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petri-net-sim

pns-server MCP Server

add_transport_agent

Add a transport agent resource with a cycle of grabbing, moving, releasing, and returning to model material handling equipment.

Instructions

Add a TransportAgent (cyclic resource) pattern.

Models any resource that picks up, moves, releases, and returns: robots, forklifts, AGVs, cranes, couriers.

Cycle: [Queue]+[Free] -> Grab -> Move -> Release -> Return -> [Free]

Args: name: Name for this agent (e.g., "Robot1", "Forklift", "AGV") grab_time: Mean time to grab/pick item in time_unit grab_deviation: Standard deviation for grab in time_unit grab_distribution: Distribution for grab time move_time: Time to move WITH item in time_unit move_distribution: Distribution for move release_time: Mean time to release/place item in time_unit release_deviation: Standard deviation for release in time_unit release_distribution: Distribution for release return_time: Time to return EMPTY in time_unit (default: same as move_time) return_distribution: Distribution for return time_unit: Unit for all time values — "s", "min", or "h"

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes
grab_timeNo
grab_deviationNo
grab_distributionNounif
move_timeNo
move_distributionNodet
release_timeNo
release_deviationNo
release_distributionNounif
return_timeNo
return_distributionNodet
time_unitNos

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

With no annotations provided, the description fully carries the burden of behavioral disclosure. It explains the complete cycle (Queue+Free -> Grab -> Move -> Release -> Return -> Free) and describes all parameters, leaving no ambiguity about the tool's behavior.

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 well-structured with sections for intro, examples, cycle, and args. It is front-loaded with purpose. However, it could be slightly more concise as some explanations are repeated across parameter lines.

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

Completeness5/5

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

Given the tool complexity (12 params, 1 required) and presence of an output schema, the description covers purpose, usage, parameter semantics, and behavioral cycle. It provides enough context for an AI agent to use the tool correctly.

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

Parameters5/5

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

The input schema has 0% description coverage, but the description provides detailed explanations for all 12 parameters, including units and distributions. This fully compensates for the missing schema descriptions.

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 clearly states it adds a TransportAgent (cyclic resource) pattern, lists examples like robots and forklifts, and explains the cycle. This effectively distinguishes it from sibling tools like add_machine or add_conveyor.

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

Usage Guidelines4/5

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

The description provides clear context on when to use this tool (for cyclic resource patterns), but does not explicitly state when not to use it or name alternatives. The examples and cycle description implicitly guide usage.

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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