CData Sync MCP Server

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by CDataSoftware

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Server Quality Checklist

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Latest release: v1.0.0
Disambiguation4/5
Most tools have distinct purposes targeting specific resources like jobs, connections, or tables, but some overlap exists. For example, get_connection_tables and get_job_tables both list tables, though the latter is filtered for job compatibility, which could cause minor confusion. Similarly, read_jobs and read_history both provide job-related information, but their scopes are differentiated by current status versus historical records.
Naming Consistency5/5
Tool names follow a highly consistent verb_noun pattern throughout, such as cancel_job, configure_sync_server, and read_connections. All tools use snake_case with clear action prefixes like 'read', 'write', 'get', 'execute', and 'cancel', making the naming predictable and easy to understand across the set.
Tool Count3/5
With 24 tools, the count feels heavy for a data synchronization server, bordering on excessive. While the domain is complex, covering jobs, connections, tasks, and users, the number of tools could overwhelm agents and lead to decision paralysis, suggesting some consolidation might improve usability without losing functionality.
Completeness5/5
The tool set provides comprehensive CRUD and lifecycle coverage for the CData Sync domain, including jobs, connections, tasks, transformations, users, and workspaces. It supports full management from configuration and execution to monitoring and cleanup, with no obvious gaps that would hinder agent workflows, ensuring complete operational coverage.
Average 3.9/5 across 24 of 24 tools scored. Lowest: 3.2/5.
See the Tool Scores section below for per-tool breakdowns.
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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.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
Add a glama.json file to provide metadata about your server.
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If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
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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

Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses the return types (list, get, count) and common errors including permission issues, which adds useful behavioral context. However, it doesn't mention rate limits, pagination behavior (beyond the 'top' parameter), caching, or whether this is a read-only operation (implied by name but not stated).
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 well-structured with clear sections (purpose, returns, errors) and uses bullet points effectively. Every sentence earns its place, though the 'COMMON ERRORS' section could be more concise. The front-loaded purpose statement is clear, making it appropriately sized for the tool's complexity.
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 7 parameters with full schema coverage but no annotations or output schema, the description provides adequate context for a read operation. It explains what the tool accesses and the return structure, but doesn't fully address behavioral aspects like authentication requirements, rate limits, or how it differs from other read_* tools. The error information is helpful but doesn't compensate for all missing context.
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 all 7 parameters thoroughly. The description adds no parameter-specific information beyond what's in the schema. The 'RETURNS' section maps actions to outcomes but doesn't explain parameter interactions or provide additional semantic context beyond the schema's 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 'Access data transformations that run SQL in the destination (ELT pattern)', which specifies the verb ('Access'), resource ('data transformations'), and technical context ('ELT pattern'). However, it doesn't explicitly distinguish this read operation from its sibling 'write_transformations' tool, though the naming convention implies the distinction.
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. While it mentions 'ELT pattern' for context, it doesn't explain when to choose this over other read_* tools (like read_connections or read_jobs) or how it relates to write_transformations. The 'COMMON ERRORS' section offers troubleshooting hints but not usage guidelines.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
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 effectively adds context beyond the input schema: it details user roles (e.g., 'cdata_admin'), return types (list, get, count), and common errors with explanations (e.g., 'Access denied' requires admin role). This covers key behavioral aspects like permissions and error handling, though it could mention rate limits or pagination.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is structured with sections (ROLES, RETURNS, COMMON ERRORS), which aids readability, but it's somewhat verbose and could be more front-loaded. Sentences like 'Access CData Sync user accounts and their permissions' are clear, but the detailed lists and error explanations add bulk without always being essential. It's adequately sized but not optimally concise.
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 (7 parameters, no annotations, no output schema), the description does a good job of adding context. It covers roles, return types, and errors, which compensates for the lack of annotations and output schema. However, it could be more complete by explicitly stating it's a read-only tool or mentioning sibling tools, but overall it's fairly comprehensive for the given context.
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 description coverage is 100%, so the schema already documents all 7 parameters thoroughly. The description adds no parameter-specific information beyond what's in the schema. However, it implies the tool's actions (list, get, count) and roles, which loosely relate to parameters like 'action' and 'filter', but doesn't provide additional syntax or usage details. Baseline 3 is appropriate as the schema does the heavy lifting.
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's purpose as 'Access CData Sync user accounts and their permissions,' which is a specific verb+resource combination. However, it doesn't explicitly differentiate from sibling tools like 'write_users' or other 'read_' tools, though the 'Access' verb implies read-only operations. The purpose is clear but lacks sibling differentiation.
