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AI Capacity Index

ai_capacity_index
Read-onlyIdempotent

AI Compute Capacity Index: ranks data center markets by where 100MW of AI training capacity can land in the next 30/60/90 days. Returns top markets with facility_count, operator_count, deployable_mw estimate (megawatts), hyperscale_ready flag, rack power density and cooling-type signals where facility data carries them, and composite score (depth + diversity + power). Refreshed Fridays 14:00 UTC. Use for AI capex planning, GPU cluster siting, hyperscaler deal forecasting. For grid power availability use DCPI (rank_markets ai_ready). Do NOT use for a general best-markets ranking (use rank_markets) or forward grid-emergence (use grid_transition_radar).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoNumber of top markets to return (default 20)
horizonNoDeployment horizon in days: 30, 60, or 90 (default 90)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
quotaNoCaller quota state (remaining calls, tier).
_entityNoPayload class (facility|market|iso_grid|queue_results|deal|report|response); branch on it.
citationNoHow to attribute DC Hub: {source, url, license, cite_as, retrieved_at}, or the attribution line as a string.
provenanceNoSource, method, as_of, verification_counts, license, cite_as; quote it when citing.
_front_doorNoFirst-tool hint: plan_query(intent) returns the ordered plan.
_return_loopNoNext-session delta call (get_changes).
site_evaluation_handoffNoFollow-up calls [{tool, parameters, why}] when the payload carries coordinates.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added
  2. Removed
  3. Changed2 schema fields changed
    • removedInput schema / $schema
      Removed value: -"http://json-schema.org/draft-07/schema#"
    • removedOutput schema / $schema
      Removed value: -"http://json-schema.org/draft-07/schema#"
  4. Changed5 schema fields changed
    • removedOutput schema / properties / citation / additionalProperties
      Removed value: -{}
    • addedOutput schema / properties / citation / anyOf
      Added value: +[
      +  {
      +    "additionalProperties": {},
      +    "properties": {},
      +    "type": "object"
      +  },
      +  {
      +    "type": "string"
      +  }
      +]
    • changedOutput schema / properties / citation / description
      Previous value: -"Machine-readable citation: how to attribute DC Hub (dchub.cloud) for this payload."New value: +"Machine-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."
    • removedOutput schema / properties / citation / properties
      Removed value: -{}
    • removedOutput schema / properties / citation / type
      Removed value: -"object"
  5. Changed1 schema field changed
    • addedOutput schema / properties / _front_door
      Added value: +{
      +  "additionalProperties": {},
      +  "description": "In-band front-door hint (first workflow-entry tool of a session): call plan_query(intent) first for the ordered multi-step plan.",
      +  "properties": {},
      +  "type": "object"
      +}
  6. Changed5 schema fields changed
    • removedOutput schema / properties / site_evaluation_handoff / additionalProperties
      Removed value: -{}
    • addedOutput schema / properties / site_evaluation_handoff / anyOf
      Added value: +[
      +  {
      +    "items": {
      +      "additionalProperties": {},
      +      "properties": {},
      +      "type": "object"
      +    },
      +    "type": "array"
      +  },
      +  {
      +    "additionalProperties": {},
      +    "properties": {},
      +    "type": "object"
      +  }
      +]
    • changedOutput schema / properties / site_evaluation_handoff / description
      Previous value: -"Pre-built follow-up call (analyze_site / get_water_risk args) when the payload carries coordinates."New value: +"Pre-built follow-up calls (analyze_site / get_water_risk args) when the payload carries coordinates — an array of {tool, parameters, why} entries."
    • removedOutput schema / properties / site_evaluation_handoff / properties
      Removed value: -{}
    • removedOutput schema / properties / site_evaluation_handoff / type
      Removed value: -"object"
  7. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
      +  "$schema": "http://json-schema.org/draft-07/schema#",
      +  "additionalProperties": {},
      +  "description": "DC Hub envelope: structuredContent mirrors the JSON payload in content[0].text — tool-specific data fields ride at the top level alongside these envelope keys.",
      +  "properties": {
      +    "_entity": {
      +      "description": "Payload class discriminator (e.g. facility|market|iso_grid|queue_results|deal|report|response) — branch on this before parsing the rest.",
      +      "type": "string"
      +    },
      +    "_return_loop": {
      +      "additionalProperties": {},
      +      "description": "Suggested next-session delta call (get_changes since=24h) so you pull only what changed.",
      +      "properties": {},
      +      "type": "object"
      +    },
      +    "citation": {
      +      "additionalProperties": {},
      +      "description": "Machine-readable citation: how to attribute DC Hub (dchub.cloud) for this payload.",
      +      "properties": {},
      +      "type": "object"
      +    },
      +    "provenance": {
      +      "additionalProperties": {},
      +      "description": "Collection-level provenance block: {source, method, as_of, verification_counts, cite_url_template, license, cite_as}. Quote the verification level when citing.",
      +      "properties": {},
      +      "type": "object"
      +    },
      +    "quota": {
      +      "additionalProperties": {},
      +      "description": "Caller quota state (remaining calls, tier) when available.",
      +      "properties": {},
      +      "type": "object"
      +    },
      +    "site_evaluation_handoff": {
      +      "additionalProperties": {},
      +      "description": "Pre-built follow-up call (analyze_site / get_water_risk args) when the payload carries coordinates.",
      +      "properties": {},
      +      "type": "object"
      +    }
      +  },
      +  "type": "object"
      +}
  8. Changed6 schema fields changed
    • addedInput schema / properties / horizon / description
      Added value: +"Deployment horizon in days: 30, 60, or 90 (default 90)"
    • changedInput schema / properties / horizon / maximum
      Previous value: -9007199254740991New value: +90
    • changedInput schema / properties / horizon / minimum
      Previous value: --9007199254740991New value: +30
    • addedInput schema / properties / limit / description
      Added value: +"Number of top markets to return (default 20)"
    • changedInput schema / properties / limit / maximum
      Previous value: -9007199254740991New value: +500
    • changedInput schema / properties / limit / minimum
      Previous value: --9007199254740991New value: +1
  9. Added

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already establish read-only, idempotent, non-destructive behavior, so the description only needs to add context beyond that. It does: refresh cadence (Fridays 14:00 UTC) and the composition of returned signals (facility_count, operator_count, deployable_mw, hyperscale_ready, rack density, cooling type, composite depth+diversity+power). It does not state coverage limits or data staleness caveats, but the added freshness/return context is solid.

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?

Front-loads what the index is and what it returns before the usage and exclusion clauses, and every sentence carries routing or field information. It is dense and one clause longer than strictly needed, but not padded.

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?

An output schema exists, so return values need no prose elaboration, and the description still summarizes them. Combined with use cases, refresh cadence, and sibling disambiguation, an agent has everything needed to select and call it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%: limit and horizon are both documented with type, range, and defaults. The description mentions 30/60/90 days but adds no format, syntax, or edge-case meaning beyond what the schema already carries, so baseline 3 applies.

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?

States a specific verb, resource, and scope: ranking data center markets by 100MW AI-training deployability over 30/60/90-day horizons. It explicitly distinguishes itself from rank_markets (general ranking) and grid_transition_radar (forward grid emergence), so an agent can route correctly without opening a schema.

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?

Gives explicit positive use cases (AI capex planning, GPU cluster siting, hyperscaler deal forecasting), a redirect for grid power (DCPI via rank_markets ai_ready), and two explicit do-not-use cases with named alternatives. Nothing is left to inference.

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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