MCP Advbox Server

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation4/5
Most tools are clearly distinct by resource and action (e.g., list_customers vs get_customer vs create_customer). The only minor overlap is between get_lawsuit_history and get_lawsuit_movements, but descriptions clarify their different scopes.
Naming Consistency5/5
All tools follow a consistent advbox_verb_noun pattern, using standard verbs like list, get, create, and update. There are no mixed naming conventions or vague verbs.
Tool Count4/5
17 tools is slightly heavy for a typical server, but it covers multiple entities (customers, lawsuits, tasks, transactions, settings) in a coherent way. Each tool has a clear role, and the count is justified by the broad domain.
Completeness3/5
Core workflows are covered (create/get/list lawsuits, customers, tasks), but there are gaps: no update or delete for customers and tasks, no transaction detail, and no create/delete for tasks. These omissions could require workarounds but do not break primary use cases.
Average 3.5/5 across 17 of 17 tools scored. Lowest: 2.7/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
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- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
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This repository includes a README.md file.
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{
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}
```
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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. The text only restates the action from the tool name ('Update an existing lawsuit') and offers no information about side effects, whether it does partial or full updates, required permissions, or the nature of the operation beyond the verb, giving the agent almost no behavioral transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence that directly states the tool's purpose. It contains no superfluous words and is easy to parse, earning full marks for conciseness and structure.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 7 parameters, no annotations, and no output schema, the description is severely under-specified. It doesn't explain what happens after updating, what the return value is, or how the update behaves (e.g., whether unspecified fields are left unchanged). This is a mutation tool with minimal guidance, comparable to the update_drive example that also scored a 2.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema documents all 7 parameters with descriptions, so schema coverage is 100%. The tool description adds no additional meaning beyond what the schema already captures, so it appropriately hits the baseline of 3 for relying on the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (update) and the resource (an existing lawsuit in Advbox), which is specific enough to understand the tool's basic function. However, it doesn't distinguish this from sibling tools like advbox_create_lawsuit or advbox_get_lawsuit beyond the verb, so it falls short of a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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, no prerequisites, and no mention of whether it's appropriate for partial updates or only full replacements. The description merely states what it does without contextual usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It only says 'Get', which implies read-only, but does not explain what a 'movement' is, the return format, ordering, pagination, or any other behavioral traits that could affect the agent's expectations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence with no redundant words. It efficiently communicates the core purpose, though it forgoes the opportunity to include valuable context that could be added without becoming verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one well-documented parameter) and clear purpose, the description is minimally adequate. However, the absence of an output schema and any behavioral details leaves questions about the response structure and the exact nature of 'movements', making it incomplete for a fully self-sufficient description.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema fully documents lawsuit_id with 100% coverage ('Lawsuit ID'), so the baseline is 3. The description adds no additional meaning beyond the schema, neither clarifying the parameter's format nor its role in the request.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get') and resource ('movements/updates of a specific lawsuit'), making the core purpose understandable. However, it does not distinguish itself from sibling tools like advbox_get_lawsuit_history or advbox_get_last_movements, so it falls short of a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus similar alternatives. There is no mention of use cases, prerequisites, or exclusions, leaving the agent to infer the appropriate context from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description alone must convey behavioral traits. It only restates the tool's basic function and gives no information about return format, error behavior, ordering, pagination, or permission requirements. The description adds no transparency beyond what the name implies.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no filler words. It is as concise as possible while conveying the core action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no output schema and no annotations, the description fails to explain what a 'publication' is, the nature of the response, or any edge cases. It is adequate only for conveying the high-level purpose, but lacks context on behavior and results, making it incomplete for an agent to reliably use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already describes lawsuit_id as an integer 'Lawsuit ID' with 100% coverage. The description doesn't add any additional semantic detail beyond acknowledging the lawsuit context, so the schema carries the explanatory weight. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'Get' with a clear resource 'publications' and scope 'for a specific lawsuit', distinguishing it from sibling tools like get_lawsuit or get_lawsuit_history. It is unambiguous and action-oriented.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided about when to use this tool versus alternatives, or any prerequisites such as whether a lawsuit must exist. There is no mention of exclusions or fallback tools, leaving the agent without direction on selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It only states 'Create', implying a write operation, but does not explain side effects, authentication needs, validation rules, or what happens if the lawsuit does not exist. This lack of detail leaves significant ambiguity for 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence that immediately conveys the core action and resource. No filler words or redundant phrasing, making it highly efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple create operation with fully described parameters, the description is minimally adequate. However, it lacks any mention of required context like the need for an existing lawsuit or the meaning of a 'movement' in this domain. With no annotations or output schema, this gap leaves the agent to infer critical details from the tool name alone.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the parameter semantics are already fully documented in the input schema. The description adds no additional context about parameter usage or relationships, meeting the baseline but not exceeding it.