Latitude 10 Store
Server Details
Developer kits and design packs for AI agents, paid in USDC over x402. Free API readiness check.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP · MCP 2025-11-25
- URL
TDQS
Scored across 4 tools
list_products, get_product, and buy_product form a clean, distinct browse/inspect/purchase trio with no overlap. check_agent_readiness is clearly a separate domain, but it sits oddly alongside the store tools and can confuse an agent about the server's overall scope.
All four tools follow a consistent snake_case verb_noun pattern (list_products, get_product, buy_product, check_agent_readiness). No deviations or mixed conventions.
Four tools is slightly thin but well-scoped for a small store: browse, inspect, and buy the catalog. The single evaluation tool is a reasonable adjunct rather than bloat.
The core store lifecycle (list, get, buy) is fully covered, and buy_product returns the download link. Minor gaps remain: no way to re-retrieve a past purchase or view order history, which an agent can work around only by re-buying.
Available Tools
4 toolsbuy_productBuy a productAInspect
Buy a product with USDC over x402. Without a payment it returns the x402 payment requirements; with one it settles the payment and returns the product (for kits, a personal download link valid for 24 hours).
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | Product slug from list_products | |
| account | No | For dashboard-pro only: the dashboard account id the pass is for |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare this is a non-readonly, open-world, non-idempotent mutation, so the safety profile is covered. The description adds genuinely useful behavior beyond that: the unpaid call returns payment requirements rather than erroring, settlement occurs on payment, and kit purchases yield a download link valid only 24 hours. It does not discuss retry/idempotency implications for a non-idempotent purchase, which is the main remaining gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two tightly packed sentences with no filler; the core action and the payment-dependent branching are front-loaded, and the 24-hour download caveat is placed exactly where it matters.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema, the description correctly covers the return values for both modes (payment requirements vs. product/download link). For a payment-settling tool it is largely sufficient, though it omits any note on failure handling or what happens to a partially completed payment.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with both slug and account documented in the schema itself (including the dashboard-pro-only condition on account). The description adds no parameter-level detail, so the baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description names a specific verb and resource ('Buy a product') and adds the payment mechanism (USDC over x402), which clearly separates it from read-oriented siblings like get_product and list_products. It stops short of explicitly naming an alternative sibling, so it is clear but not fully differentiated by name.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
It gives concrete context for both invocation modes: without a payment it returns x402 payment requirements, with one it settles. That effectively tells the agent the two-step flow to expect, though it never states exclusions or points to a sibling tool for non-purchase lookups.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
check_agent_readinessCheck agent readinessARead-onlyIdempotentInspect
Scores an API 0-100 for how well AI agents will use it as tools, from its OpenAPI 3.0 or 3.1 spec: operationIds, summaries, descriptions, parameter descriptions, enums, examples, JSON bodies, response and error schemas, pagination, auth, idempotency and tool count (the Agentify API kit's rules). Give the spec's https URL or the spec itself. Free; returns the score, each rule's result with how to fix it, and the most costly findings. Use it before turning an API into an MCP server or listing it for agents.
| Name | Required | Description | Default |
|---|---|---|---|
| url | No | https URL of the OpenAPI document (JSON or YAML), e.g. https://api.example.com/openapi.json | |
| spec | No | The OpenAPI document itself, as JSON or YAML text (up to 2 MB). Send url or spec, not both. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly, idempotent, non-destructive, and openWorld behavior. The description adds that the tool is 'Free' and returns 'the score, each rule's result with how to fix it, and the most costly findings'—useful cost and output context beyond the annotations. It does not mention rate limits or auth requirements, so a 4 rather than 5.
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?
Front-loads the core purpose, then efficiently covers input, output, cost, and usage in four tight sentences. Every sentence carries distinct information, with no redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no output schema and full annotation coverage, the description supplies all needed context: what it does, how to supply input, what it returns, that it is free, and when to use it. Nothing material is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents both parameters thoroughly, including mutual exclusivity ('Send url or spec, not both'). The description's 'Give the spec's https URL or the spec itself' adds only slight emphasis and no syntax or format details beyond the schema, fitting the baseline 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Specific verb 'Scores' with resource 'API' and precise scope: '0-100 for how well AI agents will use it as tools, from its OpenAPI 3.0 or 3.1 spec.' Lists the evaluated criteria and the source of rules, making the tool's function unmistakable even among unrelated 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?
Explicitly states when to use it: 'Use it before turning an API into an MCP server or listing it for agents.' Also tells the agent how to provide input ('Give the spec's https URL or the spec itself'). No when-not-to-use or alternative tools are mentioned, so it falls short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_productGet a productARead-onlyInspect
One product by slug, with its price and payment options.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | Product slug, e.g. "starter-kit" |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds useful context about return content (price and payment options), but says nothing about missing-slug behavior, auth needs, or how it relates to buy_product. With annotations doing the heavy lifting, a 3 is appropriate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single sentence with zero waste, front-loading the resource and scope before the return contents. Nothing is redundant or padded.
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 one-parameter read tool with no output schema, the description covers the essentials and partly compensates for the missing output schema by naming the return fields. It stops short of noting not-found behavior or the relationship to buy_product.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% and the single slug parameter is documented with an example ("starter-kit"), so the baseline is 3. The description adds no format, casing, or lookup semantics beyond what the schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb (get) and resource (one product by slug), and the word "One" implicitly contrasts with the list_products sibling. It does not explicitly name or differentiate against buy_product or list_products, so it falls 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?
Usage is only implied by "One product by slug" – an agent can infer this is the single-item lookup rather than a list or purchase. There is no explicit when-to-use, when-not-to-use, or named alternative such as list_products or buy_product.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_productsList productsARead-onlyInspect
Everything Latitude 10 sells to agents, with prices and how to pay: developer kits, and design packs (DESIGN.md design systems for fintech dashboards, developer tools, and editorial sites; $5 per project). Check it before building the UI of a new project.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds useful content context (what's sold, $5 per project pricing, what a design pack contains) but says nothing about return format, pagination, or ordering for a catalog listing.
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 catalog scope is front-loaded in the first clause, followed by supporting detail and a usage cue. The parenthetical listing of design-pack types is somewhat dense but each element is informative, and no sentence is pure 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?
With no parameters, no output schema, and annotations covering the safety profile, the description supplies what an agent needs: what the catalog contains, the pricing model, and when to consult it. Only listing behavior (pagination/ordering) is absent, which is minor here.
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 takes zero parameters, so there is no parameter semantics to document and the baseline is 4. Nothing in the description conflicts with the empty schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description names the resource (everything Latitude 10 sells to agents) and enumerates its contents (developer kits, design packs) with pricing, so the agent knows this is the product catalog. The verb 'list' is only implied via the name, but the scope is unambiguous and distinct from get_product/buy_product.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
It gives a clear usage context: 'Check it before building the UI of a new project,' which positions it as the discovery step. It does not name or exclude the siblings (get_product, buy_product), so the routing is implied rather than explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
4 tool updates
- First observed
buy_product - First observed
check_agent_readiness - First observed
get_product - First observed
list_products
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