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azmartone67

DC Hub — Data Center & Energy Intelligence

Unlock More Data

unlock_more_data

Unlock complete datasets when results appear as previews or tools are locked. Returns upgrade plans and one-click checkout links; after payment, the next call returns full data.

Instructions

Unlock DC Hub's full depth. Call this when a result came back as a 1-of-N preview, a tool was locked, or your human wants the complete dataset. Returns the upgrade ladder + ready-to-paste checkout links your human completes in ONE click — after which your very next call returns full data (no reconnect; the checkout binds to this session). Cheapest start: 💳 $10 one-time = 1,000 API calls (no subscription). Also $9/mo Starter · $49/mo Developer · $299/mo Pro. Want the FREE identified tier instead (no payment, 10 calls/day, all tools)? Call claim_free_key. Param: reason (optional — what you were trying to do, so your human sees why it matters). Returns {plans, human_message, what_unlocks}.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
reasonNoOptional free-text describing what you were trying to do, so your human sees why an upgrade matters

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.
Behavior5/5

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

The description goes beyond annotations (which are sparse and non-mutating) by explaining the upgrade flow, session binding (no reconnect), the one-click checkout, and that the next call returns full data. It also includes pricing details and what the return object contains, offering full behavioral transparency.

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 dense but every sentence carries practical information: trigger conditions, return structure, pricing, alternative, and parameter explanation. While slightly long, it's well-structured and front-loaded with the core purpose, earning a 4 rather than a 5.

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 monetization/upgrade function, the description covers all necessary context: when to use, what it returns, how the upgrade binds to the session, pricing tiers, and an alternative free path. The presence of an output schema is supplemented by the description's explicit mention of the return fields, making it complete for an agent to act on.

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% and the single optional 'reason' parameter is already well-described in the schema. The description adds marginal context about its purpose ('so your human sees why it matters'), but this is essentially a restatement of the schema description, so a baseline 3 is appropriate.

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 the tool's purpose: to unlock full data access by returning upgrade links. It specifies the triggering conditions (1-of-N preview, locked tool, human wants complete dataset) and explicitly distinguishes itself from claim_free_key, making it distinct among siblings.

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 ('Call this when a result came back as a 1-of-N preview, a tool was locked, or your human wants the complete dataset') and names the alternative free tier (claim_free_key), giving clear decision criteria.

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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