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Create' and the resource 'movement/update for a lawsuit', making it evident this tool adds a new record associated with a case. It distinguishes itself from related siblings like advbox_create_lawsuit and advbox_update_lawsuit by referring to 'movement', though the term 'movement/update' is slightly ambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 or any prerequisites such as requiring an existing lawsuit. The description is a bare statement of functionality and does not mention typical workflows or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure, but it only states 'Get a specific customer by ID.' It does not mention read-only nature explicitly, error handling, response format, or any side effects, leaving significant behavioral ambiguity.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence that is easy to scan. It avoids unnecessary detail but is extremely brief, which while concise, might under-specify the tool's behavior.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple getter with one parameter and no output schema, the description is minimally adequate but lacks information about return value, error conditions (e.g., what happens if the ID does not exist), or any access prerequisites. It does not fully prepare the agent for invocation outcomes.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, and the parameter 'id' is already described as 'Customer ID.' The description adds no additional semantic meaning beyond what the schema provides, which is consistent with the baseline score for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Get') and resource ('a specific customer by ID'), clearly distinguishing it from sibling tools like list_customers. It unambiguously identifies the tool's function and scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not provide any guidance on when to use this tool versus alternatives such as advbox_list_customers. It gives no context about typical use cases, prerequisites, or conditions where this tool is preferred.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states the creation action without mentioning permissions, side effects, return values, or reversibility. For a mutating operation, this is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence that clearly states the action and required inputs. It is front-loaded with the primary purpose and contains no superfluous information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 14 parameters, no output schema, and no annotations, this description is too minimal. It lacks usage context, behavioral details, and return format. Although the schema covers parameter descriptions, the overall description does not provide sufficient context for an agent to fully understand when and how to use the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so all 14 parameters have descriptions. The description repeats the required parameters (users_id, customers_origins_id, name) but adds no extra meaning beyond what the schema already provides. Baseline 3 applies because the schema handles parameter semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb and resource: 'Create a new customer in Advbox.' It clearly identifies the action and the target entity, and the required fields add specificity. This distinguishes it from sibling tools like advbox_create_movement or advbox_create_task by naming the customer resource.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description states prerequisites ('Requires user ID, origin ID, and customer name') but does not explicitly provide when-to-use guidance or mention alternatives. Usage is implied by the action, but no exclusions or alternative tool references are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden of behavioral disclosure. It indicates a create operation (implying mutation) but does not mention side effects, reversibility, permissions, return values, or error behavior. This is a significant gap for a mutation tool with no annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that front-loads the core purpose ('Create a new task/appointment in Advbox') and then lists key requirements. It is efficient and free of unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 14 parameters, no annotations, and no output schema, the description is too thin. It identifies required fields but does not explain the return value, success/failure behavior, or any nuances about optional parameters. The schema covers parameter semantics, but the overall context for an agent is incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description lists required fields (creator ID, guests, task type, lawsuit, start date) which map directly to schema properties, but it adds no additional semantic meaning beyond what the schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool creates a new task/appointment in Advbox, using a specific verb and resource. It distinguishes from sibling creation tools like advbox_create_movement, advbox_create_customer, and advbox_create_lawsuit by explicitly naming the entity type.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context by listing required fields, but it does not explicitly state when to use this tool over alternatives or provide exclusions. The use case is reasonably clear from the tool name and description, but no explicit guidance is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits on its own. It merely states 'Get' with no elaboration on return values, error handling (e.g., if the ID is not found), or any side effects. For a read-only credential, the bare action is insufficient; the agent cannot anticipate what to expect on success or failure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that immediately states the action, resource, and target. It contains zero redundant or filler content, making it perfectly concise for the simple tool it describes.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with one parameter and no output schema or annotations, the description covers the basic operation but omits any information about the return value or failure behavior. The agent knows what the tool does but not what to expect back, which is a notable gap for a retrieval operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already covers the single parameter 'id' with the description 'Lawsuit ID', and schema description coverage is 100%. The description adds no additional meaning beyond what the schema provides, so the baseline of 3 applies per rubric rules.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'Get' with the resource 'lawsuit' and clearly identifies the scope as 'by ID from Advbox'. This distinguishes it from sibling tools like list_lawsuits, create_lawsuit, update_lawsuit, and get_lawsuit_history, leaving no ambiguity about whether it retrieves a single existing record versus performing other operations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'specific lawsuit by ID' implies this tool is for retrieving a single record when the ID is known, which contrasts with list_lawsuits for listing all. However, no explicit guidance is given about when to prefer this over alternatives, nor are there prerequisites or exclusions mentioned. The usage is inferred rather than directly stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of behavioral disclosure. It adds the useful trait 'Returns paginated results,' which is not fully explicit in the schema. However, it omits other behavioral aspects like read-only nature, auth requirements, or filter combination behavior, so it is only partially transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the action, and every phrase adds value—the filter categories and pagination notice are substantive. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has 20 parameters and no output schema, yet the description only covers the core action and pagination. It does not explain return fields, how filters interact, ordering, or other contextual details. Adequate but leaves meaningful gaps for such a complex tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description briefly references filter groups like customer, process number, dates, stage, and responsible, but does not add syntax, combination rules, or default behavior beyond what the schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'List lawsuits from Advbox' with specific verb+resource. It distinguishes itself from sibling tools like advbox_get_lawsuit by indicating a listing (plural) rather than a single retrieval, and the mention of filter options clarifies its scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance is provided on when to use this tool versus alternatives. While the description implies listing scenarios, it does not mention exclusions or reference siblings (e.g., advising to use advbox_get_lawsuit for a single lawsuit). Lacks clear contextual usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavior itself. It only states that it creates a lawsuit and lists required parameters, but does not mention side effects, permissions, idempotency, or response behavior. For a mutation tool, this is a significant gap in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single efficient sentence that front-loads the core purpose ('Create a new lawsuit in Advbox') and immediately follows with essential requirements. No wasted words and appropriate length for the tool's complexity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having 9 parameters, no annotations, and no output schema, the description is minimal. It does not mention optional parameters (notes, folder, process_number, etc.), return values, or prerequisites beyond required IDs. For a complex create operation, more context is needed for reliable invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, so the schema already explains each parameter. The description adds value by singling out the required parameters (users_id, customers_id, stages_id, type_lawsuits_id) but does not clarify formats, relationships, or optional parameter usage beyond the schema. This aligns with the baseline for high coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Create'), the resource ('a new lawsuit'), and the system ('in Advbox'), which distinguishes it from sibling tools like advbox_update_lawsuit. It also lists the required IDs, making the tool's scope unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'Create a new lawsuit' provides clear context that this tool is for creation, not updates (which are handled by advbox_update_lawsuit). It doesn't explicitly name alternatives or exclusions, but the implied usage is clear enough for an agent to select it appropriately.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 states it 'gets' customers, implying a read operation, but does not disclose return format, pagination, sorting, timezone handling, or any side effects. For a simple read, this is minimal but lacks important behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with no filler. Every word contributes to the purpose, and it is front-loaded with the action and resource.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with no parameters and no output schema, but the description could provide more context, such as what customer fields are returned, whether 'current month' follows a specific timezone, or whether results are ordered. These gaps make it adequate but not complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, and schema coverage is 100%, so the description is not required to explain parameters. The baseline for 0 parameters is 4, and the description does not need to compensate anything here.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Get customers with birthdays in the current month' uses a specific verb ('Get'), identifies the resource ('customers'), and adds a distinct qualifier ('birthdays in the current month') that clearly differentiates it from sibling tools like list_customers and get_customer.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The purpose implies usage (when you need customers with birthdays this month), but there is no explicit guidance on when to use it versus alternatives like list_customers. No when-not or alternative tool is mentioned, so it relies on the agent to infer utility.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry the full burden of behavioral disclosure. It indicates a read operation ('Get') but does not state side effects, return format, authentication requirements, or rate limits. The minimal description adds little beyond the basic verb, leaving the agent without key behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single six-word sentence, 'Get Advbox account settings and configuration.' It is extremely concise, front-loaded, and contains no unnecessary words, every word earning its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter tool with a straightforward getter purpose, the description adequately states the core function. However, there is no output schema and the description does not explain what the returned settings look like or any operational context, making it complete enough for simple use but not deeply informative.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has zero parameters, so schema description coverage is 100%. With no parameters, the description has no parameter semantics to add, and the baseline of 4 applies because there is nothing to clarify.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a clear verb ('Get') and resource ('Advbox account settings and configuration'), making the tool's purpose unambiguous. It also distinguishes from sibling tools like advbox_list_customers and advbox_get_customer, which target different resources.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description offers no explicit guidance on when to use this tool versus alternatives, but the tool name and description strongly imply it is the go-to tool for retrieving account settings. Since no sibling tool covers settings, the usage context is implied rather than explicitly stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry behavioral disclosure. It only says 'comprehensive filter options' and gives no insight into read-only nature, pagination, rate limits, authentication, or default behavior. The 'list' verb implies read-only, but that's not explicitly stated, leaving gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that wastes no words. It efficiently captures the key action and resource, then moves on.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 18 parameters and no output schema, the description is thin. It doesn't mention sorting, pagination, result limits, or any operation-specific behavior. While the schema covers filters, the description offers little beyond the tool name, so it falls short of complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description adds no parameter meaning beyond what the schema already provides; it merely calls filters 'comprehensive'. No extra semantics are given.