics.
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 tool has zero parameters (empty schema, 0 required), so there is nothing the description needs to document. The 'public' qualifier is consistent with a no-input read call. The zero-param baseline of 4 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a verb ('Return') and a resource ('public autonomous discovery status'), so it is not a tautology, but the resource is vague: 'autonomous discovery' is undefined jargon, and next to the sibling 'coverage_status' an agent cannot tell what domain this status belongs to. It distinguishes from siblings only through the word 'discovery', which is never elaborated.
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 whatsoever. The description does not say when to call this tool versus the similarly named sibling 'coverage_status', nor whether 'public' means it should be preferred for unauthenticated checks. There is no when/when-not or alternative routing, leaving the agent to guess.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
machine_quoteCInspectFree quote before x402 payment for quick checks, verified checks, proofs, NOT_OBSERVED proofs, changes, or bundles
| Name | Required | Description | Default |
|---|---|---|---|
| to | Yes | ||
| from | Yes | ||
| term | No | ||
| entity | No | ||
| source | Yes | ||
| product | No | ||
| event_type | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the full burden of behavioral disclosure. It conveys that the tool is free and that it occurs before x402 payment, implying it does not execute the payment. However, it does not state whether the quote is binding, what inputs drive the price, whether any state is changed, or what the response contains.
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 purpose ('Free quote before x402 payment') and lists the covered products without repetition or fluff. Slight improvement could be a clearer verb form and separation of the product list.
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 7 parameters, 3 required, no annotations, and no output schema, this short description is insufficient for an agent to confidently form a valid request. It does not mention the required source/from/to inputs, the output format of a quote, or how multiple product types are requested. The description gives only a high-level scenario, not operational 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?
With 0% schema description coverage, the description must compensate. It adds natural-language labels for the product enum ('quick checks', 'verified checks', 'proofs', 'NOT_OBSERVED proofs', 'changes', 'bundles'), giving some meaning to the product parameter. But it does not explain the required `source`, `from`, `to`, or optional `term`, `entity`, `event_type`, which are entirely undocumented.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description identifies a clear purpose: providing a free quote before x402 payment, and names the product categories covered (quick checks, verified checks, proofs, NOT_OBSERVED proofs, changes, bundles). However, it uses a noun phrase rather than a strong verb ('Free quote' vs 'Gets a quote') and does not differentiate from sibling quote tools like quote, batch_quote, or counterparty_quote.
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 'before x402 payment' implies the timing/condition for calling the tool: obtain a price before paying. But there is no explicit guidance about when to choose this tool over siblings such as batch_quote, counterparty_quote, or quote, and no exclusion statements. It remains at the level of implied usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
machine_sales_telemetryAInspectReturn aggregate machine-sales funnel: requests, quotes, paywalls, paid requests, unique payers, and USDC revenue
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
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 disclosing behavior. It says 'Return', which hints at a read-only operation, but it does not describe data freshness, time window, output format, permissions, or any side effects. For a tool without annotations, this is a minimal behavioral disclosure.
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 verb 'Return' and resource 'aggregate machine-sales funnel', then efficiently lists the six key metric categories. Every word contributes, and there is no fluff or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
While the description clearly lists the metrics, it omits the return structure, time window, units for USDC revenue, and any caveats such as lack of filtering. With no output schema and no annotations, an agent lacks some information about the exact response shape and scope. It is adequate for a simple aggregate telemetry tool but leaves notable contextual gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters and schema description coverage is 100%. With no parameters, the description does not need to explain any inputs. The list of metrics is about return values, not parameter semantics. The no-parameter baseline of 4 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description has a specific verb 'Return' and a clear resource: the aggregate machine-sales funnel. It enumerates the exact metrics returned (requests, quotes, paywalls, paid requests, unique payers, USDC revenue), making it distinguishable from the quoting-focused sibling tools such as machine_quote and quote, which are about generating individual quotes rather than aggregate metrics.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The aggregate nature of the tool implies it is used for high-l-level sales funnel metrics rather than for quoting tasks, but the description provides no explicit when-to-use or when-not-to-use guidance, and does not name any sibling tools or alternative conditions. Usage is only implied, not directly stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
machine_sourcesAInspectList ARAKEL official-source adapters and configuration status
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the behavioral burden. 'List' implies a read-only operation, but the description does not clarify what 'configuration status' actually contains, whether any prerequisites exist, or what kind of output to expect. Basic but not richly 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?
The description is a single, focused sentence that leads with the action and immediately identifies the subject. There is no filler or redundant phrasing.
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 listing tool, the description is nearly sufficient. The main gap is that 'configuration status' is vague and the absence of an output schema means the agent gets no further details about the return shape, but the low complexity keeps this from being a major deficiency.
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 tool has zero parameters, so the schema already fully covers parameter semantics. The description adds context about the resource being listed, which is appropriate, and the baseline of 4 applies here.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('List') and names a concrete resource ('ARAKEL official-source adapters and configuration status'), making the primary function clear. It does not explicitly differentiate from sibling tools, but the resource name is specific enough to avoid major ambiguity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given about when to use this tool versus siblings such as coverage_status, discovery_status, or machine_quote. An agent must infer selection entirely from the tool name and minimal resource description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
quoteCInspectFree preflight: check conclusive-result availability and exact x402 price
| Name | Required | Description | Default |
|---|---|---|---|
| to | Yes | ||
| from | Yes | ||
| term | Yes | ||
| product | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the full burden of behavioral disclosure. It discloses that the tool is free and checks availability/price, but it does not state whether the operation is read-only, has side effects, requires authentication, or what happens with invalid inputs. The 'preflight' wording hints at safety but does not make it 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?
The description is a single concise sentence that front-loads the key selling point ('Free preflight') before specifying the check. Every word earns its place; there is 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 four parameters (three required), no output schema, and no annotations, the description is far too sparse. It does not explain the required parameters' semantics, the return format, or usage context, leaving an agent to guess.
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 does not mention any of the parameters (term, from, to, product) or explain their meaning. An agent cannot determine what values to provide for these required fields from the description alone. This is a critical gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('check') and names the resource: 'conclusive-result availability and exact x402 price'. It is clear that this is a preflight quote operation. However, it does not explicitly differentiate itself from sibling tools like batch_quote, counterparty_quote, or machine_quote, so it stops short of a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given on when to use this tool versus alternatives. The word 'preflight' implies it should be used before a commitment, but there is no explicit statement of when to choose quote over batch_quote, counterparty_quote, or machine_quote, nor any 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.
Claiming 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 or an account that owns the GitHub organization, then choose Claim with GitHub.
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
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Dated, signed compliance-evidence packs: gov-fact-grounded claims + exclusion screens + trap-facts.
Screen people & companies against 12 US sanctions & exclusion lists (OFAC, LEIE, SAM, Medicaid).
Official-source US business, permit, and WHOIS evidence via read-only MCP tools.
Read-only verification evidence for paid machine services and buyer policy checks.