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. It doesn't mention sibling tools like 'write_users' or other 'read_' tools, nor does it specify prerequisites or contexts for usage. The 'COMMON ERRORS' section hints at admin requirements but doesn't offer proactive usage advice.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
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 effectively adds value by specifying the return type ('Certificate details with confirmation of upload') and listing common errors that reveal constraints like format requirements, expiration checks, duplication handling, and store type validation. This provides useful context beyond basic functionality, though it could be more comprehensive about side effects or permissions.
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 well-structured with clear sections ('RETURNS' and 'COMMON ERRORS') and front-loaded key information. It's appropriately sized, with no redundant sentences, though the error list is detailed but necessary for clarity. A minor improvement could be integrating the sections more seamlessly.
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 (uploading certificates with security implications), no annotations, and no output schema, the description does a good job of covering essential aspects: purpose, return values, and common errors. It compensates well for the lack of structured fields, though it could be more complete by mentioning authentication requirements or rate limits.
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 description coverage is 100%, so the schema already documents all parameters thoroughly. The description doesn't add any parameter-specific information beyond what's in the schema, such as explaining interactions between parameters or providing examples. However, the 'COMMON ERRORS' section implicitly clarifies parameter constraints (e.g., 'data' must be base64-encoded), which offers some additional context.
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's purpose: 'Upload SSL/TLS certificates for secure connections.' This specifies the verb ('upload') and resource ('SSL/TLS certificates') with context about their purpose ('for secure connections'). However, it doesn't explicitly differentiate from its sibling 'read_certificates' beyond the obvious upload vs. read distinction, which is why it doesn't reach 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 alternatives. It doesn't mention prerequisites, such as needing specific permissions or workspace access, or compare it to sibling tools like 'write_connections' or 'write_workspaces' that might handle related operations. The 'COMMON ERRORS' section hints at usage constraints but doesn't explicitly state when to use the tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden and does well by disclosing: 1) the three return value types (list, count, get), 2) common errors with explanations, and 3) retention policy implications ('Logs purged'). It doesn't mention authentication requirements, rate limits, or pagination behavior, but provides substantial behavioral context beyond basic functionality.
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 perfectly structured and concise: purpose statement first, followed by clearly labeled RETURN and COMMON ERRORS sections. Every sentence adds value - no repetition or wasted words. The three-section format makes it easy to scan and understand.
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 7-parameter tool with no annotations and no output schema, the description provides good context: clear purpose, return value explanation, and error handling. It doesn't explain the relationship between the three action types or provide examples of typical use cases, but covers the essentials well given the complexity.
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?
With 100% schema description coverage, the schema already documents all 7 parameters thoroughly. The description adds no parameter-specific information beyond what's in the schema. The baseline of 3 is appropriate when the schema does all the parameter documentation work.
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's purpose as 'Access API request logs for auditing, debugging, and compliance' - a specific verb ('access') with resource ('API request logs') and context (three use cases). However, it doesn't explicitly differentiate from sibling tools like 'read_history' or 'read_jobs' that might also read different types of logs.
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. With multiple 'read_' sibling tools (read_history, read_jobs, read_tasks, etc.), there's no indication of what distinguishes API request logs from other log types or when this specific tool is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
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 adds valuable context beyond basic functionality: the 'RETURNS' section details output types, and the 'COMMON ERRORS' section discloses potential issues like 'Job not found,' 'No logs available,' and 'Access denied,' which help the agent understand error handling and permission requirements. However, it doesn't cover rate limits, pagination details, or mutation effects, leaving some behavioral gaps.
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 well-structured with clear sections ('RETURNS' and 'COMMON ERRORS'), making it easy to scan. It's appropriately sized for the tool's complexity, with each sentence adding value, such as error explanations. However, it could be more front-loaded by stating the core purpose more prominently, and some redundancy exists between the description and schema (e.g., 'action' values).
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 (11 parameters, no output schema, no annotations), the description does a good job of adding context: it explains return types and common errors, which compensates for the lack of output schema and annotations. However, it doesn't fully address all contextual needs, such as detailing mutation risks (though implied as read-only) or providing examples for complex parameters like 'filter,' leaving minor gaps.
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 description coverage is 100%, so the input schema already documents all 11 parameters thoroughly. The description adds no additional parameter semantics beyond what's in the schema, such as explaining 'action' values or 'filter' usage in more detail. According to the rules, with high schema coverage, the baseline is 3, and the description doesn't compensate with extra insights.
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's purpose as 'Access and monitor data replication jobs that move data from source to destination,' which specifies the verb ('access and monitor'), resource ('data replication jobs'), and scope. However, it doesn't explicitly differentiate from sibling tools like 'read_history' or 'read_tasks,' which might also involve monitoring or accessing job-related data, so it's not fully sibling-distinctive.
