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call_function

Invoke a named callable with a JSON object of keyword arguments to execute Python code in a persistent IPython environment, preserving state across calls.

Instructions

Call a live callable by name with a JSON object of keyword arguments.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes
argumentsYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
okYes
nameYes
errorNo
resultNo
runtimeNo
truncatedNo
name_truncatedNo
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the action 'call' but does not mention potential side effects, error conditions, security considerations, or whether the call is synchronous. This is a significant gap for a tool that invokes arbitrary callables.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, focused sentence with no redundant information. Every word contributes to understanding the tool's purpose and its key parameters. It is concise and appropriately front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has no annotations, no parameter descriptions in the schema, and only a minimal description. It does not explain how to discover available callables (e.g., via 'list'), what happens if the callable does not exist, or any safety implications of executing arbitrary functions. The existing output schema may cover return values, but other essential context is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description explicitly explains both parameters: 'by name' clarifies that 'name' is the identifier of the callable, and 'with a JSON object of keyword arguments' provides meaning for 'arguments'. However, the schema allows 'arguments' to also be a string, which is not addressed, leaving ambiguity about that format. Despite the 0% schema description coverage, the description does add meaningful context beyond the parameter names.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action (call), the resource (a live callable), and the method (by name with a JSON object of keyword arguments). It is specific and unambiguous about what the tool does. However, it does not explicitly distinguish itself from sibling tool 'execute', which could be similarly interpreted.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides a general sense of when to use the tool (when you want to call a callable), but it offers no guidance on when not to use it or contrasts with alternatives like 'execute', 'search', or 'inspect'. There is no mention of prerequisites such as the callable needing to be registered first.

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

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