DACIX — The Store for AI Agents

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

No annotations are provided, so the description carries the full burden. It discloses the 5-credit cost and that output is clean markdown from rules.city. However, it does not mention error handling, rate limits, or what happens if a city or topic is not found. It is moderately transparent but leaves gaps.

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, efficient sentence that lists key features (number of cities, topics, format, credit cost) without excess. Every word contributes value.

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 3 parameters with full schema descriptions and no output schema, the description sufficiently explains the tool's purpose, output format, and cost. It could include error or edge case behavior, but for a straightforward retrieval tool it is largely 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?

Input schema has 100% description coverage, so the description adds no new meaning beyond what the schema already provides for 'city', 'topic', and 'api_key'. Baseline is 3 as the description does not enhance understanding of parameters.

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 it provides practical civic info as clean markdown for 28,674 cities worldwide, listing example topics like parking, events, public-transport. It uses specific verbs and resources, and strongly distinguishes from sibling tools which are predominantly company/business or store related.

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 usage for civic info requests but does not explicitly state when to use this tool versus alternatives like web_crawl. It provides examples of topics, giving some context, but lacks exclusions or guidance on when not to use it.

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 carries full burden. It states it is a 'Category tree' and 'Free,' but does not describe the output format, whether it is read-only, or any other behavioral traits. The description is too sparse to fully inform an agent.

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 one sentence, front-loaded with the tool's core purpose and context. Every word is meaningful and there is no extraneous 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?

Given no output schema or annotations, the description provides basic context (website, purpose, free), but lacks details about the output format (e.g., structure of the category tree) or how to use the category_id. It is minimally adequate but incomplete for an agent to fully understand the tool's behavior.

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?

No parameters exist in the input schema, so the description cannot add value beyond it. The baseline for 0 parameters is 4. The description does not need to add param semantics.

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 identifies the tool as a 'Category tree' for a specific website and states its purpose: 'pick a category_id before posting an ad.' It specifies the resource and action, and distinguishes from sibling tools like city_info and post_classified_ad.

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 usage context: 'before posting an ad.' It implies when to use this tool (as a prerequisite) but does not explicitly state when not to use it or list alternatives. However, the context is clear for a simple lookup tool.

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 discloses cost (20 credits, conditional), listing duration (90 days), and output (public URL). It could mention if the ad is live immediately or reviewed, but covers key behaviors.

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 purpose, platform, duration, return value, and cost structure. No wasted 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 10 parameters (4 required) and no output schema, the description is reasonably complete: it covers the return value and cost. It could mention error handling or how to obtain the API key (referenced in schema), but overall adequate.

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 90%, so the schema already explains most parameters. The description adds no extra parameter meaning beyond what the schema gives. Acceptable for high coverage 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 'Publish a real classified ad on micapublicitate.online' with specific verb+resource, lists duration (90-day listing), and mentions the return URL. It distinguishes from sibling tools like classified_categories by being the only posting 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 provides context by noting the 20-credit cost charged only on acceptance, implying the tool is for creating ads. It does not explicitly exclude scenarios or name alternatives, but the intent is clear.

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?

Discloses credit cost and conditional charging, and mentions multi-year history. However, does not specify behavior when no data exists (e.g., empty response or error) or any authentication details beyond the API key format.

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 core functionality, no redundant words. Efficiently covers purpose, data scope, and cost.

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?

With 3 parameters, no output schema, and no annotations, the description adequately covers purpose, cost, and key data returned. Lacks detail on output structure and error handling, but sufficient for a simple retrieval 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 description coverage is 100%, so baseline is 3. Description adds context by linking the optional year parameter to multi-year history and listing output fields, but does not significantly enhance understanding of parameters beyond schema.

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 it retrieves yearly financials for a Romanian company by CUI, listing specific data fields (net turnover, profit/loss, etc.) and indicating multi-year history. This distinguishes it from sibling tools like ro_company_lookup or ro_company_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 cost hint (20 credits charged only if data exists) but lacks explicit guidance on when to use this tool versus alternatives. No exclusion criteria or prerequisites are given beyond having a CUI.

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 carries the full burden. It discloses pagination behavior and credit cost per page. The term 'Browse' implies a read-only operation. However, it does not explicitly state read-only nature or handle invalid API key scenarios. Still, the transparency is good for a list tool.

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, well-structured sentence that front-loads the most important information: purpose, filters, pagination, and cost. No redundant or irrelevant 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?

The tool has no output schema, so the description should explain return values. It does not mention what fields are returned or if results are sorted. For a simple list tool, it is adequate but incomplete. Adding the return structure would improve completeness.

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 67% (4 of 6 parameters have descriptions). The description adds contextual meaning to the filters (e.g., 'active vs struck-off (radiata)') beyond the schema comments. It does not detail the page and per_page parameters, but pagination is mentioned in the description. Overall it adds sufficient 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?

