unlink_var_modelRemove a VAR link from a marketing mix model by providing its model hash. Safely disconnects the link without side effects, enabling cleaner model updates or corrections.
Remove an MMM's VAR link (#569). Idempotent.
| Name | Required | Description | Default |
|---|---|---|---|
| model_hash | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v0.5.0Output schema / (root)Previous value: -nullNew value: +{
+ "additionalProperties": true,
+ "title": "unlink_var_modelDictOutput",
+ "type": "object"
+}v0.3.2Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare destructiveHint=true and idempotentHint=true, so the description's 'Idempotent' note is somewhat redundant but reinforces the key behavioral trait. The description adds the specific scope ('an MMM's VAR link') and references issue #569, which gives context. No contradiction with annotations.
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 no filler. The core action is front-loaded, and the idempotency note is a valuable addition. 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 single-parameter destructive operation, the description is mostly adequate. The output schema exists, so return values are covered. However, the description doesn't clarify what 'VAR link' means in this domain or what happens to the model after unlinking, which could matter for an agent deciding whether to call this tool.
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 carries the burden for parameter meaning. However, the description doesn't explain what model_hash is or how to obtain it. The parameter name is fairly self-explanatory, but the description adds no semantic value beyond the schema.
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 states a specific action ('Remove an MMM's VAR link') with a clear resource, and the idempotency note adds useful precision. It doesn't explicitly distinguish from sibling tools like link_var_model, but the verb 'unlink' and the resource 'VAR link' make the purpose clear enough.
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 it: when you need to remove a VAR link from an MMM. It doesn't explicitly state when not to use it or name alternatives, but the sibling context (link_var_model) makes the contrast fairly obvious. No explicit exclusions or alternative routing.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.