Business Bridge MCP Server

Server Quality Checklist

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Latest release: v0.1.0
Disambiguation5/5
Each tool has a clearly distinct purpose. The Calendly, Shopify, and WordPress tools are neatly separated by platform and operation, with no overlapping functionality.
Naming Consistency4/5
Most tools follow a platform_prefix + verb_noun pattern (e.g., calendly_check_availability). However, the connection tools (connect_calendly, connect_shopify, connect_wordpress) omit the prefix, and generic tools (list_connectors, get_connector_status) use a different structure, breaking full consistency.
Tool Count4/5
13 tools is a reasonable count for a business connector hub covering three platforms plus generic connectivity management. It's slightly on the heavier side but not excessive.
Completeness2/5
The tools only provide read operations for Shopify and WordPress (products, orders, inventory, posts, pages, comments) and limited Calendly functionality (availability check, event types). Missing create, update, delete operations for all platforms, which agents would need for full workflows.
Average 3.6/5 across 13 of 13 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
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```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
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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

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must fully convey behavioral traits. It only states that posts are retrieved ('abrufen') but lacks details on permissions, rate limits, side effects, or response structure. The read-only nature is implied but not explicitly confirmed.
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 extremely concise: a single sentence for purpose followed by a brief parameter list. Every part contributes information without redundancy. It is efficiently front-loaded with 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?
Given no annotations, no output schema, and the existence of sibling tools, the description is incomplete. It does not describe return format, pagination, sorting, or error handling. A more complete description would include what the returned posts look like.
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?
Despite 0% schema description coverage, the description adds meaning beyond schema titles. It explains limit's default and maximum, search as an optional filter term, and connector_name as the connector identifier. This compensates well for the lack of schema parameter descriptions.
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 tool retrieves posts from a WordPress site ('Beiträge von einer WordPress-Site abrufen.'). It specifies the verb and resource, but does not differentiate from sibling tools like wordpress_get_pages or wordpress_get_comments, which also retrieve WordPress content.
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 usage guidelines are provided. The description does not indicate when to use this tool over alternatives, nor does it mention prerequisites or exclusions. The agent is left to infer 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.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description must disclose behavioral traits. It only states what the tool shows, but does not confirm it is read-only or mention any side effects, permissions, or rate limits. The agent might infer safety but it's not explicit.
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 long, front-loaded with the main purpose in the first sentence and additional detail in the second. No unnecessary 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?
For a simple list tool with no parameters and no output schema, the description provides a basic understanding. However, it could be more specific about the structure of the returned list (e.g., whether it includes IDs, names, or statuses). Without output schema, the agent must rely on this vague description.
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?
With zero parameters, baseline is 4. The description adds no parameter information, but it is not necessary since the schema is already complete and empty.
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 that the tool lists all available business connectors, including both platforms and configured connections. However, it does not explicitly differentiate itself from sibling tools like get_connector_status, which might also list connectors but with a focus on status.
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 on when to use this tool versus alternatives like get_connector_status or connect_*. The description is purely functional without contextual recommendations.
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 provided; description gives minimal behavioral info (static read operation, limit constraints) but lacks details on authentication, rate limits, or effects.
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?
Short and front-loaded with main purpose; docstring format with Args is efficient. No superfluous text, but could be slightly more structured.
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 2-param tool with no output schema, explanation of parameters and basic function is adequate. Missing details on response format or filtering, but not critical for this simplicity level.
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?
With schema description coverage at 0%, the description compensates by explaining both parameters: connector_name purpose and limit with defaults/max, adding meaning beyond schema titles.
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?
Description clearly states 'Retrieve products from a Shopify store' (German), which is specific and distinct from siblings like shopify_get_inventory or shopify_get_orders.
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 on when to use this tool versus alternatives like shopify_get_inventory or shopify_get_orders. No prerequisites or context provided beyond the basic description.
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 burden of behavioral disclosure. It reveals that api_key is optional and that the REST API must be enabled. However, it does not describe what happens upon success or failure, whether the connection persists, or any side effects beyond establishing a connection.
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 extremely concise, using a short title sentence followed by a prerequisite and bullet-pointed parameter explanations. Every line serves a purpose with no wasted words. The structure is easily parseable by an AI agent.
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 connection-establishment tool with no output schema, the description should ideally mention what the tool returns (e.g., success status, connection identifier). It lacks this information and also does not explain error handling or the state of the connection after invocation. The parameter details are good, but the overall context is incomplete.
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?
