Search Men Groomer (mengroomer.gr, Greece) trimmers, shavers and parts: price, stock, links.
Scored across 3 tools
Each tool targets a clearly distinct need: keyword lookup (search_products), single-item detail retrieval by product_id (get_product), and static policy/contact information (store_info). There is no plausible way an agent would confuse these three, and the descriptions explicitly reference the product_id relationship between search and get.
get_product and search_products follow a consistent snake_case verb_noun pattern, but store_info breaks the pattern by being a bare noun phrase with no verb. The deviation is minor and the intent is still obvious, so readability is not harmed.
Three tools is at the low end but well-matched to a narrow product-catalog server: search, detail, and store policies each earn their place with no filler. A slightly richer surface (e.g. category browsing) would round it out, but nothing is superfluous.
The core shopping-research lifecycle is covered: find products, inspect a specific product's price/stock/description, and answer shipping, payment, and returns questions. Gaps like category listing, filtering/pagination options, or variant lookups are minor and workable via search.
Get the current price, availability and full description of one Men Groomer product by its product_id (from search_products, e.g. K382-19120).
| Name | Required | Description | Default |
|---|---|---|---|
| product_id | Yes | e.g. K382-19120 |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full behavioral burden. 'Get' plus 'current price, availability' usefully signals a read-only, point-in-time snapshot, but it says nothing about error behavior for an invalid or stale product_id, currency/locale of prices, or rate limits.
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?
One sentence, front-loaded with the verb and resource, with the returned fields and the ID provenance packed in without waste. Nothing is repeated 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 single-parameter read tool with no output schema, the description is sufficient: it explains where the ID comes from and what fields the result contains. The main remaining gap is failure/edge-case behavior for a bad ID, which is minor at this complexity.
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 parameter already carries the same example ID, so the schema does the documentation work. The description adds the provenance hint (the ID comes from search_products), which is mild added meaning but nothing about format constraints.
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 Men Groomer product by product_id) and enumerates what comes back: current price, availability, and full description. The 'one ... by its product_id' phrasing clearly separates it from search_products, which returns multiple results.
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 names the sibling that supplies its input ('from search_products, e.g. K382-19120'), which implicitly routes the agent: search first, then fetch detail by ID. It doesn't state explicit exclusions or when-not-to-use (e.g. don't call for browsing/listing), so it stops 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.
Search the Men Groomer (mengroomer.gr, Greece) product catalog. Men Groomer store in Greece: rechargeable, waterproof men's grooming trimmers and shavers with BladeLock technology for safe shaving even in sensitive areas, plus accessories and spare parts. Works in Greek or English. Returns products with current price in EUR, stock status, product page url and image.
| Name | Required | Description | Default |
|---|---|---|---|
| page | No | Result page, default 1 | |
| query | Yes | What the customer is looking for | |
| max_results | No | 1-30, default 10 | |
| in_stock_only | No | Only products available now |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the behavioral burden and does disclose useful traits such as Greek/English support and returned fields including price in EUR and stock status. It still omits specifics about search matching, pagination behavior, and whether results are ranked, so it is adequate but incomplete.
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 core action and then adds relevant store and result context. The second sentence contains some marketing-style product detail that is less essential, but overall the structure is clear and 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?
The description helps compensate for the lack of an output schema by listing key returned fields. However, for a tool with no annotations, it does not fully explain pagination or result-count behavior, leaving some operational context to the 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 description coverage is 100%, so the baseline is 3. The description adds meaning beyond the schema by noting that queries work in Greek or English, which directly informs how the 'query' parameter should be constructed.
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 and resource: search the Men Groomer product catalog. It is clear what the tool does, but it does not explicitly distinguish itself from the sibling get_product tool, which likely handles single-product lookups.
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 implied by 'Search the ... product catalog,' and the language note helps frame the query. However, there is no explicit guidance on when to use this tool instead of get_product or store_info, and no exclusions are stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Men Groomer shipping, payment methods, returns, contact details.
| 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 behavioral burden. It does not state whether this retrieves or stores information, whether access is read-only, what authentication is needed, or what output to expect; it only names topic areas.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very short, but it is a fragmented list rather than a structured statement of purpose. 'Men Groomer' is ambiguous and the sentence is not front-loaded with a clear action.
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 informational tool with no output schema, the description gives some topic coverage. It remains incomplete because it does not clarify the tool's retrieval behavior or what the returned store information will contain beyond broad categories.
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 parameter semantics are largely irrelevant. The baseline score for a no-parameter tool applies, and the description does not need to explain argument meaning.
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 lists store-information topics (shipping, payment methods, returns, contact details), which hints at the resource. However, it is a noun-phrase fragment with no action verb, so it only vaguely states what the tool does and does not clearly distinguish itself from get_product or search_products.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no explicit guidance on when to use this tool versus the sibling product tools. The listed topics imply it is for non-product store policy/contact information, but the agent must infer that entirely.
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.
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