The description clearly states the tool lists Romanian companies with specific filters (county, active/struck-off, VAT-registered) and mentions pagination and credit cost. It distinguishes from sibling tools like ro_company_search and ro_company_lookup by explicitly listing its filter capabilities.

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 usage for filtered browsing of Romanian companies, but does not explicitly state when to use this tool versus alternatives. It lacks when-not or exclusion criteria, relying on implied context from the filter parameters.

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 the burden. Mentions credit cost (10, charged only if found) and coverage (~2M companies). Lacks details on rate limits, error handling, or other behavioral traits, but adequate 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?

Extremely concise: two sentences containing all essential information. Front-loaded with the core purpose (Romanian company registry profile by CUI). No superfluous text.

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 (2 params, no output schema, no nested objects), the description adequately covers input, output fields, and cost. Missing explicit output structure, but sufficient for a straightforward lookup.

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 for both parameters. Description adds context: explains CUI as tax ID, notes credit cost, and clarifies that credits are only charged on success. Provides meaning beyond basic schema.

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 the tool retrieves a Romanian company registry profile by CUI (tax ID) and lists the specific fields returned (legal name, status, VAT, CAEN, address). Distinguishes from siblings like ro_company_search (search by name) and ro_company_list.

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?

Implies usage by specifying lookup by CUI, contrasting with search or list tools. Does not explicitly state when not to use or provide alternatives, but context from sibling names makes it clear.

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. Description mentions credit cost but lacks disclosure of rate limits, idempotency, or read-only nature. Adequate but minimal extra behavioral context beyond purpose.

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?

Single sentence plus credit note conveys purpose, returns, and cost without waste. Exceptionally 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?

No output schema, but description lists returned fields per match. Lacks details on pagination, error handling, or matching criteria, but sufficient for a search tool with 2 required params.

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 for both parameters. Description adds slight value for api_key ('Get one with store_register') but is mostly redundant. Baseline 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?

Clearly states verb 'Search' and resource 'Romanian companies by name', and enumerates returned fields (CUI, legal form, county, active/struck-off). Distinguishes from siblings like ro_company_lookup (by CUI) and ro_company_financials.

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?

Mentions '10 credits' indicating cost, but no explicit when-to-use or when-not-to-use guidance. Sibling tools suggest alternatives, but no comparative advice is given.

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 cover behavioral traits. It mentions a credit cost (10 credits) and implies a read-only operation. However, it lacks details on error handling, rate limits, or what happens if no companies are found, leaving some gaps.

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, informative sentence with an additional note on credits. It is front-loaded with key information and contains no unnecessary 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?

Without an output schema, the description does not explain the return format or structure (e.g., list of companies, fields, pagination). For a search tool with 4 parameters, this is a significant gap in completeness.

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 for all parameters, so the description adds no additional meaning beyond the schema. 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 action 'Find' and the resource 'Romanian company registered at an address', with a specific use case ('due diligence: who is registered here?'). It effectively distinguishes from sibling tools like 'ro_company_search' which likely searches by name.

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 usage for due diligence by address, providing clear context. However, it does not explicitly state when to use this tool versus alternatives or when not to use it, so it falls 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.

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

No annotations provided, so description carries full burden. It implies read-only behavior but doesn't explicitly state no side effects, auth requirements beyond the API key, or other behavioral details like 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?

Single sentence with no wasted words. Action is front-loaded and explicitly states what is checked.

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, so description should detail return values. It mentions credit balance and owned templates but is vague on structure. Adequate for a simple tool but could be more specific.

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%, so baseline 3. Description adds no extra meaning beyond what the schema already provides for the api_key parameter.

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 action (Check) and resource (DACIX account) with specifics (credit balance and owned templates). It distinguishes itself from siblings like store_buy or store_catalog effectively.

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 when-not-to-use guidance. However, context from sibling names implies it's for read-only account info, but the description lacks explicit exclusions or 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 that the tool returns a checkout_url, fulfillment is automatic after payment, and suggests verification via store_order_status. It does not mention failure modes but is adequate for a purchase action.

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 exceptionally concise at two sentences, with no wasted words. It effectively communicates the core action, return value, and follow-up step.

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 3 parameters and no output schema, the description provides the essential workflow: buy product, get URL, pay, confirm. It lacks error handling details but is functionally complete for typical use cases.

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 no parameter-specific information beyond what is already in the input schema. Although schema coverage is 67%, the description does not elaborate on parameters like api_key, product_id, or quantity, missing an opportunity to add 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?

The description clearly states 'Buy a product' and specifies it returns a Stripe checkout_url, distinguishing it from sibling tools like store_catalog and store_order_status by mentioning fulfillment and confirmation.

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 clear usage context: it returns a checkout URL that should be opened for payment, and suggests confirming with store_order_status. While it does not explicitly state when not to use it, the guidance is sufficient.

