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Calculation methodology

get_methodology
Read-only

How TripLedger derives residency, Schengen, and travel-summary numbers, including counting rules, windows, uncertainty, and limits. Pass an optional topic; omitted topic defaults to all.

Input Schema

NameRequiredDescriptionDefault
topicNo

Output Schema

NameRequiredDescriptionDefault
scopeYes
warningYes
documentsYes
conventionsYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and openWorldHint=false, so safety is covered. The description adds genuine value by characterizing the payload as explanatory content (counting rules, windows, uncertainty, limits) rather than raw data, which tells the agent what kind of answer to expect.

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?

Two short sentences with the subject (what the numbers mean and how they are derived) front-loaded and the optional-parameter behavior trailing. Nothing is redundant or padded.

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

Completeness4/5

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

With an output schema present and full annotation coverage, return values and safety need no explanation, so the description is nearly complete for a single optional-enum documentation tool. The only residual gap is whether the methodology is static reference text or personalized to the user's data, which could affect how the agent frames the result.

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?

Schema description coverage is 0%, so the description must carry the load, and it does explain that the topic argument is optional and that omitting it defaults to all — a default the schema does not state. The enum values themselves are self-describing and need no further gloss.

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

Purpose4/5

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

States a specific resource and scope: it explains how residency, Schengen, and travel-summary figures are derived, including counting rules, windows, uncertainty, and limits. This clearly separates it from data-returning siblings like get_residency_status or check_schengen_status, though it never names those siblings explicitly to make the contrast unmistakable.

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 the tool is for understanding methodology rather than fetching current numbers, but it never says when to prefer it over get_residency_status/get_travel_summary, nor any exclusion. The only explicit usage instruction ('Pass an optional topic; omitted topic defaults to all') is about invocation, not selection.

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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