convert_ssis_package

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: it generates multiple JSON artifacts and stubs, returns a summary and warnings, and supports specific features like Self-Hosted IR and cross-package dedup. However, it lacks details on error handling, performance, or side effects like file system changes.

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

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

The description is front-loaded with the core purpose in the first sentence, followed by a concise list of generated artifacts and supported features. Every sentence adds value without redundancy, making it efficient and well-structured for quick understanding.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (13 parameters, no annotations, no output schema), the description is reasonably complete. It covers the conversion process, outputs, and key features, but lacks details on return values (beyond 'summary' and 'warnings') and error conditions, which could be important for a tool with many parameters and no output schema.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents all 13 parameters thoroughly. The description adds no additional parameter semantics beyond what the schema provides, such as explaining interactions between parameters or usage examples. Baseline 3 is appropriate when the schema does the 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 specific action ('Convert a single SSIS package') and resource ('.dtsx file') to output ('Azure Data Factory JSON artifacts'), listing the exact types generated. It distinguishes from sibling tools like analyze_ssis_package or deploy_to_adf by focusing on conversion rather than analysis or deployment.

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 no explicit guidance on when to use this tool versus alternatives like analyze_ssis_package or validate_adf_artifacts. It mentions the tool's capabilities but does not specify prerequisites, ideal scenarios, or when other tools might be more appropriate, leaving usage context implied at best.

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