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DC Hub — Data Center & Energy Intelligence

Research Dossier (async)

research_task
Read-onlyIdempotent

Commission a research dossier: submit a question for a cited synthesis across DC Hub's data-center and energy corpora, then poll the returned task ID to fetch the finished brief.

Instructions

Commission an ASYNC, CITED research dossier from DC Hub's corpora (news, deals, facilities, market deep-dive narratives + live market components) — a decision-ready analyst brief with [n] citations, not a lookup. Requires a key (one claim_free_key call), 5 dossiers/day. Submits the question, waits up to ~35s for completion, and returns the finished dossier inline when ready; if still running, returns {task_id} — call research_task task_id= to fetch it. Params: question (required for a new dossier, min 12 chars) OR task_id (poll an earlier one). Typical completion under a minute. Answers "write me a cited brief on this", "what do recent deals say about gas-bridged power". Try: research_task question="What do recent deals say about gas-bridged power for data centers in ERCOT?". Do NOT use for a single fact (use search_intelligence / semantic_search); this synthesizes ACROSS sources with citations.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
task_idNoPoll an earlier submission: the task_id returned by a previous research_task call
questionNoThe research question (min 12 chars) — omit when polling with task_id

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?

The description discloses important behavioral traits beyond annotations: async execution, ~35s wait, inline return vs task_id response, polling mechanism, rate limit, and key requirement. It complements the readOnly/idempotent/destructive hints without contradicting them.

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 purpose and includes high-value exclusions, examples, and constraints. It is somewhat dense and repeats a few details already present in the schema, but every section earns its place given the async complexity.

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?

The description fully covers the async lifecycle: submit, wait, poll, fetch, quota, and key requirement. With an output schema present for return values, nothing needed for correct invocation is missing.

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?

Schema coverage is 100%, so the baseline is 3. The description adds meaningful OR-choice semantics: question for a new dossier vs task_id for polling, plus example usage. Some details repeat schema descriptions, but the added context still raises the value.

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 names a specific action ('Commission'), a specific resource ('ASYNC, CITED research dossier'), and the scope of sources (DC Hub's corpora). It also explicitly contrasts this with 'not a lookup', helping distinguish it from the many sibling search and get tools.

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?

The description explicitly states when to use the tool ('synthesizes ACROSS sources with citations') and when not to ('Do NOT use for a single fact'), naming the alternatives (search_intelligence / semantic_search). It also covers the key requirement, daily quota, and async polling workflow.

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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