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 through the 'RETURNS' section, which lists operations like 'list,' 'get,' 'status,' etc., suggesting when to use this tool for different monitoring tasks. However, it lacks explicit guidance on when to use this tool versus alternatives like 'read_history' or 'execute_job,' and doesn't mention prerequisites or exclusions, leaving usage context partially implied.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden and does well by explaining what the tool returns (list, get, count operations), common errors with troubleshooting advice, and workspace functionality. It doesn't cover rate limits, authentication requirements, or pagination behavior, but provides substantial operational context.
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?
Well-structured with clear sections (purpose, workspace context, returns, errors). The information is front-loaded and organized, though the workspace explanation could be more concise. Every section adds value for understanding the tool's functionality.
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 read tool with 7 parameters, 100% schema coverage, and no output schema, the description provides good context about what workspaces are, three distinct operations, and common errors. It covers the essential 'what' and 'why' though could benefit from more usage guidance relative to sibling tools.
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 fully documents all 7 parameters. The description doesn't add parameter-specific information beyond what's in the schema, but the 'RETURNS' section clarifies the three action types, which aligns with the 'action' parameter enum. Baseline 3 is appropriate when schema does the heavy lifting.
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 'Access CData Sync workspaces for multi-tenant organization' and explains what workspaces are used for (organizing jobs, connections, transformations, isolating resources). It distinguishes from siblings like 'write_workspaces' by being a read operation, though it doesn't explicitly contrast with other read_* tools.
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 through the 'RETURNS' section showing three actions (list, get, count) and mentions multi-tenant deployments context. However, it doesn't provide explicit guidance on when to choose this tool over other read_* tools or when to use specific actions versus alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
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 effectively describes key behaviors: naming requirements (uniqueness, character restrictions, case-sensitivity), return values for each action type, and common error conditions with explanations. This provides substantial operational context beyond basic functionality.
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 well-structured with clear sections (purpose, naming rules, returns, errors) and uses bullet points for readability. While comprehensive, every sentence adds value - no redundant information. It could be slightly more concise by integrating some sections, but overall it's efficiently organized.
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 mutation tool with no annotations and no output schema, the description provides excellent coverage of behavioral aspects (naming rules, returns, errors). It compensates well for the lack of structured metadata. The main gap is the absence of usage guidance relative to sibling tools, but otherwise it's quite complete for operational understanding.
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 all parameters thoroughly. The description adds some context about workspace naming requirements that relates to the 'name' and 'newName' parameters, but doesn't provide additional parameter semantics beyond what's in the schema descriptions. This meets the baseline 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 clearly states the tool's purpose with specific verbs ('Create, update, or delete') and resource ('CData Sync workspaces'), making it immediately understandable. It distinguishes itself from sibling tools like 'read_workspaces' by focusing on write operations rather than read operations.
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. It doesn't mention prerequisites, when to choose create/update/delete, or how it relates to sibling tools like 'write_users' or 'read_workspaces'. The agent must infer usage from the description alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden and does well by disclosing return format ('Array of certificate objects with name, subject, expiration, and thumbprint') and common errors ('No certificates found', 'Access denied'). It doesn't mention pagination behavior, rate limits, or authentication requirements, but provides substantial behavioral context beyond basic purpose.
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 efficiently structured with clear sections (purpose, returns, common errors) using minimal sentences. Each section earns its place by providing distinct, valuable information without redundancy or unnecessary elaboration.
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 read-only listing tool with 100% schema coverage but no output schema, the description provides good context: clear purpose, return format, and error conditions. It could improve by mentioning pagination behavior (implied by top/skip parameters) or workspace context, but covers the essentials well given the tool's moderate complexity.
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 all 6 parameters thoroughly. The description adds no parameter-specific information beyond what's in the schema. Baseline 3 is appropriate when schema does the heavy lifting, though the description could have explained parameter relationships or usage patterns.
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 purpose with specific verb ('List') and resource ('SSL/TLS certificates used for secure connections'). It distinguishes itself from sibling tools like 'write_certificates' by focusing on read-only listing rather than creation/modification.
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. While it distinguishes from 'write_certificates' by implication, there's no explicit comparison to other read_* tools (e.g., read_connections, read_jobs) or explanation of when certificate listing is appropriate versus other operations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden and does well by disclosing key behavioral traits: authentication requirements ('If not authenticated with CData Sync, you will be prompted for credentials'), constraints on running jobs, and the need to use exact table names. It also mentions job types and task addition timing, adding valuable operational context beyond basic functionality.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is moderately concise but could be more front-loaded; it starts with core functionality but includes detailed job type explanations that might be better in parameter documentation. Some sentences, like the job type list, feel redundant given the schema. However, it avoids excessive verbosity and stays focused on key points.