Schema description coverage is 0%, but the description provides clear, one-line explanations for all three parameters: connector_name (unique name), site_url (URL with example), and api_key (optional, type: Application Password or JWT Token). This adds meaningful context beyond the schema's bare field names and types.
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 action: 'WordPress-Site verbinden' and 'Richtet eine Verbindung zu einer WordPress-Site ein.' It specifies the resource (WordPress site) and includes a prerequisite (REST API must be enabled). The name and context distinguish it from sibling connect_* tools.
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 mentions a prerequisite (REST API enabled) but provides no guidance on when to use this tool versus alternatives like connect_calendly or connect_shopify. There is no explicit context for when-not-to-use or when to choose another connector.
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?
The description implies a read-only operation ('abrufen'), but no explicit behavioral traits are disclosed beyond that. The limit parameter's default and maximum are stated, which adds some transparency. However, with no annotations, the description does not cover error behavior, authentication needs, or whether results are paginated. Overall, 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise, consisting of a single-sentence purpose and a list of two parameters. No unnecessary words. It is front-loaded with the main action.
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 (2 parameters, no output schema), the description covers the essentials. However, it lacks details on expected output format, potential errors, or any filtering options beyond limit. It is minimally complete but could be more informative.
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 0%, so the description must add meaning. It provides a brief explanation for connector_name and adds default and max value for limit. However, the description for connector_name ('Name des WordPress-Connectors') adds little beyond the schema title. The limit details are helpful but not extensive.
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 it retrieves pages from a WordPress site. The tool name 'get_pages' and the first sentence 'Seiten von einer WordPress-Site abrufen' directly indicate the resource (pages) and action (retrieve). This distinguishes it from siblings like wordpress_get_posts and wordpress_get_comments.
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 on when to use this tool versus alternatives like wordpress_get_posts. There is no mention of prerequisites, context, or scenarios where get_pages is appropriate.
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 exist, so description carries burden. It describes behavior (shows events, gaps are free slots) but does not explicitly state read-only nature, permissions, or side effects. Adequate but could be improved.
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?
Front-loaded with purpose, followed by a brief behavioral note and a well-structured parameter list. Efficient use of sentences, no redundancy. Slightly verbose in parameter section but acceptable.
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 tool with 3 params and no output schema, description covers purpose, parameters, and basic behavior. Lacks return format details, which output schema would provide if present. 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?
Schema description coverage is 0%, but description provides detailed parameter explanations: connector_name as Calendly connector, start/end_time with ISO format examples. Adds meaning beyond schema's title and type.
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?
Description clearly states it checks availability in a time range (Verfügbarkeit in einem Zeitraum prüfen), specifies it shows planned events and free slots as gaps. This is a specific verb-resource combination that distinguishes it from sibling tools like calendly_get_event_types.
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 on when to use this tool versus alternatives. Does not mention when not to use or suggest other tools for different scenarios. Implicitly assumes use for checking free slots, but no explicit context.
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 fully disclose behavioral traits. It does not explicitly state read-only behavior, authentication requirements, or potential side effects. The verb 'abrufen' implies retrieval but is not explicit.
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 concise with two sentences and an Args section. Language is German, which may cause inconsistency with English tool names, but it is clear and front-loaded.
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 has one parameter and no output schema, the description adequately explains it returns active event types with duration and booking URLs. This is sufficient for a simple list tool.
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?
Schema coverage is 0% for the single parameter 'connector_name'. The description adds an Args section explaining it as 'Name des Calendly-Connectors', which adds meaning beyond the schema's title.
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 retrieves event types from Calendly, specifying it shows active types with duration and booking URLs. It distinguishes from sibling 'calendly_check_availability' which checks availability.
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 for listing event types but provides no guidance on when to use vs. alternatives or when not to use. No exclusions or alternative tools mentioned.
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 full burden. It specifies limit constraints (max 50) and status filter options, but does not disclose whether the operation is read-only, any potential side effects, or pagination behavior. The provided details are adequate but not comprehensive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded with the purpose in the first sentence. The parameter list is structured with clear labels and constraints, containing no extraneous information.
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?
As a retrieval tool with no output schema, the description could explain the return format (e.g., fields, ordering). It covers input parameters but lacks information on output structure such as order fields, pagination, or total count. This leaves some context gaps for an agent.
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?
Schema description coverage is 0%, so the description must compensate. It adds meaning to all three parameters: connector_name (purpose), limit (default and max), and status (allowed values). This provides essential context beyond the schema's type and title.
