CData Sync MCP Server

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.

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.

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.

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.

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.

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.