apply_changes

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

With no annotations, the description carries the full burden of behavioral disclosure. It discloses that the tool reloads the subsystem and activates every pending change, including those staged by humans, which is a significant side effect. It also mentions the confirm requirement. However, it does not mention whether the operation is reversible, what happens on failure, or if it could cause downtime. For a mutation tool, this is adequate but not rich.

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?

Two sentences with no filler. The first sentence front-loads the action and the confirm requirement. The second sentence adds important context about the scope (all pending changes including human-staged). Every word earns 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 mutation tool with no annotations, the description covers the key aspects: what it does, what it requires, and a warning about the scope. It does not explain the output format, but since the tool has an output schema, that is not the description's job. It could mention irreversibility or potential service disruption, but the warning about applying ALL changes is a strong implicit caution. Overall, it is reasonably complete.

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 coverage is 0%, so the description must compensate. It adds meaning for both parameters: it specifies the valid values for 'subsystem' and states that 'confirm' must be true, which is not in the schema (schema only shows type and default). This goes beyond the schema and helps an agent use the tool correctly.

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?

Clearly states the verb 'apply' and the resource 'ALL staged changes of a subsystem', and explicitly enumerates the valid subsystems ('firewall', 'dhcp' or 'dns'). This distinguishes it from the sibling get_pending_changes (which retrieves changes) and restart_service (which restarts a service).

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 states a key precondition ('Requires confirm=true') and warns that it applies all pending changes, including human-staged ones. However, it does not explicitly say when to use this tool vs alternatives (e.g., after reviewing pending changes, or when you only want to apply your own changes). It gives context but not explicit routing or exclusions.

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