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analyze_peak_loads

Read-onlyIdempotent

Decomposes peak heating and cooling loads into components (solar, people, lighting, equipment, infiltration, envelope) and flags unusual timing, excessive loads, or component dominance for QA/QC.

Instructions

Analyze peak heating and cooling loads for QA/QC.

Decomposes facility and zone-level peaks into components (solar, people, lighting, equipment, infiltration, envelope) and flags potential issues such as unusual peak timing, excessive loads, or component dominance.

Requires a completed simulation with SQL output and the SensibleHeatGainSummary and HVACSizingSummary reports. The decomposition needs a weather-file run period; after a design-day-only run, cooling and heating report available=false and only the sizing loads are populated.

Input Schema

Name	Required	Description	Default
No arguments

Output Schema

Name	Required	Description
`flags`	No
`cooling`	Yes	Facility-level peak load with component breakdown and zone ranking. When EnergyPlus recorded no peak, ``available`` is false, ``peak_w`` is ``None``, and ``unavailable_reason`` states why.
`heating`	Yes	Facility-level peak load with component breakdown and zone ranking. When EnergyPlus recorded no peak, ``available`` is false, ``peak_w`` is ``None``, and ``unavailable_reason`` states why.
`sizing_cooling`	No
`sizing_heating`	No
`total_floor_area_m2`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed10 schema fields changedv0.11.0Oct 16, 2026

changedOutput schema / properties / cooling / description

Previous value: -"Facility-level peak load with component breakdown and zone ranking."New value: +"Facility-level peak load with component breakdown and zone ranking.\n\nWhen EnergyPlus recorded no peak, ``available`` is false, ``peak_w`` is ``None``,\nand ``unavailable_reason`` states why."

addedOutput schema / properties / cooling / properties / available
```
Added value: +{
+  "default": true,
+  "type": "boolean"
+}
```

addedOutput schema / properties / cooling / properties / peak_w / anyOf

Added value: +[
+  {
+    "type": "number"
+  },
+  {
+    "type": "null"
+  }
+]

removedOutput schema / properties / cooling / properties / peak_w / type
```
Removed value: -"number"
```

addedOutput schema / properties / cooling / properties / unavailable_reason

Added value: +{
+  "anyOf": [
+    {
+      "type": "string"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null
+}

changedOutput schema / properties / heating / description

Previous value: -"Facility-level peak load with component breakdown and zone ranking."New value: +"Facility-level peak load with component breakdown and zone ranking.\n\nWhen EnergyPlus recorded no peak, ``available`` is false, ``peak_w`` is ``None``,\nand ``unavailable_reason`` states why."

addedOutput schema / properties / heating / properties / available
```
Added value: +{
+  "default": true,
+  "type": "boolean"
+}
```

addedOutput schema / properties / heating / properties / peak_w / anyOf

Added value: +[
+  {
+    "type": "number"
+  },
+  {
+    "type": "null"
+  }
+]

removedOutput schema / properties / heating / properties / peak_w / type
```
Removed value: -"number"
```

addedOutput schema / properties / heating / properties / unavailable_reason

Added value: +{
+  "anyOf": [
+    {
+      "type": "string"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null
+}

First observedv0.9.3Jul 28, 2026

TDQS

A4.7/5.0

Behavior5/5

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

Annotations already cover read-only/idempotent/no-destructive semantics, but the description adds substantive behavior beyond them: the exact component decomposition, the types of anomalies flagged, and a concrete failure mode (design-day-only runs yield available=false with only sizing loads populated). That failure-mode disclosure is the kind of context annotations cannot convey.

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?

Three tight paragraphs: purpose first, then decomposition/flagging behavior, then prerequisites and edge-case behavior. Every sentence carries information an agent needs; no filler or repetition of the name.

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?

With an output schema present, return values need not be described. The description covers purpose, behavioral scope, prerequisites, and a failure mode, leaving nothing material an agent must know before calling it.

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 tool takes zero parameters, which sets a baseline of 4. The description correctly adds nothing about inputs because there are none, and it does not mislead about configurable options.

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?

States a specific verb and resource ('Analyze peak heating and cooling loads') and immediately sharpens it with the decomposition (solar, people, lighting, equipment, infiltration, envelope) and QA/QC flagging behavior. This clearly separates it from neighboring report/query tools like view_simulation_report, query_simulation_table, and run_simulation.

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?

Gives concrete preconditions: a completed simulation with SQL output plus the SensibleHeatGainSummary and HVACSizingSummary reports, and a weather-file run period. It even states what happens after a design-day-only run. It does not name alternative sibling tools for related checks, so it stops short of a 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.