Simulate budget changes across channels or dimension cells to forecast performance via posterior response sampling, automatically blocking invalid models.
Evaluate the exact requested channel or dimension-cell scenario with posterior response sampling. Rejected models are blocked.
| Name | Required | Description | Default |
|---|---|---|---|
| config | Yes |
Changes observed during successful MCP inspections.
v0.4.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry the behavioral burden. It mentions posterior response sampling and blocked rejected models, but does not clarify whether the tool is read-only, what model status is required, or what happens on success or 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 short and mostly front-loaded, but 'Rejected models are blocked.' is cryptic and adds little without supporting context. It is concise but not fully self-contained.
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 complex nested config schema, no output schema, and zero annotations, this description is insufficient. It does not explain expected return values, input construction, constraints, or how the simulation results are delivered.
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%, and the description adds no meaning to the sole 'config' parameter. The agent receives no help understanding model_id, changes, cell_changes, or planning_periods from the description.
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 it evaluates an exact requested channel or dimension-cell scenario via posterior response sampling, which helps distinguish it from optimization and prediction siblings. However, it omits the word 'budget' and does not explicitly contrast itself with optimize_budget or get_response_curves.
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?
No guidance on when to use this tool versus alternatives. The description implies use for specific scenario evaluation but provides no exclusions, prerequisites, or comparison to sibling tools like optimize_budget or predict_expected_spend.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.