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get_climate_intel

Read-onlyIdempotent

Retrieve seismic hazard data (USGS ASCE 7) and NOAA climate normals for a latitude/longitude. Returns peak ground acceleration, seismic design category, cooling degree-days, and extreme temperatures for data center site evaluation.

Instructions

Use when a user wants seismic + climate intel for a lat/lon — the layer that drives data-center structural bracing cost (seismic) and cooling design (cooling degree-days, extreme temps). Grounded STRICTLY in USGS ASCE 7 (seismic) + NOAA climate normals via ACIS; every value traces to a federal source and missing data is declared unavailable, never estimated. Example: get_climate_intel lat=33.45 lon=-112.07. Returns {seismic_hazard_usgs:{status, peak_ground_acceleration_g, ss, s1, seismic_design_category, hazard_class}, climate_normals_noaa:{status, reference_station:{id,name,distance_km}, cooling_design_metrics:{cooling_degree_days_annual, extreme_max_dry_bulb_f, extreme_max_wet_bulb_f (null if source lacks it), data_vintage}}, overall_climate_summary, data_availability, sources}. radius_km (optional, default 25) snaps to the nearest NOAA station; beyond it climate returns unavailable_exceeds_radius. Seismic is US (ASCE 7); non-US → seismic unavailable. For natural-hazard ratings use get_disaster_risk; for one blended verdict use get_composite_site_score.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
latNoSite latitude in decimal degrees (-90 to 90, required), e.g. 33.45
lonNoSite longitude in decimal degrees (-180 to 180, required), e.g. -112.07
radius_kmNoMax distance (km) to snap to the nearest NOAA station (optional, default 25)
Behavior5/5

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

Discloses data sources (USGS, NOAA), behavior for non-US locations (unavailable), radius constraints, and the fact that missing data is declared unavailable—all beyond annotations which only indicate read-only and idempotent.

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?

Despite length, every sentence is purposeful: starts with usage, explains constraints, lists output structure, and ends with sibling references. Efficient and well-organized.

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?

Description fully equips the agent with output format, constraints (US-only seismic, radius limits), data provenance, and example usage—no missing critical details despite no output schema.

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?

Input schema has 100% coverage, but the description adds meaning by explaining radius behavior (snap to nearest station, unavailable beyond limit) and providing an example, exceeding baseline.

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 explicitly states the tool provides seismic and climate intel for a lat/lon, with clear differentiation from siblings (get_disaster_risk, get_composite_site_score).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Clearly states when to use ('Use when a user wants seismic + climate intel for a lat/lon') and provides alternatives for related tools, guiding the agent on tool 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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