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 high complexity (32 parameters, no annotations, no output schema), the description provides adequate context for a write operation tool by covering purpose, constraints, and authentication. However, it lacks details on error responses, return values, or interaction with sibling tools like execute_job, leaving some gaps for a tool of this scope.
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 description coverage is 100%, so the schema already documents all 32 parameters thoroughly. The description adds minimal parameter-specific information beyond restating job types from the schema and emphasizing exact table name usage, which is partially covered in the schema's queries description. This meets the baseline of 3 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 clearly states the tool's purpose as 'Create, modify, or delete data replication jobs' with specific verbs and resource, and distinguishes it from siblings by mentioning job orchestration with scheduling, transformations, error handling, and notifications. It explicitly differentiates from read-only siblings like read_jobs by indicating write operations.
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 for when to use this tool (for managing replication jobs) and includes important constraints like 'Cannot modify/delete running jobs' and 'Add tasks after creating the job.' However, it doesn't explicitly mention when to use alternatives like execute_job for running jobs or read_jobs for viewing jobs, though the purpose implies this distinction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden and does well. It discloses critical behavioral traits: the 'update' action actually creates a new task (counterintuitive behavior), returns different outputs per action, and lists common errors with specific guidance. It also mentions sequential execution by index and workspace override capability.
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?
Well-structured with clear sections (IMPORTANT, RETURNS, COMMON ERRORS) and front-loaded purpose. Some redundancy exists (table name guidance appears in multiple places), but overall efficient with every sentence earning its place.
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 complex 7-parameter mutation tool with no annotations and no output schema, the description provides substantial context: behavioral quirks (update creates new), error guidance, sibling tool references, and execution details. It compensates well for the lack of structured metadata, though could benefit from more explicit prerequisites or side effects.
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 all parameters thoroughly. The description adds some context about table names needing exact values from get_connection_tables and the REPLICATE query behavior, but most parameter semantics are already in the schema. Baseline 3 is appropriate when schema does heavy lifting.
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 manages tasks within jobs, specifying that tasks define what data to replicate. It distinguishes from siblings like read_tasks (read vs write) and write_jobs (tasks vs jobs). However, it doesn't explicitly differentiate from other write_* tools beyond the task focus.
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 for when to use this tool: managing tasks for data replication. It explicitly references sibling tools get_connection_tables for table names and read_tasks for verifying TaskId. However, it doesn't specify when NOT to use it or alternatives for similar operations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden and does well by disclosing return values for each action (create, update, delete) and listing common errors with troubleshooting guidance. It adds valuable context about SQL dialect requirements, connection verification, and job dependencies, though it could mention permissions or rate limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with clear sections (purpose, returns, common errors) and uses bullet points for readability. Every sentence earns its place, though the common errors section could be slightly more concise. It's appropriately sized for a complex tool.
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 complex mutation tool with 14 parameters and no annotations or output schema, the description provides good coverage: it explains the tool's purpose, return values, and common errors. However, it could better address behavioral aspects like idempotency, side effects, or authentication requirements to be 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?
Schema description coverage is 100%, so the schema already documents all 14 parameters thoroughly. The description doesn't add any parameter-specific semantics beyond what's in the schema, but it doesn't need to compensate. Baseline 3 is appropriate as the schema does the heavy lifting.
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 purpose with specific verbs ('Create, update, or delete') and resource ('SQL transformations for ELT processing'). It distinguishes itself from sibling tools like 'execute_query' (which runs queries) and 'read_transformations' (which only reads) by emphasizing write operations on transformation configurations.
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 through the 'ELT processing' mention and common errors like checking SQL dialect and connections, but it doesn't explicitly state when to use this tool versus alternatives like 'write_jobs' or 'execute_query'. No clear exclusions or prerequisites are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden and excels. It discloses critical behavioral traits: password requirements, return values for create/update actions, common errors with explanations, and bulk operation support. This covers mutation effects, error handling, and operational constraints, providing comprehensive guidance beyond the input schema.
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 well-structured with clear sections (purpose, requirements, returns, errors), making it easy to scan. It's appropriately sized for a complex tool with 9 parameters, though some redundancy exists (e.g., password requirements are stated in both the description and schema). Every sentence adds value, but minor trimming could improve efficiency.
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 (9 parameters, mutation operation, no annotations, no output schema), the description is largely complete. It covers purpose, behavior, errors, and returns, compensating well for the lack of structured metadata. However, it could enhance completeness by detailing output formats more explicitly or mentioning authentication needs, though the latter is somewhat implied by the context.
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 all parameters thoroughly. The description adds minimal parameter-specific information beyond the schema, such as reiterating password requirements and noting bulk efficiency. It doesn't provide additional syntax, format, or usage nuances, so it meets the baseline for high schema coverage.
