product-barcode-api

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

There are no annotations, so the description carries the full burden. It discloses the returned data, the paid-plan requirement, and per-call billing, which is useful. However, it does not mention whether the operation is read-only, what authentication is required, or that the returned credentials are sensitive.

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 concise sentences with no wasted words. The core purpose is front-loaded, and the second sentence adds the monetization constraint.

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 parameterless endpoint with no output schema, the description gives the essential facts: what is returned, how access is granted, and the cost. Minor gaps remain around auth details and response format, but they are not critical for basic invocation.

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, and the input schema is empty. No parameter explanation is needed, so the baseline of 4 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 states a clear purpose: it returns the username and password for the MySQL database containing product information. This distinguishes it from sibling tools that fetch products, history, or market lists.

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 intended use is implied: use this endpoint when you need database credentials. It also states a prerequisite (subscribing to the $100 plan) and cost, but it does not explicitly describe when not to use it or compare it to 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 carries full behavioral burden. It does disclose a genuinely useful behavioral trait absent from structured data: metered billing with an average credit cost. Beyond that, it says nothing about return format, rate limits, or pagination termination behavior, and 'Lists' only implicitly signals a read-only operation.

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 short sentences with the purpose stated first and billing second. Nothing is padded or redundant; 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?

For a paginated list tool with a fully documented schema and no output schema, the description covers purpose and cost but omits any routing guidance against its many siblings. Given the crowded sibling set, that omission leaves a real gap in what the agent needs to select this tool correctly.

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 parameter descriptions are rich (credit costs, defaults, market filtering, dependencies like historyPrices requiring marketPrices). The description adds nothing beyond the schema on parameters, so the baseline 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 states a specific verb and resource ('Lists products') and mentions pagination as the mechanism. However, it does not differentiate this tool from close siblings such as get_api_external_search or get_api_external_product_of_market, leaving the agent to guess why it would list products here rather than search for them.

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 guidance on when to use this tool versus the seven sibling tools. Nothing indicates whether this is a bulk catalog listing versus a targeted lookup, nor are there any prerequisites or exclusions mentioned. 'Using pagination' is a mechanism, not a usage guideline.

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 are provided, so the description must convey behavior. It mentions billing ('Billing per call: 1 Credits') but fails to disclose whether the operation is read-only, potential failure modes, or side effects. The description is not misleading but is insufficient for 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 extremely concise, consisting of two short sentences. It conveys the essential purpose and billing information without unnecessary words, making it easy to parse quickly.

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 is adequate for a simple retrieval operation, but it omits details about return values, error handling, or whether the market parameter is optional (though the schema notes it). It is not incomplete to the point of confusion, but could be more thorough given the lack of annotations and output 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?

The input schema already provides detailed descriptions for both parameters (barcode and market), including that market must exist in the system. The tool description adds only the synonym 'relevant store' for the market parameter, which does not significantly enhance understanding. Given high schema coverage, the baseline score of 3 is appropriate.

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 function: retrieving historical price information for a product at a specific store. It uses a specific verb ('retrieves') and a distinct resource ('historical price information'), which distinguishes it from sibling tools that likely handle search or product listings.

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 the tool is used when historical price data is needed (e.g., 'relevant store' suggests providing a market), but it does not explicitly contrast with alternatives like search or marketList. It gives some context but lacks clear guidance on when to prefer this tool over others.

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 carries the full burden. It discloses the read-only nature via 'Retrieves' and the zero-credit cost, which is useful. Yet it does not specify return format, ordering details beyond 'recently updated,' or any potential limitations, making it moderately transparent but not rich.

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, clear sentence stating the core purpose, followed by a brief billing note. It is front-loaded, efficient, and contains 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?

Given the tool's simplicity (no parameters, no output schema), the description provides the essential facts: what it returns and its cost. It could elaborate on the output structure, but for a straightforward list retrieval, the current description is adequately complete.

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 no parameters, so the schema is trivially covered. The description adds no parameter-specific information because none exist. According to the baseline rule for zero-parameter tools, a score of 4 is appropriate.

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 ('Retrieves') and resource ('20 most recently updated products') with a specific output scope ('along with their market prices'). This distinguishes it from siblings like getProducts or search by focusing on recency and the free billing aspect.

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 offers implied usage context: it is free and returns the latest products, so an agent would use it when these criteria are needed. However, it does not explicitly mention alternatives or when not to use it, leaving the comparison to siblings like search or getProducts implicit rather than explicit.

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 are present, so the description must convey the safety and behavior profile. It says 'Retrieves' and explicitly mentions billing at 0 credits, but it does not disclose caching, freshness, response shape, or any access requirements.

