modify_deployment_config

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

With no annotations provided, the description carries full burden for behavioral disclosure. While 'modify' and 'update' imply mutation, it doesn't specify permissions required, whether changes are reversible, rate limits, error conditions, or what 'update the deployment' entails operationally. The Returns section mentions a response dictionary but gives no details about success/failure indicators or structure. This is inadequate for a mutation tool with zero annotation coverage.

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 structured with Args, Example Usage, and Returns sections, which is good organization. However, the example is overly long (25+ lines) with embedded comments and syntax issues, making it inefficient. The core purpose statement is clear but could be more front-loaded. Some sentences like 'Add these if any additional detectors than that in the policy are needed' are instructional rather than descriptive.

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 mutation tool with 2 parameters (one being a complex nested object), 0% schema description coverage, no annotations, and no output schema, the description is incomplete. While it shows an example configuration, it doesn't explain the full behavioral context: what fields are modifiable, validation rules, side effects, error handling, or response format. The Returns section is vague ('A dictionary containing...') without structural details.

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 0%, so the description must compensate. It names both parameters ('deployment_name' and 'new_deployment_config') and provides an extensive example showing a complex nested configuration object with guardrails policies. However, the example contains syntax errors (e.g., 'sample_deployment_config =' inside JSON) and doesn't clearly map to the actual parameter structure. It adds some semantic value but doesn't fully document the parameter expectations beyond the basic names.

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: 'Modify the deployment configuration and update the deployment.' This specifies the verb ('modify' and 'update') and resource ('deployment configuration' and 'deployment'), making it clear this is a mutation operation. However, it doesn't explicitly differentiate from sibling tools like 'modify_model_config' or 'update_guardrails_policy' that might handle similar configuration changes.

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. With siblings like 'add_deployment', 'get_deployment_details', 'list_deployments', and 'remove_deployment', there's no indication of prerequisites (e.g., deployment must exist), when to choose modification over recreation, or what happens if the deployment doesn't exist. The example shows complex configuration but doesn't explain usage context.

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