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's purpose: 'Create or update CData Sync users.' It specifies the verb ('create or update') and resource ('CData Sync users'), but doesn't explicitly differentiate from sibling tools like 'read_users' beyond the obvious write vs. read distinction. The description is specific but could better highlight what makes this tool unique among write 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 description implies usage through the 'RETURNS' and 'COMMON ERRORS' sections, suggesting when to expect certain outcomes, but lacks explicit guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, compare with other write tools (e.g., 'write_workspaces'), or specify scenarios for bulk vs. single operations. Usage is inferred rather than stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
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 effectively describes several important behavioral traits: authentication requirements ('If not authenticated with CData Sync, you will be prompted for credentials'), constraints on usage ('Cannot modify or delete connections currently in use by running jobs'), and provider-specific behavior ('Connection strings are provider-specific - consult CData documentation'). It also mentions that 'To change providers, delete and recreate the connection,' which is valuable operational guidance. The main gap is lack of information about rate limits, error handling, or response format.
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 appropriately sized at 4 sentences, with the core purpose stated first. Each sentence adds value: authentication requirements, connection definition, provider-specific guidance, and operational constraints. There's no redundant information, though the final sentence about changing providers could be integrated more smoothly with the preceding content about constraints.
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 mutation tool with 6 parameters, no annotations, and no output schema, the description provides reasonable coverage of authentication, constraints, and provider-specific considerations. However, it lacks information about what happens after operations (success/failure responses, what gets returned), doesn't mention error conditions beyond the 'in use' constraint, and doesn't provide examples of common provider strings or connection string formats. Given the complexity of connection management, more complete guidance would be beneficial.
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?
With 100% schema description coverage, the schema already documents all 6 parameters thoroughly. The description adds minimal parameter-specific information beyond what's in the schema - it mentions connection strings are 'provider-specific' and 'may contain credentials,' which slightly elaborates on the schema's 'Format varies by provider' and 'handle securely' notes. However, it doesn't provide significant additional semantic context about how parameters interact or practical usage examples 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 purpose with specific verbs ('create, update, or delete data connections') and identifies the resource ('data connections'). It distinguishes itself from sibling tools like 'read_connections' by emphasizing write operations, and from other write_* tools by focusing specifically on connection management rather than jobs, tasks, or other resources.
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 about when to use this tool ('Create, update, or delete data connections') and mentions important constraints ('Cannot modify or delete connections currently in use by running jobs'). It also implicitly distinguishes from 'read_connections' for read operations. However, it doesn't explicitly mention when NOT to use this tool versus alternatives like 'write_jobs' or other write_* tools, nor does it provide explicit alternatives for specific scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden and adds valuable behavioral context beyond the input schema. It discloses authentication requirements (prompt for credentials if not authenticated), execution behavior (tasks run sequentially or parallel), and constraints (running jobs cannot be modified/deleted until complete). It does not mention rate limits or error handling, but covers key operational traits.
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 appropriately sized and front-loaded with the core purpose in the first sentence. Each subsequent sentence adds necessary context (authentication, execution mode, parameter usage, constraints) without redundancy. It could be slightly more structured but remains efficient with zero wasted sentences.
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 (executing jobs with authentication and behavioral constraints), no annotations, and no output schema, the description does a good job covering key aspects like purpose, usage, and behavioral traits. It lacks details on output format or error responses, but for a tool with rich schema coverage and no annotations, it is reasonably 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 description adds some meaning for parameters like 'waitForResults' (explaining its effect on synchronous vs. asynchronous execution) and implies job identification via name or ID. However, with 100% schema description coverage, the schema already documents all parameters thoroughly, so the description provides only marginal additional value beyond the schema's detailed descriptions.
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 purpose with specific verbs ('Run a job immediately, bypassing its schedule') and distinguishes it from siblings like 'cancel_job' or 'read_jobs' by emphasizing immediate execution rather than scheduled runs or status queries. It specifies the resource (job) and the unique action of bypassing schedules.
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 on when to use this tool (to run a job immediately) and mentions an alternative approach (using waitForResults parameter for synchronous vs. asynchronous execution). However, it does not explicitly state when not to use it compared to siblings like 'cancel_job' or 'read_jobs', which limits the score.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
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 effectively describes what the tool does (access tasks), what it returns (array of task objects with specific fields), and common errors with remediation steps. It doesn't cover aspects like rate limits, authentication needs, or pagination behavior, but provides substantial operational context beyond basic purpose.
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 well-structured with clear sections (purpose, required parameters, returns, common errors) and uses bullet points for readability. It's appropriately sized at 4 sentences, though the error section could be slightly more concise. Every sentence adds value without redundancy.
