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Chuk MCP Maritime Archives

by IBM

maritime_crew_career

Reconstruct career histories of VOC crew members by searching name and optional origin. View chronological voyages, ranks held, career span, and final fate.

Instructions

Reconstruct career history for crew members matching a name.

Searches the VOC Opvarenden dataset for all records matching the given name, groups them by individual (using name + origin), and reconstructs each person's career chronologically.

Args: name: Name to search for (substring, case-insensitive) origin: Optional origin city to disambiguate (exact match) output_mode: Response format — "json" (default) or "text"

Returns: JSON or text with career reconstruction(s)

Tips for LLMs: - Common names may match multiple individuals; use origin to disambiguate - Look at ranks_held to see career progression (e.g. matroos -> stuurman -> schipper) - career_span_years shows how long someone served the VOC - final_fate shows how their career ended - Each voyage includes ship_name, rank, and embarkation_date

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes
originNo
output_modeNojson
Behavior4/5

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

With no annotations, the description carries full burden and explains the search, grouping, reconstruction process, output format options (json/text), and result fields (ranks_held, career_span_years, final_fate, voyage details). It does not mention rate limits or edge cases but is sufficiently transparent for safe use.

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 well-structured starting with purpose, then process, then parameters, then tips. Every sentence provides valuable information without redundancy. It is concise yet comprehensive.

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 has 3 parameters, no output schema, and no annotations, the description is remarkably complete: it explains the overall behavior, parameter details, return format, and practical usage tips. No important aspect is missing.

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?

Schema coverage is 0%, so the description must compensate, which it does thoroughly: name (substring, case-insensitive), origin (optional, exact match, disambiguate), output_mode (json default or text). This adds substantial meaning beyond the basic schema types.

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 tool reconstructs career history for crew members by name, which distinguishes it from sibling tools like maritime_search_crew (just search) and maritime_get_crew_member (single member). It specifies the action (reconstruct, searches, groups, reconstructs), resource (VOC Opvarenden dataset), and scope (chronological career).

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 provides tips on when to use origin to disambiguate and what fields to look at, but does not explicitly state when to use this tool versus alternatives like maritime_search_crew or maritime_get_crew_member. It implies usage context but lacks explicit when-not or alternative guidance.

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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