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb + resource: 'List financial transactions from Advbox'. This clearly distinguishes it from sibling tools that list customers, lawsuits, or tasks. No ambiguity about what the tool does.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The context is clear: this is the go-to tool for listing financial transactions, directly distinguished from siblings by the resource type. However, it lacks explicit 'when to use vs alternatives' guidance or any exclusions, so it doesn't hit the top score.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description should disclose operational details. It adds scope context but does not mention pagination behavior, default ordering, or that 'filter options' are actually not present in the schema beyond limit/offset. Some gaps remain.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single efficient sentence, but the phrase 'with filter options' is misleading since no filter parameters exist beyond pagination. Minor inaccuracy slightly reduces conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read-only tool with full schema coverage and no output schema, the description provides essential scope but omits behavioral details such as result ordering and defaults. It is adequate but not fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema fully describes limit and offset with basic descriptions, so the tool description adds no parameter-specific meaning. Baseline of 3 applies because the schema covers everything and the description doesn't mislead.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Get the latest movements across all lawsuits', using a specific verb and resource scope that distinguishes it from advbox_get_lawsuit_movements, which targets movements for a specific lawsuit.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'across all lawsuits' implies when to use this tool (when broad scope is needed), but it does not explicitly name alternatives or state exclusion criteria. The guidance is clear but implicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of behavioral disclosure. It adds value by mentioning pagination, which is a key behavioral trait. However, it does not disclose authentication requirements, default sorting, filter combination behavior, or response shape beyond 'paginated results', leaving notable gaps for a tool with 14 optional parameters.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, concise, and front-loaded. It conveys the resource, capability, and key feature (paginated results) without wasted words. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 14 optional parameters and no output schema, the description is relatively thin. It mentions filtering and pagination but does not explain how filters combine, whether results have a default order, or what the response includes. The schema covers parameter semantics, so the description is minimally viable but not fully complete for such a complex listing tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description adds only a high-level summary of filters (name, phone, email, location, creation date) and does not provide additional semantics beyond what the schema already describes for each parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists customers from Advbox, with a specific verb ('List') and resource ('customers'), and mentions the primary capabilities (filtering, pagination). It distinguishes itself from siblings like advbox_get_customer (single customer retrieval) and advbox_create_customer (creation) by explicitly indicating a multi-record listing function.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use for customer listing with filtering and pagination, which is clear for selecting this over get_customer or create_customer. However, it does not explicitly name alternatives or state when not to use this tool, so it lacks explicit exclusions but provides adequate context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden of behavioral disclosure. 'Get' implies a read-only operation, which is helpful, but the description does not explain any additional behavior such as return format, ordering, or whether the history includes all statuses. It is minimally transparent but not misleading.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, purposeful sentence that immediately states the tool's function. It contains no redundant words or filler, earning its place efficiently.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one parameter and no output schema, the description is sufficiently complete. It clearly conveys what the tool returns (task history) and the scope (specific lawsuit). While it could mention that the result is a list, the implication is strong enough.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents the only parameter (lawsuit_id) with a clear meaning. The description adds no extra semantic detail beyond what the schema provides, which is acceptable given the baseline of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Get') and clearly identifies the resource ('task history of a specific lawsuit'). It effectively distinguishes this tool from siblings like advbox_get_lawsuit (which retrieves lawsuit details) and advbox_get_lawsuit_movements (which retrieves movements).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description establishes clear context: use this tool to retrieve task history for a specific lawsuit, indicated by the required lawsuit_id parameter. However, it does not explicitly mention alternatives or exclusions, such as using advbox_list_tasks for a broader task list.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must carry the transparency burden. It does disclose the paired date requirement and 90-day maximum range, which is useful. However, it does not explicitly state that the operation is read-only, nor does it mention pagination or return format, though 'List' implies read-only.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences: the first states the purpose, the second provides a critical constraint. Every word earns its place, and the structure is front-loaded with the key action. There is no redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (15 parameters, no output schema, no annotations), the description is succinct but adequately covers the essential context: it states what the tool does and highlights a key restriction (90-day range). The schema covers parameter details, so the description doesn't need to repeat them. It could mention response format, but for a list tool the implied paginated list is sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already documents all 15 parameters (100% coverage), so the baseline is 3. The description adds value beyond the schema by explicitly stating the maximum 90-day date range constraint, which is not present in any parameter description. This gives the agent additional context for constructing valid date filters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a clear verb and resource: 'List tasks/appointments from Advbox.' This precisely identifies the tool's action and scope, and distinguishes it from sibling tools like advbox_list_customers and advbox_list_lawsuits.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context that this is for tasks/appointments and includes a critical usage constraint: date filters require both start and end dates and the date range is limited to 90 days. It doesn't explicitly exclude alternatives, but the tool's name and purpose make the use case obvious.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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