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 read operation with no annotations and no output schema, the description provides good context: clear purpose, required parameters, return format, and error handling. It doesn't explain the full structure of returned task objects or pagination details, but given the schema's comprehensive parameter documentation and the tool's relatively straightforward nature, it's mostly 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 schema already documents all 7 parameters thoroughly. The description adds minimal parameter-specific information beyond the schema - it only emphasizes that 'jobName' is required for all actions, which is already clear from the schema's required array. This meets the baseline for high schema coverage.
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's purpose: 'Access tasks within a specific job' with the verb 'access' and resource 'tasks'. It distinguishes from siblings like 'read_jobs' (which reads jobs) and 'write_tasks' (which writes tasks). However, it doesn't explicitly differentiate from other read_* tools like 'read_connections' or 'read_users' beyond the resource type.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance: it states 'REQUIRED: jobName parameter for all actions', names alternatives ('Verify job name with read_jobs' and 'add tasks with write_tasks'), and includes error handling advice ('Job not found' - Verify job name with read_jobs). This gives clear when-to-use and when-not-to-use context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
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 effectively describes the action ('Stop a currently running job'), outlines return values (success confirmation or error details), and lists common error scenarios, which helps anticipate outcomes. However, it doesn't mention side effects (e.g., if cancellation is irreversible) or operational constraints like rate limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and front-loaded, starting with the core purpose, followed by returns and common errors in clear sections. Every sentence adds value—no redundant or vague information—making it efficient for an agent to parse and understand the tool's behavior.
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 (a mutation operation with no annotations or output schema), the description provides good contextual completeness by explaining what the tool does, its returns, and error cases. However, it lacks details on side effects (e.g., if data is lost) or prerequisites (e.g., authentication needs), leaving some gaps for a mutation 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%, with each parameter clearly documented in the input schema (e.g., 'jobName' as 'Name of the running job to cancel'). The description adds no additional parameter semantics beyond what the schema provides, so it meets the baseline score of 3 for high schema coverage without compensating value.
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 purpose with a specific verb ('Stop') and resource ('a currently running job'), distinguishing it from sibling tools like 'execute_job' (which starts jobs) and 'read_jobs' (which lists jobs). The description immediately communicates the core functionality without ambiguity.
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 specifying 'currently running job' and listing common errors like 'Job not running' and 'Job not found', which help identify when the tool is appropriate. However, it doesn't explicitly state when to use this tool versus alternatives (e.g., when to cancel vs. delete a job) or mention prerequisites like required permissions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
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 effectively adds context beyond basic purpose: it specifies the return format ('Array of table names in exact format needed for tasks'), lists common errors with troubleshooting tips, and mentions prerequisites ('Must be created and tested first' in schema description). However, it doesn't cover aspects like rate limits, performance implications, or authentication details beyond error hints.
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 appropriately sized and front-loaded: the first sentence states the core purpose, followed by clearly labeled sections for returns and common errors. Every sentence earns its place by providing essential information without redundancy, making it easy to scan and understand.
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 complexity (8 parameters, no output schema, no annotations), the description is mostly complete: it covers purpose, returns, and errors, which helps compensate for the lack of output schema. However, it could improve by mentioning sibling tool relationships more explicitly or detailing behavioral traits like pagination handling (implied by skipTable) more clearly.
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 all 8 parameters thoroughly. The description does not add any parameter-specific semantics beyond what the schema provides (e.g., it doesn't explain parameter interactions or provide examples). Baseline 3 is appropriate as the schema does the heavy lifting, but no extra value is added.
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 purpose with specific verb ('Discover') and resource ('available tables/views in a data source'), and distinguishes it from siblings by mentioning it's 'Essential before creating jobs'—differentiating it from job-related tools like execute_job or get_job_tables. The title being null doesn't affect this clarity.
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 for when to use this tool ('Essential before creating jobs'), but does not explicitly state when not to use it or name specific alternatives among siblings. It implies usage for discovery tasks but lacks explicit exclusions or comparisons to tools like get_table_columns or read_connections.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
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 effectively describes the return format ('Array of column objects with name, type, nullable, and key information') and common errors that reveal behavioral traits like permission requirements and exact naming conventions. This adds valuable context beyond the input schema, though it could mention rate limits or side effects if applicable.
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 appropriately sized and front-loaded, with the core purpose stated first, followed by returns and errors in clear sections. Every sentence earns its place by providing essential information without redundancy, making it easy to scan and understand quickly.
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 moderate complexity (3 parameters, no output schema, no annotations), the description is largely complete. It covers purpose, returns, and common errors, which helps an agent use the tool correctly. However, it could improve by mentioning potential side effects or performance considerations, though the lack of output schema is mitigated by detailing the return format.
