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add_flow

Add a flow between stocks in a Stella system dynamics model, specifying the rate equation, source, and destination to represent material transfer.

Instructions

Add a flow between stocks in the current model

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
xNoX position (optional, auto-positioned if not specified)
yNoY position (optional, auto-positioned if not specified)
nameYesFlow name
unitsNoUnits
equationYesFlow rate equation
model_idNoSession-scoped model ID. Optional; defaults to the current model for this session.
to_stockNoDestination stock (null for external sink)
from_stockNoSource stock (null for external source)
non_negativeNoPrevent negative values
workspace_idNoOpaque application workspace handle. Required by MCP 2026-07-28 clients; supported legacy stdio clients may omit it to use the process-local compatibility workspace.
graphical_functionNoGraphical function (lookup table) definition

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
flowYes
model_idYes
Behavior2/5

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

Annotations already indicate a mutating operation (readOnlyHint false), but the description adds no behavioral detail beyond that. It does not disclose whether adding a flow can overwrite existing flows, whether it requires existing stocks to exist, or how the model state is affected. For a model-building operation, this lack of context could lead to misuse.

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

Conciseness4/5

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

The description is a single, front-loaded sentence with no tautology or filler. It is appropriately concise, though it could incorporate a bit more context (e.g., mentioning equation or external connections) without becoming bloated.

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?

Given the tool's complexity (11 params, nested objects, output schema), the description is too minimal. It does not convey the full range of flows (external sources/sinks, graphical functions, non_negative flag) and may mislead an agent into thinking flows only connect two stocks. The rich schema does not compensate for the lack of conceptual orientation in the description.

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?

Schema description coverage is 100%, with all 11 parameters including nested graphical_function fully described in the input schema. The tool description adds no parameter-level meaning beyond what the schema provides, so the baseline of 3 is appropriate.

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 ('Add a flow') and the resource ('between stocks in the current model'), distinguishing it from siblings like add_stock and add_connector. However, it narrows the scope by saying 'between stocks' when flows can also connect to external sources/sinks (from_stock/to_stock null), which is not mentioned.

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?

No guidance is provided on when to use this tool versus alternative tools like add_connector or update_flow. The description lacks contextual cues or exclusions, leaving the agent without decision support for tool selection.

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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