DACIX — The Store for AI Agents

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

With no annotations provided, the description carries the full burden for behavioral disclosure. It mentions a 5-credit cost and lists output elements, implying a safe read operation. However, it does not explicitly state read-only behavior, potential failure modes (e.g., non-public URLs), or rate limiting.

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 that front-loads the core purpose and list deliverables, ending with the credit cost. No filler 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?

For a simple fetch-audit tool with two well-documented parameters and no output schema, the description covers the main output items and cost. Minor gaps: no mention of error handling, timeout, or page size limits.

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 'url' and 'api_key'. The description adds no further parameter meaning; '5 credits' is a cost note, not parameter guidance. Baseline 3 is appropriate as the schema already documents 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 uses 'Full SEO audit of a page' as a specific verb-resource combination and enumerates the exact elements checked (title, meta description, OG tags, headings, links, word count), clearly distinguishing it from sibling tools like web_crawl, web_fetch, and compare_pages.

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 guidance on when to use this tool versus alternatives such as compare_pages or web_crawl. The description does not mention prerequisites, limitations, or suitable contexts beyond the implicit SEO auditing use case.

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 exist, so description must cover behavior. It mentions credit cost and markdown output but lacks details on rate limits, data freshness, or read-only nature.

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?

Singlesentence format is highly concise, front-loads key info (city count, output format, topics, cost) with 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?

For a tool with no output schema, it adequately describes return format (markdown) and scope. Could mention that it is a read operation and clarify api_key purpose.

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 100% of params with brief descriptions. The description adds value by listing example topics (parking, events, etc.) and clarifying 'topic' usage, going 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 provides civic info for cities with specific topics and city count, distinguishing it from sibling tools which are unrelated.

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?

While no explicit when-to-use or alternatives are given, the tool's purpose is clear and no similar tools exist, making guidance implicit.

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 only mentions 'Category tree' and 'free', lacking details about authentication, rate limits, output format, or what happens if no categories exist. Minimal behavioral disclosure.

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 front-loads the core purpose ('Category tree'), adds domain context, and ends with the actionable 'pick a category_id'. 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?

For a parameterless tool with no output schema or annotations, the description is minimally adequate: it states the purpose and use case. However, it omits details about the output structure (list? tree?), which would help an agent parse the result.

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 baseline is 4. The description correctly implies no input is needed, and it does not provide any parameter-specific info. No gap exists since schema coverage is 100%.

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 a 'category tree' and specifies the domain (Romanian classifieds). It explicitly connects to the use case: 'pick a category_id before posting an ad', which distinguishes it from sibling tools like '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 indicates when to use this tool ('before posting an ad'), providing clear context. It does not explicitly state when not to use it or list alternatives, but the sibling tool names and purpose implicitly guide selection.

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 burden. It discloses that the tool fetches multiple pages, compares titles/word counts/previews, and requires 10 credits. It does not mention destructive actions or side effects, but the read-only nature is implied by 'fetch ... compare'. Adding idempotency or safety note would improve score.

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 the core functionality, constraints (2-5 pages), and cost (10 credits). No unnecessary words or redundant 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 2 params, no output schema, and decent description, the tool is adequately explained. However, it could describe the output format (e.g., side-by-side table) or mention that results are read-only. The cost hint is useful, but missing output details slightly reduce 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 100%, so baseline is 3. The description adds context by stating urls should be 2-5 pages and api_key can be obtained via store_register, but the schema already covers these. No additional parameter details 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 the action (fetch, compare), the resource (pages), and the specific items compared (titles, word counts, content previews). It also specifies the range of pages (2-5) and a cost (10 credits), making it distinct from sibling tools like web_fetch or web_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?

The description implies usage when you need to compare page details, but it provides no explicit guidance on when not to use it or mention alternatives. While the cost (10 credits) hints at a non-free operation, there is no comparative advice against other tools.

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 covers key behaviors: ad is real, 90-day listing, returns URL, costs 20 credits if accepted. Could mention rejection case or rate limits.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, front-loaded with purpose and cost. 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?

Adequate for a posting tool with 10 params, no output schema. Covers platform and credit cost but misses pre-requisites (e.g., category_id from classified_categories) and post-posting 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?

Schema coverage is high (90%), so baseline is 3. Description adds platform and credit context but no additional parameter-specific meaning 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 the verb 'Publish', the resource 'real classified ad', platform 'micapublicitate.online', duration '90-day listing', and return value 'public URL'. It distinguishes from siblings as the only ad-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?