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 description coverage is 100%, so the input schema already documents all three parameters thoroughly. The description does not add significant meaning beyond the schema, such as explaining parameter interactions or usage nuances. It references parameters indirectly in error messages but doesn't enhance their semantics, warranting the baseline score 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 clearly states the tool's purpose with specific verbs ('Get column details') and resources ('for a specific table'), distinguishing it from siblings like get_connection_tables (which lists tables) or execute_query (which runs queries). It explicitly mentions what details are retrieved: names, data types, and keys.
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 for when to use this tool (to get column metadata for a specific table) and includes implicit guidance via error messages (e.g., use exact table names from get_connection_tables). However, it does not explicitly state when not to use it or name alternatives among siblings, such as get_connection_tables for table lists instead of column details.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
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 effectively discloses behavioral traits: it's a destructive operation (deletion), requires admin permissions (from 'Access denied' error), and notes that some logs may be protected. The 'RETURNS' and 'COMMON ERRORS' sections add valuable context beyond basic functionality.
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 appropriately sized and front-loaded, starting with the core purpose, followed by returns and errors. Each section (purpose, returns, errors) is concise and adds value without redundancy, making it easy to scan and understand.
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 no annotations and no output schema, the description provides good context: it explains the tool's purpose, return value, and common errors. However, it could be more complete by detailing prerequisites (e.g., workspace setup) or behavioral nuances like batch deletion support, but it covers key aspects adequately for a deletion 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 schema already documents all parameters well. The description does not add meaning beyond the schema, such as explaining parameter interactions or usage nuances. Baseline 3 is appropriate as the schema handles the heavy lifting.
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 purpose with a specific verb ('Delete') and resource ('API request log entries'), including the reasons ('for privacy compliance or cleanup'). It distinguishes from sibling tools like 'read_requests' by focusing on deletion rather than reading.
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 for privacy compliance or cleanup, providing clear context. However, it does not explicitly state when to use this tool versus alternatives like other 'write_' tools or specify exclusions, such as when logs are protected (mentioned only in errors).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden and excels at disclosing critical behavioral traits. It explains authentication prompting, immediate effect of changes, reconnection impacts, security restrictions (no password viewing), and workspace context propagation. These details go far beyond what a basic schema would convey.
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 appropriately sized and front-loaded with the core purpose. Each sentence adds value: authentication behavior, action types, critical warnings, and workspace implications. While comprehensive, it could be slightly more concise by combining some related concepts.
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 complex configuration tool with 7 parameters and no output schema, the description provides substantial context about behavior, security, and side effects. It covers authentication flows, immediate effects, workspace implications, and security restrictions. The main gap is lack of information about return values or error conditions.
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 all 7 parameters thoroughly. The description adds some context about workspace IDs and authentication precedence, but doesn't provide significant additional parameter semantics beyond what's in the schema. This meets the baseline 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 clearly states the tool's purpose: 'Configure the MCP server's connection to CData Sync.' It specifies the dual functionality (get/view and update/modify) and distinguishes it from sibling tools by focusing on server configuration rather than data operations like read_workspaces or write_connections.
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 for when to use this tool: for configuring server connections, with specific actions ('get' to view, 'update' to modify). It mentions authentication prompts and workspace context implications. However, it doesn't explicitly state when NOT to use it or name specific alternatives among siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden and does so well. It discloses key behavioral traits: the tool can run in sync or async modes (via waitForResults), returns specific result formats (success/async/error), and lists common errors with explanations. It doesn't cover rate limits or auth needs, but provides substantial operational context.
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 well-structured with clear sections (purpose, important note, returns, common errors) and uses bullet points for readability. It's appropriately sized but could be slightly more front-loaded; the 'IMPORTANT' note is critical and placed well, though some redundancy exists between the description and schema for queries.
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 (6 parameters, mutation-like operation) and lack of annotations/output schema, the description is largely complete. It covers purpose, constraints, return values, and errors. However, it doesn't explain the relationship between jobName and jobId parameters or provide examples of query names, leaving minor gaps.
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 minimal parameter-specific information beyond the schema—it mentions 'queries' must 'match existing task patterns' and implies job context usage, but doesn't elaborate on parameter interactions or provide examples. It meets but doesn't exceed the baseline.
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 specific action ('execute pre-defined queries') and resource ('within a job context'), distinguishing it from siblings like execute_job or read_tasks. It explicitly notes the limitation 'cannot run arbitrary SQL', which further clarifies its purpose relative to potential alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance on when to use this tool: 'for testing or ad-hoc operations' and 'can only execute queries already defined as tasks'. It implicitly contrasts with execute_job (which might run full jobs) and read_tasks (which only reads task definitions), offering clear context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses authentication behavior ('If not authenticated with CData Sync, you will be prompted for credentials'), which is valuable context beyond the input schema. However, it lacks details on rate limits, error handling, or performance characteristics that would be helpful for a tool with 9 parameters.
