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IBM

Chuk MCP Maritime Archives

by IBM

maritime_get_speed_profile

Retrieve historical sailing speed statistics for a route, including mean, median, and standard deviation of daily distances, with optional filtering by departure month to analyze seasonal wind patterns.

Instructions

Get historical sailing speed statistics for a route.

Returns per-segment speed profiles derived from CLIWOC ship track data, including mean, median, and standard deviation of daily distances (km/day). Optionally filtered by departure month for seasonal variation.

Args: route_id: Route identifier (e.g., "outward_outer", "return"). Use maritime_list_routes to see available routes. departure_month: Optional month (1-12) for seasonal speed data. If not provided, returns all-months aggregate. output_mode: Response format — "json" (default) or "text"

Returns: JSON or text with per-segment speed statistics

Tips for LLMs: - Compare different months to see seasonal wind patterns (e.g., monsoon effects on Indian Ocean segments) - Use with maritime_estimate_position for more informed position estimation - High std_dev indicates variable conditions on a segment - Low sample_count means less reliable statistics - The mean_km_day can help assess whether a voyage was running ahead or behind schedule

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
route_idYes
departure_monthNo
output_modeNojson
Behavior3/5

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

Without annotations, the description partially bears the burden. It discloses data source (CLIWOC) and output details but omits side effects, auth requirements, or rate limits. The description implies read-only behavior but doesn't confirm it.

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 well-structured with summary, Args, Returns, and Tips sections. It front-loads the core purpose. While comprehensive, it could be slightly more concise without losing clarity.

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 no output schema and three parameters, the description is fully complete: it explains output format (JSON/text), lists return fields (mean_km_day, std_dev, sample_count) in tips, and covers all inputs. No gaps remain.

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 fully compensates by detailing each parameter: route_id usage, departure_month as optional filter, output_mode with default and examples. It adds significant meaning beyond the 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 gets historical sailing speed statistics for a route, including specific metrics (mean, median, std dev) and optional seasonal filtering. It effectively distinguishes the tool from siblings by focusing on route-level speed profiles.

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 tips for LLMs on comparing months and using with other tools, implying appropriate use cases. However, it does not explicitly state when not to use this tool or contrast it with alternatives like maritime_aggregate_track_speeds.

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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