Mentions credit cost and conditional charge, but no explicit when-to-use, when-not-to-use, or alternatives like classified_categories as prerequisite.

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 discloses the data returned (net turnover, profit/loss, etc.) and cost (20 credits, charged only if data exists). However, it does not mention authentication requirements (api_key) or rate limits, though these are standard.

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 core purpose and data fields, followed by cost info. Every sentence adds value with no 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?

Given no output schema, the description partially explains returns (multi-year history of specific fields) but does not describe format (e.g., array of objects) or error cases (invalid CUI, no data). Cost info is helpful, but completeness is moderate.

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 is 3. The description adds context by listing returned fields and mentioning multi-year history, but does not elaborate on parameter 'an' (year) usage or error handling. It adds some value but not significantly beyond 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 tool retrieves yearly financials for Romanian companies by CUI, listing specific data fields (net turnover, profit/loss, employees, equity, assets, debt) and mentions multi-year history. This distinguishes it from sibling tools like ro_company_lookup (basic info) and ro_company_search (name-based 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?

The description implies when to use (for financial data by CUI) but does not explicitly guide on when not to use or compare to alternatives like ro_company_lookup. It mentions cost, which helps with decision-making, but lacks explicit usage context.

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 responsibility. It mentions pagination and credit cost but does not disclose default behavior when no filters are applied (e.g., returns all companies?), error conditions, rate limits, or authentication requirements beyond the schema. The description is too sparse for safe invocation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is very concise at one sentence, front-loaded with 'Browse Romanian companies with filters'. It efficiently lists the key features. However, it might be too short to be fully informative.

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 listing tool with multiple filters, pagination, and a required API key, the description is incomplete. It lacks details on default behavior, pagination semantics (how page/per_page work), credit cost per page without clarifying cumulative costs, and expected response format. No output schema exists, so additional 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?

The description maps filter names to parameters (judet, radiata, tva), adding minimal clarification beyond the schema descriptions. Schema coverage is 67% (page and per_page lack descriptions), and the description mentions pagination but does not explain the page/per_page parameters. It adds some value but leaves gaps.

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 'Browse Romanian companies with filters' and lists specific filters (judet, radiata, tva). It distinguishes from sibling tools like ro_company_lookup (single lookup) and ro_company_search (search by name) by focusing on browsing with filters and pagination.

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 alternatives. It does not mention that for a single company lookup one should use ro_company_lookup or for name-based search use ro_company_search. The description lacks context for tool selection.

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 must cover behavioral traits. It mentions credits and charging condition, but does not state if the operation is read-only, auth requirements beyond api_key, or behavior on not found.

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 conveys purpose, fields, coverage, and cost. Front-loaded with key info. Slightly lacking in structure for complex details but adequate for its length.

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 lookup tool with only 2 parameters and no output schema, the description covers core functionality, return fields, and cost. Lacks error behavior details but is reasonably 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?

Schema coverage is 100% with descriptions for both parameters. The description adds no parameter-level detail beyond 'by CUI (tax ID)' which is already in schema. Baseline 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 retrieves a Romanian company registry profile by CUI, listing specific fields like legal name, status, VAT, CAEN, address. It specifies the resource and action but does not explicitly distinguish from sibling tools like 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?

No guidance on when to use this tool versus alternatives (e.g., when to use ro_company_search vs this lookup). No prerequisites or exclusions mentioned.

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 provides basic behavioral info: it is a search tool that returns specific fields and costs credits. It does not disclose rate limits, data freshness, or whether the operation is read-only (though implied). No contradiction with annotations.

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 a cost note. It is front-loaded with essential information, no fluff, and every piece contributes to understanding the tool.

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 and no annotations, the description tells what is returned and the cost, but lacks details on number of results, pagination, or sorting. For a simple search tool, it is adequate but not fully comprehensive.

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 schema already has 100% coverage, but the description adds context: query is a 'company name fragment' (not exact match), and api_key is a DACIX key obtained via store_register. This aids correct parameter usage beyond 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 states the verb 'Search', the resource 'Romanian companies', and specifies that it searches by name. It lists the returned information (CUI, legal form, county, active/struck-off) and the cost (10 credits). This clearly differentiates it from sibling tools like ro_company_lookup 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 usage by saying 'Search Romanian companies by name', which suggests when to use it (when you have a company name fragment). However, it does not explicitly state when not to use it or mention alternative tools for different search criteria (e.g., by CUI or address).