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, direct sentence that communicates the purpose, scope, and billing cost without unnecessary detail.

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?

This is a simple zero-parameter list tool with no output schema. The description states what is returned, market names, and the billing details, which is sufficient for this low-complexity 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?

There are zero parameters and 100% schema coverage, so the description has no parameter burden to carry. The baseline for a no-parameter tool is 4.

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 what the tool does: retrieves market names used in filters. It is specific enough to distinguish from sibling tools like product_of_market or search, though it does not explicitly name alternatives.

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 phrase 'used in the filters' implies when this tool would be relevant, but there is no explicit guidance about when to prefer it over sibling tools. No exclusions or alternative recommendations are provided.

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 carries the burden and does disclose read-style behavior, optional price history, and metered billing implications. It does not mention response shape, not-found behavior, error cases, or side effects, which leaves meaningful transparency gaps for a tool with no annotation safety profile.

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 core behavior is front-loaded and the description is compact, with no marketing filler. The only minor inefficiency is the slightly redundant billing phrasing 'Billing per call: Credits: metered (~0 avg)', but overall it is concise.

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 low-complexity and all parameters are documented in the schema, but there is no output schema or annotations. The description provides enough to attempt a call, but 'price and details' is vague about the result structure, currency/units, and what happens when the product is not found or the market name is invalid.

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 reiterates barcode, store name, and optional history but adds no new parameter meaning beyond what the schema already gives, such as value formats, allowed market names, or default behavior.

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 action and resource: returns the current price and details of a product based on barcode and store name. The title reinforces the market-price retrieval focus. It does not explicitly contrast with sibling tools, but the barcode+store keying makes the purpose clear.

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 the tool: when a barcode and store name are available. It does not state when not to use it or point to alternatives like search or history, so the agent must infer routing from sibling names rather than explicit guidance.

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 carries the full behavioral burden. It usefully discloses the result-count bounds (min 1, max 10) and a per-call billing cost (~0.85 avg credits), which is real value beyond the schema. But it omits auth/permission requirements, error behavior, and what the response looks like.

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 dense clauses with the core action front-loaded and no filler. Every element (search keys, result range, billing) earns its place, though the semicolon-joined billing note reads slightly like metadata appended rather than integrated prose.

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 no annotations, the description covers the input action and result cardinality but leaves the return shape and error/empty-result behavior unexplained. It is adequate but not complete for an agent to predict what comes back.

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 all four parameters (query, marketPrices, historyPrices, preferredMarkets) are already well documented in the schema itself, including credit costs and the dependency of historyPrices on marketPrices. The description adds no parameter-level meaning beyond that, so the baseline 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?

States a specific verb and resource ('Searches for products by barcode or name') and quantifies the result set (1–10 products). However, it does not distinguish itself from the close sibling get_api_external_getProducts or get_api_external_product_of_market, so an agent cannot easily tell which search/list tool to pick.

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 never states when to use this tool versus the many sibling lookup tools, nor prerequisites such as whether marketPrices/historyPrices should be toggled for a given intent. Usage context is implied only by the parameter names in the schema.

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 carries the full burden. It states the tool 'sends products to email address' but the schema reveals the email parameter is optional and that the file also returns in the API response when no email is given. This is misleading—the description implies email is mandatory. It also omits behavioral traits like the response format (Excel file) and any authentication requirements beyond the plan restriction.

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 concise, with two sentences front-loading the core purpose. It includes relevant business constraints (plan and billing) without unnecessary fluff. However, the emphasis on email might mislead the agent, and the structure could better separate the optional email behavior.

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 there is no output schema and no annotations, the description should explain what the tool returns. It only mentions sending to email, omitting that the Excel file is also returned in the response when no email is specified. It doesn't address prerequisites like authentication, and the optionality of email is not conveyed. The description is insufficient for an agent to understand the full behavior and call this tool correctly.

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 input schema provides exhaustive descriptions for all four parameters (100% coverage). The description adds no parameter-level detail beyond what the schema already offers, so it meets the baseline but doesn't compensate for anything missing.

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 sends products in Excel format to an email address, which distinguishes it from siblings like getProducts (which likely returns raw JSON). However, it doesn't explicitly mention that the API also returns the file in the response body, only focusing on email delivery. The plan restriction adds specificity but doesn't fully differentiate from similar product-fetching 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?

The description mentions the $350/month plan requirement and per-call billing, which are constraints but not usage guidance. It does not explain when to prefer this tool over alternatives like getProducts or search, nor does it clarify that email is optional. No context is given about typical scenarios (e.g., bulk export vs. single product lookup).

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