Read-only catalogue MCP for Lowtoxgear — Australian low-tox lifestyle brand. 5 tools.
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Average 3.9/5 across 5 of 5 tools scored. Lowest: 2.9/5.
Tools are largely distinct: filter_by_certification is for certification-specific searches, search_products for general keyword search, get_product for single product details, list_collections for collections, and get_policies for policies. The two search tools have overlapping purposes but descriptions clarify their specific intents.
All tool names follow a consistent verb_noun pattern in snake_case: filter_by_certification, get_policies, get_product, list_collections, search_products. This makes it easy for an agent to predict naming conventions.
With 5 tools covering search, filter, detailed info, collections, and policies, the set is well-scoped for a storefront read-only API. Each tool serves a distinct purpose without unnecessary bloat.
The tool set covers key product discovery and policy retrieval, but lacks a dedicated tool to list all products or products by collection. This forces reliance on search_products, which may not return all results or handle empty queries gracefully.
filter_by_certificationAInspectFind Lowtoxgear products matching a specific low-tox certification or standard. Searches product tags + product_type for the term. Use for queries like "show me GOTS-certified products" or "PFAS-free options". Common terms: "GOTS", "OEKO-TEX", "PFAS-free", "fluorocarbon-free", "fragrance-free", "organic", "responsibly sourced".
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | 1–50. Default 20. | |
| certification | Yes | Certification or low-tox standard to match |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description effectively discloses behavior: it searches specific fields (tags, product_type) for the given term. It lacks mention of case sensitivity or multiple terms, but is sufficient for a simple filter.
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 and a list of examples. Every element adds value, and the key information is front-loaded.
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 tool's simplicity (2 params, no output schema), the description fully covers usage, examples, and behavior. No gaps are apparent.
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 100% with descriptions, but the description adds value by explaining how the certification parameter is used (matching product tags and product_type), going beyond the schema's generic description.
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: find Lowtoxgear products by certification or standard. It specifies the search scope (product tags + product_type) and distinguishes from sibling tools like search_products which likely do broader searches.
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 explicit query examples and common search terms, guiding when to use the tool. However, it does not explicitly contrast with sibling search_products, though the specificity implies certification-focused use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_policiesAInspectGet Lowtoxgear shipping, refund, privacy, terms policy URLs, the bot/agent policy text, AND a pointer to the sister scanner service (com.lowtoxgear/scanner) for chemical-safety analysis of barcoded products.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description must fully disclose behavior. It states what is returned but does not mention side effects, authentication needs, rate limits, or whether the operation is read-only. This is insufficient for a tool with no annotation backing.
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 efficiently conveys all key information. It is slightly run-on but contains no redundant or extraneous content.
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, no-output-schema tool, the description provides sufficient detail on the return data. However, it lacks any mention of whether the policy URLs are static or dynamic, or any conditions for the scanner pointer.
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?
There are no parameters, so the schema coverage is 100% trivially. The description adds value by detailing the returned data (URLs, text, pointer), exceeding the baseline expectation for zero-parameter tools.
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 retrieves policy URLs, text, and a scanner pointer. It uses specific verbs ('Get') and resource ('Lowtoxgear policies'), distinguishing it from sibling tools focused on certification, products, collections, and search.
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 when-to-use or alternative guidance is provided. While the purpose is narrow and self-explanatory, the description does not discuss context or exclusions, leaving the agent to infer usage solely from the name and sibling names.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_productAInspectGet detailed info for a single Lowtoxgear product by URL handle. Returns title, vendor, type, tags, full description HTML, variants with prices/SKU/availability, and images.
| Name | Required | Description | Default |
|---|---|---|---|
| handle | Yes | Product URL slug, e.g. "black-hole-duffel-40l" |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses that the tool returns detailed info (list of fields) and implies read-only behavior via 'Get,' but does not explicitly confirm no side effects, authentication needs, or rate limits. The description adds value beyond the name but lacks full behavioral transparency.
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, front-loaded with the primary purpose in the first sentence and return details in the second. Every word earns its place; 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 simple, single-parameter tool with no output schema, the description covers the essential: what it does, how to use it (by handle), and what it returns (full list of fields). No gaps are evident given the tool's simplicity.
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 100% for the single parameter 'handle,' so baseline is 3. The description adds nothing beyond the schema's description of the handle as a 'Product URL slug,' except the example value 'black-hole-duffel-40l' which provides practical guidance but does not significantly augment 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 explicitly states 'Get detailed info for a single Lowtoxgear product by URL handle,' specifying the verb ('get'), resource ('product'), and scope ('single by URL handle'). It lists return fields (title, vendor, etc.), clearly distinguishing it from siblings like search_products (search multiple) and list_collections (collections).
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 communicates clear context: use this tool when you need detailed information for one product identified by its URL handle. It does not explicitly state when not to use or name alternatives, but the context makes it obvious that for single-product lookups this is appropriate, while search_products handles broader searches.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_collectionsCInspectList all public collections on Lowtoxgear with title, handle, URL, and product count. Examples: "Certified Activewear", "Clean Supplements", "GOTS Certified", "Low-Tox Home Products".
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | 1–100. Default 50. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It only states 'list all public collections' without mentioning read-only nature, pagination, authentication, or any 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 a single sentence followed by examples. It is front-loaded and efficient, though the examples are somewhat redundant with the 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?
For a simple list tool with one parameter and no output schema, the description is adequate but lacks details like ordering, full scope, or pagination behavior beyond the limit parameter.
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 100%, and the schema fully describes the 'limit' parameter. The description adds no additional parameter information, so baseline score of 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 clearly states the tool lists all public collections with specific fields and provides examples. It is a specific verb+resource, but lacks explicit differentiation from sibling tools.
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 on when to use this tool versus alternatives like filter_by_certification or search_products. The description only states what it does.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_productsAInspectSearch the Lowtoxgear catalogue by keyword. Australian low-tox lifestyle brand spanning certified activewear, clean supplements, GOTS-organic apparel, and low-tox home goods. Returns up to 10 product summaries with title, price (AUD), image, availability, and storefront URL. Natural-language queries work: "organic cotton tee", "PFAS-free duffel", "snow bibs", "magnesium supplement".
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | 1–10. Default 10. | |
| query | Yes | Free-text keyword or phrase |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It describes return format (up to 10 summaries with specific fields) and accepts natural language. Does not mention auth, rate limits, or side effects, but search is generally non-destructive.
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 well-structured sentences: first states core purpose and context, second details return format and query examples. No redundant or unnecessary 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?
For a search tool with two parameters and no output schema, description fully covers inputs, behavior, and outputs. Examples provide clarity on usage. No gaps identified.
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 100%, but description adds value by explaining natural-language queries work and listing example queries. Also clarifies limit range and default, which are already in schema but reinforced.
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 tool searches the Lowtoxgear catalogue by keyword, mentions brand and product categories, and lists return fields. Distinguishes from siblings like filter_by_certification and list_collections by focusing on keyword search.
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?
Provides context on natural-language queries and examples. Does not explicitly exclude alternative tools, but sibling names imply different use cases (filtering, collection listing). Lacks explicit 'when not to use' guidance.
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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