Skip to main content
Glama
IBM

Chuk MCP Maritime Archives

by IBM

maritime_galleon_transit_times

Compute transit days for Manila Galleon voyages across the Pacific. Use eastbound crossing times as an ENSO proxy to evaluate historical El Niño and La Niña effects.

Instructions

Compute transit times for Manila Galleon voyages (1565-1815).

Returns per-voyage transit days (arrival_date - departure_date) for 250 years of Pacific crossings. The galleon trade provides direct tropical Pacific exposure through the ENSO-affected trade wind belt, making transit times a potential ENSO proxy.

Args: trade_direction: "eastbound" (Acapulco→Manila, trade-wind route, ~75 days) or "westbound" (Manila→Acapulco, northern route, ~165 days) year_start: Earliest departure year (inclusive) year_end: Latest departure year (inclusive) fate: Filter by voyage fate ("completed", "wrecked", etc.) max_results: Maximum records to return (default: 500) output_mode: Response format - "json" (default) or "text"

Returns: JSON or text with transit records and summary statistics

Tips for LLMs: - Eastbound galleons are the best ENSO detector: they sail directly through the trade wind belt - During El Nino (weakened trades), eastbound crossings should take LONGER; during La Nina (stronger trades), FASTER - Westbound route goes north via Kuroshio Current at ~38N, less directly affected by tropical ENSO - Use trade_direction="eastbound" for ENSO analysis - Compare transit_days across known ENSO years vs neutral years - 213 voyages have complete transit data (of 250 total) - Mean eastbound: 75 days (std 14); westbound: 165 days (std 17)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
trade_directionNo
year_startNo
year_endNo
fateNo
max_resultsNo
output_modeNojson
Behavior4/5

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

Without annotations, the description carries the full burden. It discloses the return type (per-voyage transit days with summary statistics), data completeness (213 of 250 voyages have complete data), and typical values (mean and std). No destructive behavior is implied; it reads as read-only. No contradictions with annotations.

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 relatively long but well-structured with clear sections (description, args, returns, tips). Each sentence adds value, though some tips might be considered extra. It is front-loaded with the core purpose.

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?

Given no annotations and no output schema, the description is fairly complete. It covers purpose, parameters, return format, and usage guidelines. It could mention error handling or output format details more, but it is sufficient for an 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, so the description fully compensates by explaining each parameter in the 'Args' block, including purpose, examples, and constraints (e.g., default values, direction-specific details). This adds significant meaning beyond the schema.

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 computes transit times for Manila Galleon voyages, with a specific verb 'Compute' and resource 'transit times'. It distinguishes from siblings by focusing on galleon voyages and ENSO proxy, which is unique among the maritime tools listed.

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 guidance on when to use the tool (e.g., 'Use trade_direction="eastbound" for ENSO analysis') and offers tips for LLMs. However, it does not explicitly state when not to use the tool or name alternative sibling tools for similar tasks.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/IBM/chuk-mcp-maritime-archives'

If you have feedback or need assistance with the MCP directory API, please join our Discord server