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 adds '10 credits' (a cost behavior) but does not mention any other behavioral traits such as authentication requirements (though api_key parameter exists in schema), rate limits, or what happens if no companies are found. The description is insufficient for a tool without annotations.

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 core purpose. The parenthetical adds context without redundancy. Every word earns its place, and the length is appropriate for the tool's complexity.

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, the description does not explain return values. It covers the basic purpose but omits details about optional parameter interactions (e.g., how strada and numar work together) and the output format. The tool has 4 parameters, so more contextual explanation 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 description coverage is 100%, with all parameters having descriptions (e.g., 'City, e.g. cluj', 'Street number (optional)'). The tool description adds '10 credits' but no additional parameter meaning. Baseline 3 is appropriate as the schema already provides parameter 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 states the action ('find') and the specific resource ('every Romanian company registered at an address'), with a parenthetical clarifying the use case ('due diligence: who is registered here?'). It distinguishes from sibling tools like 'ro_company_search' (likely by other criteria) and 'ro_company_lookup' (by ID).

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 at a specific address, but does not explicitly state when to avoid this tool or mention alternative tools (e.g., ro_company_search for other search criteria). No exclusionary guidance is 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. 'Check' implies read-only, but it does not explicitly state that the operation has no side effects or requires authentication beyond the API key. The description is adequate but lacks explicit behavioral guarantees.

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, front-loaded sentence with no extraneous words. It immediately communicates the tool's 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?

Given the simplicity (single param, no output schema), the description covers the return items (balance, templates). It could mention response format but is complete enough for a straightforward 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?

Schema description coverage is 100% (api_key well described). The tool description adds minimal value beyond the schema: it mentions account checking but does not further detail the parameter's purpose or constraints.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb ('Check') and resource ('DACIX account'), listing exact items ('credit balance and owned templates'). This clearly distinguishes it from siblings like store_buy (buying) and store_catalog (listing all templates).

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 when you need to view account details (balance/templates). It provides clear context but does not explicitly state when not to use it or name alternative tools.

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 discloses the key behavior: returns a Stripe checkout URL for payment, automatic fulfillment after payment, and suggests confirming with store_order_status. It does not mention potential side effects or authorization beyond the api_key, but it covers the main workflow adequately.

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 at two sentences, with no wasted words. The most important information ('Buy a product') is front-loaded, and every sentence adds 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 the tool's moderate complexity (3 parameters, no output schema, no annotations), the description covers the essential behavior and next steps. It lacks error handling details or elaboration on the checkout process, but it is sufficient for an AI agent to use the 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 description does not add any parameter-level details beyond what is already in the input schema. The schema covers 67% of parameters with descriptions, and the description restates nothing about parameters. The baseline of 3 is appropriate given the 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 starts with 'Buy a product' which clearly states the action and resource. It then explains the specific behavior (returns Stripe checkout URL) and distinguishes from sibling tools like store_catalog and store_order_status by mentioning the checkout process and automatic fulfillment.

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 guidance on how to use the tool's output: open the checkout URL or give it to the user to pay. It also advises confirming fulfillment with store_order_status. While it doesn't explicitly state when not to use the tool, the context is sufficient for an agent to decide.

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 bears full burden. It discloses the read-only nature ('List everything...') and the lack of auth requirement. For a simple listing tool, this is transparent, though it omits potential details like response format or pagination.

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 extraneous words. The description is front-loaded with the main purpose and includes specific detail (domain name, item types, auth requirement).

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 (zero parameters, no output schema), the description provides essential context: what the tool lists and that no auth is needed. It could mention how the results relate to sibling tools like store_buy, but 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?

Schema description coverage is 100% (no parameters exist). The description adds no parameter-specific information, which is acceptable as there are none. 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 explicitly states it lists everything for sale at a specific domain, specifying the types of items (agent templates and API credit packs). It distinguishes from siblings like store_buy (purchasing) and store_download_template (downloading).

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 clearly implies this tool is for browsing available items before purchase, and notes that no authentication is needed. While it doesn't explicitly list when not to use it, the context from sibling tools makes it straightforward.

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 does not disclose behavioral traits like authentication requirements, error handling for non-purchased items, or rate limits.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Single sentence conveying essential purpose and content; no redundant 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?

Lacks details on success/failure behavior, required prior state (purchase), and return format; inadequate for a tool with no 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?