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 carries the full burden. It discloses that no authentication is needed, which is helpful. However, it does not describe the return format, whether the list is complete, or any potential rate limits or data freshness. For a read-only listing tool, this is 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?

The description is a single sentence that efficiently conveys purpose, content, and an access requirement. Every word adds value, with no redundancy. It is front-loaded with the core action and resource.

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 has no parameters or output schema, the description is largely complete for its simplicity. It identifies the tool's domain (store catalog), items listed, and access requirement. However, it could explicitly state that the operation is read-only and safe, which would be helpful for agent reasoning.

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, so schema coverage is 100% by default. The description adds meaning by explaining what is listed (agent templates and API credit packs), which is useful context beyond the empty schema. Baseline for 0 params is 4, and this is met.

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: listing everything for sale at dacix.store, specifying two categories (agent templates and API credit packs). It uses a specific verb 'list' and distinguishes from sibling tools like store_buy or store_download_template.

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 notes 'No auth needed,' which is a useful prerequisite. While it doesn't explicitly say when to use vs alternatives, the context with sibling tools (e.g., store_buy for purchasing) implies this is the discovery tool before any purchase or download.

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?

Without annotations, the description bears full responsibility for behavioral traits. It does not disclose side effects, rate limits, or authentication requirements beyond the api_key parameter. It also does not clarify what happens if the template is not purchased or if the api_key is invalid.

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 with key info front-loaded. However, it is too sparse and omits important context, making it borderline insufficient.

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 low complexity (2 params, no output schema), the description covers the basic purpose and result format. Missing error scenarios and prerequisites, but acceptable for a simple retrieval 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 50%: only api_key has a description. The description adds no further meaning for product_id; it only implies it identifies the template. Overall, description adds minimal value over the schema.

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 ('Download'), the resource ('purchased agent template'), and the content format ('full JSON: system prompt, tools, schemas'). This distinguishes it from sibling tools like store_buy or store_catalog.

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. It does not mention prerequisites like needing to have purchased the template or how to obtain an API key. Missing any 'when not to use' or alternative tool references.

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 carries the burden. It discloses the context (post-payment, pending→paid) but does not mention side effects, rate limits, or required permissions.

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?

Single sentence, no redundant words. Clearly conveys the core function.

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 no output schema, incomplete parameter description, and no annotations, the tool definition lacks details on response format, error handling, and prerequisites.

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 50% (only api_key described). The description adds no parameter meaning; order_id is left undefined in both schema and 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 checks order status after payment and mentions the status transition (pending to paid). This distinguishes it from other store tools like store_buy or store_catalog.

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 usage after payment to check status change but does not explicitly state when to use or avoid this tool, nor mention 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?

No annotations are provided, so the description carries the full burden. It discloses the main outcome (account creation, API key, credits) but does not mention side effects like duplicate registration handling, email verification requirements, rate limits, or how errors are returned. The description is too minimal for a registration tool.

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, concise and front-loaded. The first sentence states the purpose, and the second provides a crucial usage note about storing the key. Every word 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?

The tool has no output schema, so the description partially compensates by mentioning the return of an API key and credits. However, it does not specify the response structure, error handling, or whether registration is immediate. Given the low complexity, it is slightly incomplete.

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 covers 100% of parameters with descriptions for both email and password. The description does not add new information about the parameters beyond what is in the schema. Therefore, 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 that the tool creates a DACIX account and returns an API key and free trial credits. It uses specific verbs ('Create', 'get') and the resource is well-defined. This distinguishes it from sibling tools like 'store_buy' or 'ro_company_financials'.

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 that this tool should be used first to obtain the API key for authenticating other tools, but it does not provide explicit guidance on when to use it versus alternatives (e.g., if already registered, use 'store_account' instead). It lacks a clear 'when not to use' statement.

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 burden of behavioral disclosure. It mentions server-side fetching and clean text output, but does not disclose potential issues like rate limits, handling of dynamic content, or error scenarios. Transparency is 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?

The description is extremely concise with two sentences totaling 25 words. It front-loads the core action and includes key context (cost) without any fluff.

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 covers the basic function and cost, but lacks details on output format, error handling, and limitations (e.g., JavaScript rendering, authentication requirements). Given no output schema, more behavioral context would be beneficial.

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%, so parameters are well-documented in the schema. The description does not add new information about parameters beyond what is in the schema (e.g., 'url' and 'api_key' are already described). 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 fetches any public web page server-side and returns clean readable text. The verb 'Fetch' and resource 'public web page' are specific, and no sibling tool has similar functionality, so it is well-distinguished.

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 credit cost ('Costs 5 credits, new accounts get 25 free'), which implies when to use it sparingly. However, it does not explicitly state when not to use it or provide alternatives. Usage context is present but incomplete.

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