Set IC-CAP input data from a dictionary, automatically converting string keys like ('M', '11') to tuple keys for simulations and transforms.
Set Input data from a dictionary. String keys such as '("M", "11")' are converted to tuple keys for IC-CAP. Data format: {"('M', '11')": [val1, val2, ...]}.
| Name | Required | Description | Default |
|---|---|---|---|
| data | Yes | ||
| force | No | ||
| input_path | Yes |
Changes observed during successful MCP inspections.
v0.2.2Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the burden of behavioral disclosure. It usefully reveals a non-obvious conversion behavior: string keys like '("M", "11")' are converted to tuple keys for IC-CAP. However, it does not explain the meaning of the 'force' parameter, whether existing data is overwritten, or what happens on failure.
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 compact and front-loaded with the core action. The key-conversion note and the data format example each add necessary operational detail without unnecessary verbosity.
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?
Given the absence of annotations, output schema, and parameter documentation, the description still leaves important gaps. It fully explains the data payload structure but not the target path semantics or the 'force' flag, so an agent may still be uncertain about edge behavior. The core call is likely usable, but not completely specified.
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 adds meaningful semantics for the 'data' parameter by specifying the expected dictionary shape and key conversion behavior. It does not explain 'input_path' or 'force', leaving those parameters to be inferred from names and defaults.
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 clear verb and resource: 'Set Input data from a dictionary.' It also distinguishes itself from sibling field-level tools like input_set_field by emphasizing bulk dictionary-based data assignment. However, it does not explicitly name or contrast itself with those siblings.
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 usage context is implied: use this tool when you need to assign an entire Input data structure from a Python dictionary. It provides a concrete data format example, which helps correct invocation, but it does not state when to prefer this over alternatives such as input_set_field or input_get_data.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.