With 50% schema description coverage, description adds no extra meaning for the undocumented product_id parameter. api_key description already exists in 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 the verb 'Download' and resource 'purchased agent template', specifying contents as 'full JSON: system prompt, tools, schemas'. It distinguishes from siblings 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 vs alternatives (e.g., store_buy, store_catalog). No prerequisites or conditions mentioned.

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 fully bears the transparency burden. It indicates a read operation ('check') and the expected state transition, which is sufficient for a simple lookup. No contradictions.

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 10 words, front-loaded with verb and resource. 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?

No output schema exists, so the description should hint at return values. It does not. Additionally, it lacks details on error handling or prerequisites, making it 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?

The description does not mention or explain any parameters. Schema coverage is 50% (api_key described, order_id not), but the description adds no value to parameter understanding.

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 'check' and the resource 'order status', with specific context 'after payment (pending → paid)'. This distinguishes it from sibling tools like store_buy or store_register.

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 context (check after payment, pending to paid transition) but does not explicitly state when not to use it or mention alternatives. It gives sufficient guidance for typical usage.

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 the description must cover behavioral traits. It mentions account creation and free credits, but omits side effects like email uniqueness checks, password strength requirements beyond 'min 8 characters', or error handling. The description gives a reasonable overview but lacks depth 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 long, front-loads the action ('Create a DACIX account'), and conveys essential information without redundancy. Every sentence is meaningful.

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, the description partially explains the return value (API key, credits) but lacks details on the response format, error states, or expected prerequisites (e.g., email not already registered). The tool's complexity (2 parameters, no nested objects) reduces the bar, but more completeness is needed for a critical account creation function.

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. The description does not add extra meaning to the 'email' and 'password' parameters beyond what the schema already provides (e.g., format, examples). The mention of API key output is not parameter-specific.

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 creates a DACIX account and provides an API key plus free trial credits. It distinguishes itself from sibling tools like store_account (account management) and store_buy (purchasing) by specifying the registration and credential generation purpose.

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 this tool is a prerequisite for other tools by stating 'Store the key — it authenticates every other tool here.' However, it does not explicitly mention when not to use it (e.g., if already registered). This is a minor gap.

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 discloses that fetching is server-side, costs 5 credits, and requires an API key. However, it does not mention rate limits, error handling, or behavior for non-public URLs. The 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 a single sentence that conveys all essential information without redundancy. It is front-loaded with the core purpose and includes the credit cost efficiently.

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 lacks details about the output format, such as whether text is returned as plain text or structured data. No information about error responses or pagination. Given no output schema, the description should clarify the return value more precisely.

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 has 100% description coverage for its two parameters, so the baseline is 3. The description does not add extra meaning beyond the schema, such as format or constraints for the URL or API key. It remains at 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 (fetch), resource (any public web page), and output (clean readable text). It specifies server-side execution, which distinguishes it from client-side fetches. However, it does not explicitly differentiate from the sibling tool 'web_fetch', which may have similar functionality.

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 but provides no guidance on when to use this tool versus alternatives like 'web_fetch' or 'web_search'. There is no information about prerequisites, limitations, or 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 provided, so the description carries the full burden. It discloses that scripts, styles, and nav are stripped, and provides word count and credit cost. However, it does not mention error handling, rate limits, or size restrictions.

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 key action and output, with 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?

For a simple 2-parameter tool with no output schema, the description covers the main purpose, output type, and cost. However, it could be more explicit about the return format (e.g., JSON or plain text) and any limitations.

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 the description adds minimal value beyond the schema. It mentions 'enhanced text extraction' but does not elaborate on parameters beyond what the schema already provides.

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 'Fetch' and the resource 'a page', and specifies the enhanced text extraction output. It distinguishes from sibling tools like web_crawl and web_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?

The description implies fetching a single page with text extraction but does not explicitly state when to use this tool versus alternatives like web_crawl or web_search. No exclusion criteria or prerequisites are mentioned.

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 output format (titles, URLs, snippets) and credit cost, but no annotations exist; additional details like idempotency or error handling would improve 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?

Single sentence plus cost note is extremely concise and front-loaded with essential 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 simple search tool, the description covers output and cost; missing details like result ordering or language/region defaults, but overall sufficient.

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 descriptions cover all parameters (100%), but the tool description adds no extra meaning beyond what the schema already provides, so baseline score 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?

Description clearly states it searches the web via DuckDuckGo and returns structured results, effectively distinguishing it from sibling tools like web_crawl or web_fetch.

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 for general web search and mentions cost, but lacks explicit guidance on when to use versus alternatives or constraints like rate limits or required permissions.

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