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Chuk MCP Maritime Archives

by IBM

maritime_did_speed_test

Tests whether the difference between eastbound and westbound sailing speeds changed significantly between two time periods, using bootstrap resampling to isolate wind changes from symmetric technology improvements.

Instructions

Formal 2x2 Difference-in-Differences test: direction x period.

Tests whether the difference between eastbound and westbound speeds changed significantly between two time periods. A significant DiD means one direction gained more than the other — isolating wind changes from symmetric technology improvements.

DiD = (period2_east - period1_east) - (period2_west - period1_west)

Uses bootstrap resampling for confidence intervals and p-values. Defaults to voyage-level aggregation for statistically independent samples (daily observations within a voyage are autocorrelated).

Args: period1_years: First period as "YYYY/YYYY" range or "YYYY,YYYY,..." list period2_years: Second period as "YYYY/YYYY" range or "YYYY,YYYY,..." list lat_min: Minimum latitude for position bounding box lat_max: Maximum latitude for position bounding box lon_min: Minimum longitude for position bounding box lon_max: Maximum longitude for position bounding box nationality: Filter tracks by nationality code month_start: Filter by start month (1-12). Supports wrap-around month_end: Filter by end month (1-12). Used with month_start aggregate_by: "voyage" (default, independent samples) or "observation" (more data but autocorrelated) n_bootstrap: Bootstrap iterations (default: 10000) min_speed_km_day: Minimum speed filter (default: 5.0) max_speed_km_day: Maximum speed filter (default: 400.0) wind_force_min: Minimum Beaufort force (0-12). Requires wind data wind_force_max: Maximum Beaufort force (0-12). Requires wind data exclude_years: Years to exclude from both periods, as "YYYY/YYYY" range or "YYYY,YYYY,..." list. output_mode: Response format - "json" (default) or "text"

Returns: JSON or text with 4-cell summary, marginal diffs, DiD estimate, bootstrap 95% CI, and p-value

Tips for LLMs: - Always splits by direction (eastbound vs westbound) - Use lat_min=-50, lat_max=-30 for the Roaring Forties - Positive DiD = eastbound gained more = wind strengthened - Use wind_force_min/max for Beaufort-stratified DiD - Default aggregate_by="voyage" gives correct p-values - If DiD scales with Beaufort, that is genuine wind change - Periods accept comma-separated year lists for non-contiguous years (e.g., "1720,1728,1747" for ENSO El Nino years)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
period1_yearsYes
period2_yearsYes
lat_minNo
lat_maxNo
lon_minNo
lon_maxNo
nationalityNo
month_startNo
month_endNo
aggregate_byNovoyage
n_bootstrapNo
min_speed_km_dayNo
max_speed_km_dayNo
wind_force_minNo
wind_force_maxNo
exclude_yearsNo
output_modeNojson
Behavior4/5

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

Discloses DiD formula, bootstrap resampling, aggregation rationale, and default parameters. No annotations provided, so description carries behavioral burden well. No contradictions.

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?

Well-structured with sections, formula, and LLM tips. Slightly verbose in parameter descriptions (some redundancy with schema defaults), but overall efficient and front-loaded.

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 covers purpose, methodology, all parameters, return format (4-cell summary, marginal diffs, DiD estimate, bootstrap CI, p-value), and interpretation. No output schema, but description compensates completely.

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?

With 0% schema description coverage, description thoroughly explains all 17 parameters, including defaults, formats (e.g., 'YYYY/YYYY' range), examples (lat_min=-50 for Roaring Forties), and usage guidance (wind_force_min/max for Beaufort-stratified DiD).

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?

Clearly states it's a 'Formal 2x2 Difference-in-Differences test: direction x period' and explains what it measures (difference between eastbound and westbound speeds over two periods). Distinct from sibling tools like maritime_compare_speed_groups or maritime_wind_direction_by_year.

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?

Provides tips for LLMs on when to use (e.g., wind change analysis), how to interpret results (positive DiD = wind strengthened), and defaults (aggregate_by='voyage'). Doesn't explicitly mention alternatives, but context is clear.

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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