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CorporateTravel Dispatch MCP

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dispatch_get_cps

Read-onlyIdempotent

Retrieve the current Critical Predictability State (CPS) score for HEMS operations, computed from six weather and airspace factors to determine GO, CAUTION, or NO-GO status.

Instructions

Get the current Critical Predictability State (CPS) — the HEMS go/no-go score.

CPS is computed from six factors: ceiling, visibility, wind, precipitation, airspace restriction, and GDP (Ground Delay Program). Final state is one of: GO, CAUTION, or NO-GO per Part 135.609 thresholds.

Returns: str: JSON object with: state (str: GO/CAUTION/NO-GO), score (float: 0.0-1.0), factors: { ceiling: {value, score, label}, visibility: {value, score, label}, wind: {value, score, label}, precip: {value, score, label}, airspace: {value, score, label}, gdp: {value, score, label} }, computed_at (str: ISO timestamp).

Examples: - "Is it a go for HEMS operations?" -> call, check state field - "What's limiting the CPS score?" -> call, find lowest factor scores

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

Annotations already declare readOnlyHint, destructiveHint, idempotentHint, openWorldHint. The description adds significant behavioral detail: explains CPS computation from six factors, final states (GO/CAUTION/NO-GO), and return structure with nested factor objects.

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?

Concise yet informative: clear header, bulleted factors, return type description, and two relevant examples. No wasted words.

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?

Fully describes the tool's purpose, computation, return structure, and example use cases. Given no parameters and supportive annotations, nothing is missing.

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

Parameters4/5

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

No parameters exist (0 params, schema coverage 100%), so baseline is 4. Description adds no parameter info, which is appropriate.

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 starts with a clear verb and resource: 'Get the current Critical Predictability State (CPS) — the HEMS go/no-go score.' It specifies the purpose (HEMS go/no-go) and distinguishes from sibling tools by focusing uniquely on CPS.

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?

Includes usage examples (e.g., 'Is it a go for HEMS operations?' and 'What's limiting the CPS score?') that clarify when to use the tool. However, it lacks explicit statements about when not to use or alternatives among siblings.

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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