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DC Hub — Data Center & Energy Intelligence

Semantic Search

semantic_search
Read-onlyIdempotent

Retrieve meaning-based answers to conceptual questions covering data center news, M&A deals, facilities, and market analyses, with relevant results ranked and cited.

Instructions

Use for CONCEPTUAL / fuzzy questions where keyword filters fall short — semantic (meaning-based) retrieval across DC Hub's industry news, M&A deals, 22,100+ discovered facilities, and per-market DCPI deep-dive analysis narratives, ranked by relevance with citable source fields (news url/title, deal parties/value, facility name/location, deep-dive market/url). Examples: "what is happening with behind-the-meter gas for AI data centers?", "deals involving nuclear power for hyperscalers", "why is Northern Virginia constrained?" — semantic_search q="behind-the-meter gas for AI data centers". Params: q (required, natural-language query); corpus (optional CSV subset of news_articles,deals,discovered_facilities,market_narratives; default all); k (1-15, default 8). Returns {results:[{source_table, kind, text, score, cite:{…}}]}. Complements the exact-filter tools (get_news / list_transactions / search_facilities) with relevance ranking; for a full token-budgeted market briefing use get_market_context. Cite "DC Hub (dchub.cloud)".

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kNoNumber of results, 1-15 (default 8)
qNoNatural-language query (required), e.g. "grids opening up for AI load in the Southeast"
queryNoAlias for q — the same natural-language query; send exactly one of q/query
corpusNoOptional CSV of corpora: news_articles, deals, discovered_facilities, market_narratives (default: all)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
quotaNoCaller quota state (remaining calls, tier) when available.
_entityNoPayload class discriminator (e.g. facility|market|iso_grid|queue_results|deal|report|response) — branch on this before parsing the rest.
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.
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.
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.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • removedInput schema / $schema
      Removed value: -"http://json-schema.org/draft-07/schema#"
    • removedOutput schema / $schema
      Removed value: -"http://json-schema.org/draft-07/schema#"
  2. Changed5 schema fields changedv2.3.20
    • removedOutput schema / properties / citation / additionalProperties
      Removed value: -{}
    • addedOutput schema / properties / citation / anyOf
      Added value: +[
      +  {
      +    "additionalProperties": {},
      +    "properties": {},
      +    "type": "object"
      +  },
      +  {
      +    "type": "string"
      +  }
      +]
    • changedOutput schema / properties / citation / description
      Previous value: -"Machine-readable citation: how to attribute DC Hub (dchub.cloud) for this payload."New value: +"Machine-readable citation: how to attribute DC Hub (dchub.cloud) for this payload. Normally an OBJECT {source, url, license, cite_as, retrieved_at}; a bare string is accepted and carries the attribution line itself."
    • removedOutput schema / properties / citation / properties
      Removed value: -{}
    • removedOutput schema / properties / citation / type
      Removed value: -"object"
  3. Changed1 schema field changedv2.3.14
    • changedInput schema / properties / query / description
      Previous value: -"Alias for q"New value: +"Alias for q — the same natural-language query; send exactly one of q/query"
  4. Changed1 schema field changedv2.3.12
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
      +  "$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"
      +    },
      +    "_front_door": {
      +      "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"
      +    },
      +    "_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": {
      +      "anyOf": [
      +        {
      +          "items": {
      +            "additionalProperties": {},
      +            "properties": {},
      +            "type": "object"
      +          },
      +          "type": "array"
      +        },
      +        {
      +          "additionalProperties": {},
      +          "properties": {},
      +          "type": "object"
      +        }
      +      ],
      +      "description": "Pre-built follow-up calls (analyze_site / get_water_risk args) when the payload carries coordinates — an array of {tool, parameters, why} entries."
      +    }
      +  },
      +  "type": "object"
      +}
  5. Addedv2.3.7

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already mark the tool as read-only, idempotent, and non-destructive. The description adds useful behavioral context beyond those: results are 'ranked by relevance', span multiple corpora, and include citable source fields, plus a concrete results shape. It does not address auth or rate limits, but for a read-only retrieval tool this is sufficient.

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?

The description is front-loaded with the primary use case and then organized into examples, params, returns, and routing to alternatives. It is somewhat long and repeats some schema content, but every section earns its place and the structure makes it skimmable.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the output schema and rich annotations, the description is nearly complete: it covers purpose, when to use it, parameter defaults, return shape, and citable source fields. The main gap is not mentioning the `query` alias, though that is already covered in the input schema.

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 coverage is 100%, so the baseline is 3. The description adds multi-domain example queries and restates defaults for k and corpus, but it largely repeats schema descriptions, omits the `query` alias, and says `q` is required even though the schema/context signal does not mark it required. Overall, it adds only modest value beyond the schema.

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 clearly states a specific operation: semantic, meaning-based retrieval across four named corpora (news, deals, facilities, market narratives). It also distinguishes itself from exact-filter tools by targeting conceptual/fuzzy questions, and provides concrete examples that make its scope unmistakable.

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 explicitly says when to use the tool ('CONCEPTUAL / fuzzy questions where keyword filters fall short') and when to prefer alternatives: get_news / list_transactions / search_facilities for exact filters, and get_market_context for a full token-budgeted briefing. This is direct when/when-not guidance.

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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