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 appropriately sized with four sentences that each serve a distinct purpose: stating the tool's function, noting authentication behavior, differentiating from a sibling, and providing usage context. It's front-loaded with the core purpose, though the authentication note could be slightly more concise.
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 (9 parameters, no output schema, no annotations), the description does a good job covering purpose, usage guidelines, and authentication. However, it could better address behavioral aspects like pagination (implied by skipTable parameter) or what 'job compatibility' entails, leaving some gaps for a tool of this scope.
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 description coverage is 100%, so the schema already documents all parameters thoroughly. The description adds minimal parameter semantics beyond the schema, only implying that parameters relate to 'job configuration and connection capabilities.' This meets the baseline 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 clearly states the verb ('List tables available to add') and resource ('to a specific job'), and explicitly distinguishes it from the sibling tool get_connection_tables by noting it's 'filtered for job compatibility.' This provides specific differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states when to use this tool ('Use when expanding job scope or adding new tables to existing job') and provides an alternative ('Similar to get_connection_tables but filtered for job compatibility'), giving clear guidance on tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Since no annotations are provided, the description carries the full burden of behavioral disclosure. It effectively describes several important behavioral traits: authentication requirements ('If not authenticated with CData Sync, you will be prompted for credentials'), prerequisites ('Connections must be created and tested before being used in jobs'), and concurrency behavior ('Multiple jobs can use the same connection simultaneously'). However, it doesn't mention rate limits, error handling, or response formats, which would be helpful for a tool with 9 parameters.
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 well-structured and appropriately sized. It front-loads the core purpose, then lists the three actions with their purposes, followed by important behavioral notes. Every sentence adds value: authentication requirements, action explanations, prerequisites, concurrency note, and counting clarification. While efficient, it could be slightly more concise by combining some related points about the actions.
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 (9 parameters, no output schema, no annotations), the description does a good job of providing necessary context. It explains the three main actions, authentication requirements, prerequisites for using connections in jobs, and concurrency behavior. However, for a tool with this many parameters and no output schema, it could benefit from mentioning what the return values look like for each action type or providing examples of typical responses.
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?
With 100% schema description coverage, the input schema already documents all 9 parameters thoroughly. The description adds some context about parameter usage (e.g., 'For counts, use 'list' and count results' which relates to the action parameter) and mentions that connections must be tested before use (relevant to the test action). However, it doesn't provide significant additional semantic meaning beyond what's already in the schema descriptions, so the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
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 purpose: 'Access data source/destination connections that define how CData Sync connects to databases, APIs, and files.' It specifies the resource (connections) and distinguishes from siblings like write_connections (for creation/modification) and get_connection_tables (for table-level operations). The description also lists the three specific actions available (list, get, test), making the purpose highly specific.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance on when to use this tool versus alternatives. It states: 'Use 'list' to see all available connections, 'get' to retrieve details about a specific connection, 'test' to verify credentials and connectivity.' It also clarifies when NOT to use it: 'Note: For counting connections, use 'list' and count the results client-side.' This directly addresses potential confusion with counting operations and provides clear alternatives within the same tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
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 effectively describes key behavioral traits: authentication requirements (prompt for credentials if not authenticated), API limitations (count action not supported, workaround provided), and the nature of returned data (history records with specific fields like status, duration). It doesn't cover rate limits or error handling, but provides substantial operational context.
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 appropriately sized and front-loaded, starting with the core purpose followed by authentication notes, record details, usage instructions, and API limitations. Every sentence adds value, though it could be slightly more streamlined by combining some related points about filtering and counting.
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 (7 parameters, no annotations, no output schema), the description provides good contextual completeness. It covers purpose, authentication, data format, usage patterns, and API limitations. The main gap is the lack of output format details (though it mentions record fields), but it compensates with strong operational guidance for a read-only history 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 schema already documents all 7 parameters thoroughly. The description adds minimal parameter-specific information beyond the schema, mentioning 'list' action and client-side filtering for counts. It provides context about parameter usage but doesn't add significant semantic value beyond what's in the schema descriptions.
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 purpose: 'Access job execution history to analyze performance, troubleshoot failures, and audit data movements.' It specifies the verb ('access') and resource ('job execution history'), distinguishes it from siblings like 'read_jobs' or 'execute_job' by focusing on historical execution data, and lists specific use cases (performance analysis, troubleshooting, auditing).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance on when to use this tool vs alternatives: it states 'Use 'list' to browse history with filters/sorting' and notes 'Count action not supported by API - use 'list' and count results client-side.' It also mentions authentication requirements ('If not authenticated with CData Sync, you will be prompted for credentials'), helping the agent understand prerequisites.
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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