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azmartone67

DC Hub — Data Center & Energy Intelligence

Analyze Site

analyze_site
Read-onlyIdempotent

Evaluate one property for data-center suitability in a single call, returning a composite 0-100 score covering power, gas, fiber, market, and risk.

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 or location), lon (-180 to 180, required unless candidate_id or location), location (a market NAME or metro slug instead of coordinates, e.g. location="ashburn" — resolved to that market's PUBLISHED CENTROID through the DCPI market row, with a resolved_from block naming what it resolved to; a MARKET-level read, NOT the parcel you named, and a trailing state is not stripped so "Ashburn, VA" will not resolve), 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 — returns a capacity_context block sizing that load against nearby installed generation; it deliberately does NOT move overall_score, and the block names where the load IS applied), 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 or location given), e.g. 33.45
lngNoAlias for lon — either name works
lonNoSite longitude in decimal degrees (-180 to 180; required unless candidate_id or location given), e.g. -112.07
stateNoUS state abbreviation (optional) — improves the tax-incentive lookup, e.g. AZ
latitudeNoAlias for lat — either name works
locationNoMarket NAME or metro slug instead of coordinates, e.g. "ashburn", "northern-virginia", "dallas". Resolved to that market's PUBLISHED CENTROID through the DCPI market row, and the answer carries a resolved_from block saying so. This is a MARKET-level read, not the parcel you named — pass lat/lon for a specific site. Not an alias for lat/lon: a place name is not a coordinate.
longitudeNoAlias for lon — either name works
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)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
fiberNoFiber read: {connectivity_score, nearest_carrier_km, near_net_bucket, top_carriers[], single_carrier_risk} (full payload)
quotaNoCaller quota state (remaining calls, tier) when available.
lockedNoWhich sections are Pro-locked on the free headline: {per_factor_breakdown, nearby_infrastructure, power_cost, fiber_carriers, site_analysis_report}
nearbyNoNearby infrastructure counts: {substations_50km, power_plants_80km, gas_pipelines_50km, facilities_100km, fiber_carriers_in_state, generation_capacity_mw, total_capacity_mw} (full payload)
scoresNoPer-factor breakdown (full/paid payload)
_entityNoPayload class discriminator (e.g. facility|market|iso_grid|queue_results|deal|report|response) — branch on this before parsing the rest.
previewNoHeadline preview line (free tier)
verdictNoVerdict string, e.g. "Excellent site" / BUILD-CAUTION-AVOID read
citationNoMachine-readable citation: how to attribute DC Hub (dchub.cloud) for this payload. Normally an OBJECT {source, url, license, cite_as, retrieved_at}; a bare string is accepted and carries the attribution line itself.
locationNoEcho of the analyzed location (full payload)
power_costNoPower cost read: {industrial_cents_kwh, commercial_cents_kwh, period, basis} (full payload)
provenanceNoCollection-level provenance block: {source, method, as_of, verification_counts, cite_url_template, license, cite_as}. Quote the verification level when citing.
_front_doorNoIn-band front-door hint (first workflow-entry tool of a session): call plan_query(intent) first for the ordered multi-step plan.
_return_loopNoSuggested next-session delta call (get_changes since=24h) so you pull only what changed.
overall_scoreNoAlias of composite_score on the full payload
site_headlineNotrue when this is the free citable HEADLINE (score + verdict + limiting factor)
interpretationNoVerdict prose on the full payload
composite_scoreNo0-100 composite site suitability score (free HEADLINE tier and full tier)
limiting_factorNoSingle top limiting factor (the lowest sub-score) — always present on the free headline
site_evaluation_handoffNoPre-built follow-up calls (analyze_site / get_water_risk args) when the payload carries coordinates — an array of {tool, parameters, why} entries.
Install Server

TDQS

A5/5.0
Behavior5/5

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

Beyond readOnly/idempotent annotations, it discloses key behaviors: location resolves to market centroid rather than parcel, candidate_id uses frozen mint and fails closed with candidate_expired, capacity_mw adds a capacity_context block without moving overall_score, and free vs Pro returns are clearly separated.

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?

Long but dense: front-loaded use case, example, parameter notes, return structure, and routing exclusions. No filler; the length is justified by 12 parameters and several behavioral caveats.

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?

Covers input modes, output shape, free/pro constraints, alias semantics, failure behavior, and alternative tools. An agent has everything needed to decide, call, and interpret this tool without extra lookups.

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?

Even with 100% schema coverage, the description adds meaning: it explains parameter relationships and side effects (capacity_mw sizing, location's resolved_from block, candidate_id ignoring lat/lon, state improving tax lookup), which are not evident from the schema alone.

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 opens with an explicit use case ('ONE specific lat/lon... full multi-factor data-center suitability read') and gives a concrete example. It differentiates itself from siblings by naming what it is not (compare_sites, find_alternatives).

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?

It provides explicit when-to-use guidance, a call example, and direct exclusions with named alternatives: water/disaster/climate/tax reads route to get_water_risk etc., 2+ sites to compare_sites, site matching to find_alternatives.

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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