Filtrous MCP Catalog Server

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

Without annotations, the description carries the full burden. It discloses authentication requirements and placeholder status, but does not mention rate limits, data freshness, or potential impacts of usage. This is adequate but not comprehensive.

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: the first clearly states purpose and scope, the second adds critical context (API key requirement and placeholder data). No extraneous words.

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 tool is simple with one parameter and no output schema. The description lists the returned information (price, availability, stock) and caveats (placeholders, restrictions). It is sufficiently complete for a basic read operation.

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 single parameter (sku) is fully described in the schema (100% coverage). The tool description adds no additional parameter-level meaning beyond what the schema provides, achieving the baseline.

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 verb 'Get' and the resources 'price, availability, and (when permitted) stock' for a specific SKU. It differentiates from sibling tools like get_product_details (general product info) and request_quote (quote generation).

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 specifies that the tool requires a valid API key ('KEYED tool') and notes that data is placeholder until Acumatica sync. However, it does not explicitly contrast with sibling tools or state when to use this vs alternatives.

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

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

With no annotations, the description discloses a key behavioral trait: 'Open tool — no API key required.' This helps the agent understand auth requirements. It also describes the return content (variants, SKUs, etc.), but does not mention potential errors or rate limits. Sufficient for a simple read-only lookup.

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 sentences with no unnecessary words. The first sentence delivers the core purpose, and the second adds authentication transparency. Every sentence earns its place.

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 low complexity (one required parameter, no output schema, no nested objects), the description explains what data is returned (variants, SKUs, options, prices, images, spec metafields). Lacks details on error handling for invalid handles, but adequate for a straightforward lookup tool.

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. The description adds context by stating 'by its handle' and referencing search_products as the source, slightly enhancing the schema's description. With high coverage, baseline is 3, and the description provides marginal added value.

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?

Clearly states it gets full details for one product by its handle, listing specific data included (variants, SKUs, etc.). Distinguishes from siblings like search_products (search vs single product), get_price_and_lead_time (pricing only), and request_quote (quotes).

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 clear context: use the product handle (e.g., from search_products) to retrieve full details. Implicitly guides the agent to first search, then use this tool. Does not explicitly state when not to use or mention alternatives, but the sibling tools cover different use cases.

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

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

With no annotations provided, the description must disclose all behavioral traits. It successfully mentions that an API key is required ('KEYED tool') and that the process is asynchronous ('Sales follows up out-of-band'). However, it does not disclose potential side effects (e.g., quote creation), error scenarios, or return format, leaving gaps in 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-loading the core purpose in the first sentence and adding auth/async context in the second. Every word serves a purpose, with no fluff or redundancy.

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 complexity (nested parameters, no output schema, no annotations), the description covers the essential aspects: what it does, auth requirements, and post-submission behavior. It could be improved by noting any response or confirmation, but overall provides a sufficient mental model for correct use.

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 description adds minimal meaning beyond the input schema, summarizing that the tool takes SKUs and contact info. The schema already has descriptions for items and notes (67% coverage), and the description does not elaborate on parameter constraints or usage nuances. Baseline 3 is appropriate given moderate schema coverage.

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 action ('Submit a quote request'), the resource ('one or more SKUs'), and the required context ('buyer contact info'). It distinguishes itself from sibling tools (get_price_and_lead_time, get_product_details, search_products) by being a write/submission tool rather than a read/inquiry tool.

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 implies when to use this tool (when needing to submit a quote request) and provides context about post-submission behavior ('Sales follows up out-of-band'). However, it lacks explicit guidance on when not to use it or alternatives, though the purpose is clear enough for an agent to differentiate from siblings.

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

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

No annotations provided, so description carries full burden. It mentions return fields and openness, but lacks details on pagination, sorting, or potential side effects. Adequate but not thorough.

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 sentences, front-loaded with purpose and example. No wasted words. Efficient and clear.

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?

No output schema, but description lists return fields. No mention of sorting or pagination details beyond limit. For a search tool, this is largely complete given lack of annotations.

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 covers both parameters with descriptions. Description adds extra context: field filters (product_type:, tag:) are honored, which adds meaning beyond schema. Good.

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 searches the Filtrous catalog by free text or spec terms, with an example. It lists returned fields and distinguishes siblings (get_price_and_lead_time, get_product_details, request_quote) by being the search entry point.

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 'Open tool — no API key required,' indicating easy access. Does not explicitly say when not to use it, but the sibling tool names imply alternatives for price/details/quotes. Context is clear enough.

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