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analyze_site

Read-onlyIdempotent

Score a single parcel for data-center suitability using power, gas, fiber, market, and risk factors. Returns overall score and verdict.

Instructions

Use when a user has ONE specific lat/lon (a parcel, a candidate site) and wants the full multi-factor data-center suitability read in one call. Example: "Score this Phoenix parcel for a 100MW build — power, gas, fiber, market & risk." — analyze_site lat=33.45 lon=-112.07 capacity_mw=100 state=AZ. Params: lat (-90 to 90, required unless candidate_id), lon (-180 to 180, required unless candidate_id), candidate_id (a cand_… from get_refined_queue — resolves coordinates from the frozen mint and ignores lat/lon), capacity_mw (target load in MW, e.g. 50-500), state (2-letter US, optional — improves the tax-incentive/context lookup), include_grid/include_risk/include_fiber (booleans, default true). Returns (full, paid): {overall_score (aka composite_score, 0-100 composite — for the integrity-first version that never imputes a missing factor, use get_composite_site_score), interpretation (verdict string, e.g. "Excellent site"), scores{power_infrastructure, gas_pipeline_access, fiber_connectivity, market_conditions, risk_resilience — each 0-100}, nearby{substations_50km, power_plants_80km, gas_pipelines_50km, facilities_100km, fiber_carriers_in_state, generation_capacity_mw, total_capacity_mw}, power_cost{industrial_cents_kwh, commercial_cents_kwh, period, basis}, fiber{connectivity_score, nearest_carrier_km, near_net_bucket, top_carriers[], single_carrier_risk}, location, citation}. FREE tier returns a REAL, citable HEADLINE — composite_score + verdict + the single top limiting factor (the lowest sub-score) + citation; the full per-factor breakdown, nearby infrastructure, power cost, fiber carriers, and the branded Site Analysis PDF (generate_site_analysis) are Pro. For dedicated water / disaster / climate / tax reads use get_water_risk / get_disaster_risk / get_climate_intel / get_tax_incentives. Do NOT use to compare 2+ sites (use compare_sites) or to find sites that match a target (use find_alternatives).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
latNoSite latitude in decimal degrees (-90 to 90; required unless candidate_id given), e.g. 33.45
lonNoSite longitude in decimal degrees (-180 to 180; required unless candidate_id given), e.g. -112.07
stateNoUS state abbreviation (optional) — improves the tax-incentive lookup, e.g. AZ
capacity_mwNoTarget power load for the build in megawatts (MW), e.g. 100 (typical 50-500)
candidate_idNoPREFERRED for queue survivors: a cand_… id from get_refined_queue — coordinates come from the FROZEN mint (lat/lon args are ignored; zero transcription drift; expired ids fail closed with candidate_expired). See dchub.cloud/docs/candidate-lifecycle
include_gridNoInclude grid-headroom / substation analysis (default true)
include_riskNoInclude water/drought/climate risk analysis (default true)
include_fiberNoInclude fiber-connectivity analysis (default true)
Behavior5/5

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

Annotations declare readOnlyHint=true, idempotentHint=true, which align with the description of a read operation. Description adds details on free vs pro returns, candidate_id expiration, and the integrity-first score variant, going beyond 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?

Description is long but well-structured with clear sections: when to use, example, parameters, returns, free/pro, and exclusions. Every sentence adds value, but could be slightly trimmed 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 8 parameters and no output schema, the description is remarkably complete: explains free vs pro return structure, candidate lifecycle, and alternative tools for specific dimensions. Only minor omission is broader error scenarios.

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?

Input schema has 100% description coverage, but the tool description adds critical context: the relationship between lat/lon and candidate_id, mutual exclusivity, and the behavior of candidate_id (frozen mint, transcription drift). Also explains the boolean flags and the capacity_mw range.

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?

Description clearly states 'analyze a site' for one specific lat/lon or candidate_id, providing a verb and resource. It distinguishes from siblings like compare_sites and find_alternatives, and uses a concrete example.

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?

Explicitly states when to use (one site, full multi-factor read) and when not to (comparing or finding sites), with specific alternatives mentioned. Also explains free vs pro usage.

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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