diff_deployments

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

With no annotations, the description carries the full burden. It discloses the behavior of comparing specific attributes across versions, which is useful. However, it does not explicitly state whether the operation is read-only or if any side effects occur. The term 'diff' implies non-mutating, but this is not confirmed.

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 two sentences, front-loaded with the core action and a specific list of diffed attributes. The second sentence adds contextual value by labeling it as a root-cause tool. Every word earns its place with no redundancy.

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?

While an output schema exists (so return values are covered), the description lacks details on parameter formats and any prerequisites or constraints (e.g., whether versions must be consecutive). It adequately conveys the tool's primary purpose but leaves gaps in operational details that could trip up an 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?

Schema description coverage is 0%, so the description must compensate. It mentions 'two model versions' which maps to version_a and version_b, but does not explain the expected format for versions or model_name. The description lists diff categories (training data span, params, etc.) but those are not the parameters themselves. Thus, an agent gets no additional clarity on how to fill the three required parameters.

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 function: 'Diff two model versions' with a specific list of what is diffed (training data span, params, eval metrics, feature schema). It also distinguishes itself from siblings by labeling itself as 'the primary root-cause tool,' making its role unique among the listed tools.

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 implies when to use this tool—for root-cause analysis of what changed between deployments. It says it correlates 'what changed between the incumbent and the newly deployed version,' giving clear context. However, it does not mention specific exclusions or when to prefer sibling tools like get_drift_report or summarize_metric_anomalies.

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