call_write_toolRun write operations to create or change Gcore Cloud resources by specifying an operation name and optional arguments, then confirm when prompted.
Run a write operation (creates or changes something). May ask the user to confirm.
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | Operation name from search_tools. | |
| arguments | No | Per the schema. A list runs it per item, approved once. | |
| confirm_token | No | Only when a previous response asked for it. |
Changes observed during successful MCP inspections.
v1.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=false, destructiveHint=false, and openWorldHint=true, so the safety profile is covered. The description adds one genuinely new behavioral fact — a possible user confirmation step — but leaves it vague ('May'), without saying when confirmation triggers, what a pending-confirmation response looks like, or how confirm_token is returned.
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 short sentences with the effect statement front-loaded and zero filler. It is efficient, though the brevity edges into under-specification rather than crisp completeness.
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 an open-world dispatcher that mutates state and involves an asynchronous confirmation handshake, the description is too thin: it does not explain failure behavior, the confirm_token round-trip, or what distinguishes this from call_destructive_tool. There is no output schema to fill those gaps.
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 all three parameters are already documented in the schema, including the per-item list behavior and the confirm_token conditionality. The description adds no parameter meaning beyond that, so baseline 3 applies.
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?
States a specific verb ('Run a write operation') and clarifies the effect as 'creates or changes something', which separates it from the read path. It does not explicitly name the sibling it is not (call_destructive_tool), so the write-vs-destructive boundary is only implied.
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?
There is no when-to-use guidance: nothing tells the agent to prefer call_read_tool for reads, call_destructive_tool for destructive ops, or execute_code for scripting. The only routing hint, that `name` comes from search_tools, lives in the schema rather than the description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.