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 verb 'abrufen' (retrieve) and the resource 'Bestellungen aus einem Shopify-Store' (orders from a Shopify store). It distinguishes from sibling tools like shopify_get_inventory and shopify_get_products by specifying the target resource.
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 alternatives (e.g., shopify_get_inventory, shopify_get_products). It only lists parameters without contextualizing selection criteria.
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 provided, so description carries full burden. It adds parameter details like default and max limit, implying read-only behavior. However, it does not disclose auth needs, error scenarios, or whether it modifies data.
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?
Very concise: a single purpose sentence followed by a clear args list. No fluff, front-loaded, every sentence adds value.
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?
Adequate for a simple list tool with 3 parameters. Explains parameters well but lacks information on return format, pagination, or error handling. Since no output schema exists, a note on response structure would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description fully compensates by explaining each parameter: connector_name purpose, limit with default and max, post_id as optional filter. Adds clear meaning beyond the input 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?
Description states verb 'abrufen' (retrieve) and resource 'Kommentare' (comments) from a WordPress site, making purpose clear. However, it does not explicitly differentiate from sibling tools like wordpress_get_posts or wordpress_get_pages, 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 Guidelines2/5
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. It simply describes what it does. Missing context such as preferred over search or filtering capabilities.
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 provided. The description indicates a read-only check, but does not explicitly state no side effects or permissions required. Adequate but not detailed.
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?
Two sentences plus a clearly formatted args list. No waste, front-loaded with main action.
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?
No output schema; description does not detail the return format or fields. Adequate for a simple status check but could be more 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 0% but description adds an example and context for the single parameter, though no additional constraints or format details.
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 checks the status of a specific connector, showing whether it is configured and its settings. This distinguishes it from sibling 'list_connectors' which lists all connectors.
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 a specific connector status check, but does not explicitly state when not to use or contrast with alternatives like list_connectors.
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 behavioral traits. It only states the basic operation (retrieve) but does not mention authentication needs, rate limits, return format, or error handling.
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 extremely concise with two sentences plus parameter details. Every sentence adds value, and the main purpose is front-loaded.
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 two-parameter tool with no output schema, the description covers what the tool does and the parameters. It could mention the return format or error conditions, but is largely complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description provides useful meanings for both parameters: connector_name as the connector name and limit with default and max values, adding significant value beyond the schema.
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 it retrieves inventory levels from Shopify and shows stock for all product variants. It is distinct from sibling tools like shopify_get_orders and shopify_get_products.
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 use when inventory data is needed, but provides no explicit when-to-use guidance or comparisons to alternatives. It lacks exclusions or prerequisites.
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 full burden. It only states that it 'sets up a connection' but does not disclose whether the token is validated, whether the connection is persistent, what side effects occur, or error behavior.
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 very concise with a clear title line, then an explanation, followed by parameter descriptions. Every sentence adds value without redundancy.
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 connection tool, the description covers the core purpose and required inputs but lacks details about the return value, validation checks, or how to disconnect. Given no output schema, more behavioral context would be beneficial.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description fully explains both parameters: connector_name is a unique name, api_key is the Calendly Personal Access Token. This adds necessary meaning beyond the schema names.
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 connects to a Calendly account ('Calendly-Account verbinden') and specifies the required token source. It distinguishes itself from sibling connect tools (connect_shopify, connect_wordpress) by naming the target service.
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 tells what is needed (a Personal Access Token from a specific URL) and implies the tool is used to set up a Calendly connection. However, it does not explicitly state when not to use it or mention alternative tools.
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 full burden. It describes the action of setting up a connection but does not disclose details like whether it overwrites existing connections, performs validation, or has rate limits. The behavior is minimally 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 extremely concise with two sentences plus a parameter list, front-loading the main purpose. Every part is necessary with no redundant words.
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 has 3 required parameters, no output schema, and no annotations, the description adequately explains the purpose and parameters. It mentions the follow-up actions (querying products, orders, inventory), but lacks details on success/error handling or connection lifecycle, which are minor gaps.
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 no descriptions for its properties (0% coverage). The description adds meaning by explaining connector_name as a unique name, store_url as the Shopify store URL, and api_key as the access token, going beyond the schema.
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 ('verbinden' - connect) and resource ('Shopify-Store'), and clearly states the action of establishing a connection. It distinguishes from sibling tools like connect_calendly or connect_wordpress by naming Shopify explicitly.
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 usage context by stating that after connection, products, orders, and inventory can be queried, indicating this tool is a prerequisite for other Shopify tools. However, it does not explicitly state when not to use or provide alternatives.
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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