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bus-scheduling-mcp

bus-scheduling-mcp

by uwmyuan
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
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scheduling_run_optimization

Trigger a bus scheduling optimization by specifying an algorithm ID and parameters, and receive a task ID for tracking.

Instructions

Trigger an optimization task with a specific algo_id and parameters. Returns a task ID.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "algo_id": "<algo_id>"
    },
    "name": "scheduling_run_optimization"
  }
}

Input Schema

NameRequiredDescriptionDefault
paramsNo
algo_idYes
data_set_idNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

B3.3/5.0
Behavior2/5

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

With no annotations, the description carries the full burden. It discloses that a task ID is returned, implying an asynchronous operation, but fails to state that this is a mutation or that it kicks off a potentially expensive background job. No side effects, permissions, or polling behavior are mentioned.

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 with no filler. It efficiently states the action and immediate output.

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?

For a tool with three parameters and no output schema/annotations, the description is incomplete. It omits data_set_id, does not explain the params object structure, and does not mention how to track the task. Missing critical information for correct invocation.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must explain parameters. It mentions 'algo_id' and 'parameters' but does not explain what 'params' should contain or what 'data_set_id' is. Minimal compensation for the schema gap.

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 the action (trigger), the resource (optimization task), and key input (algo_id). It also mentions the return value (task ID), distinguishing it from sibling tools that list or retrieve data.

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

Usage Guidelines3/5

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

The description implies usage for starting an optimization run, but does not explicitly contrast it with alternatives like scheduling_get_optimization_status for checking progress. No when-not-to-use guidance is provided.

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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