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Glama

KodShop catalog

Server Details

Read-only catalog of gift cards, service top-ups and travel eSIMs sold by KodShop.

Status
Healthy
Last Tested
Transport
Streamable HTTP
URL

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Tool DescriptionsA

Average 3.9/5 across 2 of 2 tools scored.

Server CoherenceA
Disambiguation4/5

The two tools have distinct purposes: one fetches a specific product by ID, the other searches the catalog by query. There is slight overlap in that both return product information, but the input and output detail level differ sufficiently to avoid significant confusion.

Naming Consistency5/5

Both tools follow a consistent verb_noun pattern: 'get_product' and 'search_catalog'. This is clear and predictable, making it easy for agents to understand their function.

Tool Count3/5

With only two tools, the server feels minimal but is plausible for a read-only catalog lookup service. It sits at the borderline of being too thin, but the two tools cover the core lookup and search needs without unnecessary bloat.

Completeness4/5

The domain is product catalog retrieval, and the server covers searching and fetching detailed product info. Missing features like pagination or category browsing are minor gaps that agents can work around, and no write operations are expected for a catalog view.

Available Tools

2 tools
get_productAInspect

Get one catalog product by id: available denominations with prices, required order inputs, and any countries where the code cannot be redeemed.

ParametersJSON Schema
NameRequiredDescriptionDefault
idYesProduct id from search_catalog.
Behavior4/5

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

With no annotations provided, the description carries the burden of behavioral disclosure. It reveals the type of information returned, which is central to the tool's behavior. While it does not cover error handling or explicit read-only confirmation, the 'Get' verb strongly implies a safe read operation, and the description goes beyond a minimal restatement.

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

Conciseness5/5

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

The description is a single, well-structured sentence that leads with the action and resource, then efficiently lists the key returned data. There is no redundant or filler language.

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

Completeness4/5

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

The tool is simple with one parameter and no output schema. The description adequately communicates the primary purpose and the nature of the data returned, covering key details an agent needs to decide whether to invoke the tool. It omits potential edge-case behavior (e.g., not found), but this is not critical for basic use.

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

Parameters3/5

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

Schema coverage is 100%, with the 'id' parameter described as 'Product id from search_catalog.' The tool description adds no further parameter detail, but with full schema coverage, the baseline of 3 is appropriate.

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

Purpose5/5

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

The description clearly states the tool retrieves one catalog product by ID and lists specific information returned (denominations, prices, required order inputs, redemption restrictions). It distinguishes itself from the sibling search_catalog by focusing on fetching a single item by ID rather than searching.

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

Usage Guidelines4/5

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

The description implies the tool is used when you have a specific product ID and need details, and the parameter schema further indicates the ID comes from search_catalog, establishing a clear workflow. However, it does not explicitly state when not to use this tool or directly compare with search_catalog in the description itself.

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

search_catalogAInspect

Search the store catalog of gift cards, service top-ups and eSIM data plans. Returns matching products with their price, availability and product page URL.

ParametersJSON Schema
NameRequiredDescriptionDefault
typeNovoucher = gift card, recharge_fixed / recharge = top-up, e_sim = eSIM data plan.
limitNoMax products to return (default 10, max 50).
queryNoFree text matched against product name and brand, e.g. "steam" or "playstation".
countryNoISO-3166-1 alpha-2 country code the product is issued for, e.g. US, TR.
Behavior3/5

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

With no annotations, the description carries the burden for behavioral disclosure. It does disclose the return fields (price, availability, product page URL), which is useful. However, it does not mention whether the operation is read-only (though implied by 'search'), any authentication needs, or rate limits. The disclosure is basic but not misleading.

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

Conciseness5/5

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

The description is two sentences with no wasteful words. It front-loads the action ('Search') and efficiently specifies both the scope and the result fields. Every sentence earns its place.

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

Completeness4/5

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

Given four optional parameters and no output schema, the description adequately explains what is returned (matching products with price, availability, and URL). It is complete enough for a search operation, though it could mention that get_product is available for detail retrieval, but that is not strictly necessary.

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

Parameters3/5

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

The schema description coverage is 100% and all parameters have detailed descriptions, including the enum mapping for type. The tool description adds no additional parameter behavior beyond the schema, so a baseline of 3 is appropriate.

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

Purpose4/5

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

The description clearly states the tool searches a catalog of gift cards, top-ups, and eSIM plans, and returns matching products with price, availability, and URL. It uses a specific verb and resource but does not explicitly differentiate from sibling tool get_product, so it gets a 4 rather than 5.

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

Usage Guidelines3/5

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

The description implies usage: it is for searching the catalog and returning matching products. However, it provides no explicit guidance on when to use this tool versus get_product, nor any exclusions or alternative scenarios. This is implied usage without a clear decision framework.

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

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