read_workflow

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool reads source code and metadata, implying a read-only operation, but doesn't disclose key traits such as whether it requires authentication, has rate limits, what happens if the workflow doesn't exist (e.g., error handling), or the format of returned metadata. For a read tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.

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 appropriately sized and front-loaded, starting with the core purpose. The use of sections for 'Args' and 'Returns' adds structure, but the 'Returns' section could be more detailed given no output schema. There's minimal waste, though it could be slightly more informative without losing conciseness.

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 moderate complexity (reading source code with metadata), no annotations, no output schema, and low schema coverage, the description is incomplete. It doesn't explain the return value format beyond 'dict: The workflow source code and metadata,' leaving ambiguity. For a tool that likely returns structured data, more context is needed to be fully helpful to an AI agent.

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?

The description adds meaning beyond the input schema by specifying that the 'name' parameter refers to 'The name of the workflow to read,' which clarifies its purpose. However, with 1 parameter and 0% schema description coverage, the schema provides no details, and the description doesn't fully compensate—it lacks information on name format, constraints, or examples. The baseline is adjusted due to low coverage, but the description offers some semantic value.

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's purpose as 'Read the source code of a workflow script,' which is a specific verb (read) and resource (workflow script). It distinguishes from siblings like create_workflow, delete_workflow, execute_workflow, list_workflows, and update_workflow by focusing on reading source code, but doesn't explicitly differentiate from list_workflows which might also involve reading metadata. The description avoids tautology and is not misleading.

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 guidance on when to use this tool versus alternatives. It doesn't mention when to choose read_workflow over list_workflows (e.g., for detailed source vs. summary list) or other siblings, nor does it specify prerequisites like needing an existing workflow name. Usage is implied by the purpose but lacks explicit context or exclusions.

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