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get_power_service_quote

Create a signed, 15-minute, scope-bound quote for EnergyAI’s $1 Power Screen from non-sensitive site and workload facts. Returns the quoteToken required by run_power_screen, exact price, evidence boundary, authorization class, and higher-tier handoffs. Free and never spends funds. [always free — no API key required]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
stagedMwNoOptional first-stage load in MW; defaults to the lesser of 4 MW and targetMw.
targetMwYesTarget compute or flexible-load capacity in MW.
coolingModeNounknown
siteLocationYesCounty/state, balancing area, or approximate site. Do not send a street address or contact information.
storageHoursNoOptional available storage duration in hours.
workloadTypeYes
powerEvidenceNoBuyer-stated evidence maturity; confirmed still requires documentary verification.unknown
flexibilityHoursNoHours per week the workload can shift.

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden and does well: it discloses that the tool is 'signed, 15-minute, scope-bound', 'Free and never spends funds', 'always free — no API key required', and enumerates return outputs. It does not describe rate limits, error behavior, or data retention, but for a no-annotation tool this is strong coverage.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences plus a short bracketed tag. Purpose is front-loaded, followed by return values and cost assurance. There is no filler or repeated schema information.

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?

With no output schema, the description lists the key return items (quoteToken, exact price, evidence boundary, authorization class, higher-tier handoffs) and connects the tool to run_power_screen. It could define terms like 'evidence boundary' or 'higher-tier handoffs' more precisely, but it gives enough for an agent to invoke the tool 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 75%, so most parameters are already documented. The description adds a useful constraint that inputs should be 'non-sensitive site and workload facts' and reinforces scope, but it does not explain individual parameters beyond the schema. This is a solid baseline given the coverage.

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 opens with a specific verb and resource: 'Create a signed, 15-minute, scope-bound quote for EnergyAI's $1 Power Screen'. It clearly distinguishes this from siblings by naming the returned quoteToken as required by run_power_screen, so an agent can tell this is the prerequisite quoting tool rather than a generic quote or screen runner.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description states a clear context: this tool produces the quoteToken needed by run_power_screen, and it is explicitly free and safe to call. However, it does not name any alternatives or exclusions (e.g., when to use get_quote_link instead), so it falls short of fully explicit routing.

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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TDQS

C2.8/5.0
Disambiguation2/5

Several tools overlap heavily: get_node_score vs get_energy_node_score, find_local_installers vs match_installers, and route_lead vs submit_contractor_match_request are easy to confuse. The descriptions clarify details, but an agent would often need to inspect arguments to know which installer, incentive, or recommendation tool is the right one.

Naming Consistency3/5

All tool names use snake_case with a verb-leading style, which provides a consistent backbone. However, domain naming is inconsistent: the same concept appears as node vs energy_node, installer vs contractor, and incentive discovery is split across check_incentives, get_energy_incentives, list_guides, and get_guide without a predictable pattern.

Tool Count2/5

29 tools is too many for a single MCP server, especially since several fall into overlapping installer/lead, incentive, recommendation, and commercial-power categories. Many tools appear to be monetization gates or handoff variants that could reasonably be consolidated.

Completeness3/5

The set covers core user journeys: assessment creation/answering/completion, incentive guidance, installer discovery and routing, quote review, and commercial power screens. However, there are notable gaps in state management, such as no way to list or retrieve existing assessments/leads, and several checkout or handoff tools have no follow-up/status tool.