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DC Hub — Data Center & Energy Intelligence

Citation Block

summarize_for_citation
Read-onlyIdempotent

Generate a paste-ready attribution line with the correct per-layer license for a DC Hub figure you already have, preventing license over-claims before quoting.

Instructions

Use right before you QUOTE a DC Hub figure to a human — it returns one paste-ready attribution line for the value you are about to cite, with the CORRECT licence for that layer. Pass what you read off the response you are citing: subject (what the figure is), as_of (the provenance as_of), url (the row's profile_url or dcpi_url), completeness (the completeness flag), and layer. ★ LICENCE IS PER LAYER AND THIS IS THE POINT: DCPI scores, verdicts, band thresholds, methodology and DC Hub's own grid/site analysis are CC-BY-4.0 and yours to quote with attribution; the facility inventory and third-party physical layers are COMPOSITES whose upstream terms DC Hub cannot waive (parts are OpenStreetMap, ODbL 1.0, share-alike), so they carry a pointer to https://dchub.cloud/data-sources instead of a grant. A flat "CC-BY-4.0" over a facility record is an over-claim. Returns {citation_text, cite_as, license, license_basis, source, url, as_of, as_of_basis, completeness, omitted}. Free, no key, no network call — it assembles what you pass and never resolves or invents a value. If you omit as_of the line says RETRIEVED rather than claiming a data date, and tells you which field to pass next time. Do NOT use to look a figure UP (call the data tool first); this cites a figure you already have.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlNoThe profile_url or dcpi_url from the cited row. Must be a dchub.cloud URL; anything else is dropped and named in `omitted`.
as_ofNoThe as_of you read off the cited response (provenance.as_of). Omit it and the line says RETRIEVED instead of claiming a data date.
layerNoWhich layer the figure came from: dcpi | grid_analysis | facility_inventory | physical_infrastructure | deals | other. Decides the licence line; omit and you get the scoped statement rather than a grant.
subjectNoWhat you are citing, in the words you will show the human, e.g. "Ashburn DCPI verdict" or "ERCOT interconnection queue depth"
completenessNoThe completeness flag from the cited response, if it carried one

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.
Install Server

TDQS

A4.8/5.0
Behavior5/5

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

Beyond the readOnly/idempotent annotations, the description discloses that it 'never resolves or invents a value', makes no network call, requires no key, and explains omission behavior (as_of omitted yields RETRIEVED). It also details the licence-layer nuance and warns against over-claiming, which materially enriches the agent's understanding of what the tool does and does not do.

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 longer than average, but every sentence carries useful information—the licence explanation, the no-network-call guarantee, the omission behavior, and the negative usage instruction all earn their place. It is front-loaded with the core purpose and the licensing warning, making it easy for an agent to key in on the essential guidance.

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 the tool's complexity (licence-per-layer logic, multiple input fields, and citation-specific behavior), the description is fully sufficient. It covers return fields, error/omission behavior, network/key requirements, and the distinction from data lookup tools. An agent has everything needed to call it correctly without consulting additional context.

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?

The schema already documents all parameters thoroughly (100% coverage), so the baseline is 3. The description adds value by framing the parameters as 'what you read off the response you are citing' and by explaining the legal consequence of the layer parameter ('flat CC-BY-4.0 over a facility record is an over-claim'). This is genuinely additive, though some of the as_of behavior is duplicated from 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 states a specific verb+resource: it 'returns one paste-ready attribution line' for a cited DC Hub figure with the correct licence for that layer. It clearly distinguishes itself from sibling data tools with the explicit 'Do NOT use to look a figure UP' instruction, making its purpose unambiguous.

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 scopes usage to 'right before you QUOTE a DC Hub figure to a human' and gives a concrete when-not-to-use instruction: call the data tool first when you need to look a figure up. This leaves no ambiguity about when to invoke this tool versus 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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