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sim_dataset

Destructive

Generate a synthetic event log from a stored model (seeded SSA playout; case-per-arrival). Returns CSV. Deterministic: same id, same seed, same bytes.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesmodel id
seedNoPRNG seed (default 1)
casesNocases to generate (default 200, max 2000 over MCP)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.5/5.0
Behavior3/5

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

The description adds useful behavioral traits beyond annotations: determinism ('same id, same seed, same bytes') and the return format ('Returns CSV'). Annotations already indicate readOnlyHint false and destructiveHint true, but the description does not explain the nature of the destructive side effect. It provides some added context but leaves side-effect clarity to the annotations.

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 two short sentences that front-load the core purpose and then give determinism and output format. Every sentence contributes new information with no redundancy, making it appropriately sized for a tool with only three parameters.

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

Completeness3/5

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

The description covers what the tool generates, its source, output format, and determinism, which is adequate for a simple tool with fully documented parameters. However, with no output schema, the CSV structure and columns are not described, and the destructiveHint true is not elaborated in the description. An explicit note about side effects would make the definition more complete.

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%, so all three parameters (id, seed, cases) are already documented in the input schema. The description reiterates the role of id and seed in determinism but does not add new semantic details for the cases parameter or the CSV content. Since the schema carries the parameter meaning, the description meets the baseline without substantial additional value.

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

Purpose5/5

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

The description states a specific verb ('Generate'), a resource ('synthetic event log from a stored model'), and a method ('seeded SSA playout; case-per-arrival'). This clearly distinguishes it from the many sim_* siblings by emphasizing deterministic synthetic data generation from a model. It also mentions the CSV output, making the tool's purpose unmistakable.

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 gives no when-to-use or when-not-to-use guidance, and it does not reference any alternative sibling tools such as sim_scenario or sim_run_pipeline. The purpose implies use for generating synthetic event logs, but an agent cannot determine prerequisites, exclusions, or when a different sim tool would be more appropriate.

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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