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idfkit

idfkit-mcp

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by idfkit

query_simulation_table

Read-onlyIdempotent

Retrieve tabular data from the last simulation's SQL output to analyze energy use, envelope, HVAC sizing, and comfort beyond standard diagnostics.

Instructions

Query tabular report data from the last simulation's SQL output.

Use this for deeper analysis beyond the structured diagnostics in idfkit://simulation/results. Tabular data covers every EnergyPlus summary report: energy use, envelope, HVAC sizing, comfort, and more.

Omit table_name to retrieve all tables within a report at once. To discover available report names call list_simulation_reports first. Common report names:

  • AnnualBuildingUtilityPerformanceSummary — site/source energy, end uses, EUI

  • SystemSummary — unmet hours, HVAC sizing

  • EnvelopeSummary — U-values, areas, orientations

  • EquipmentSummary — HVAC component sizing

  • ZoneComponentLoadSummary — peak heating/cooling loads by zone

  • LightingSummary — lighting power density

Preconditions: simulation completed with SQL output available (sql_available: true in idfkit://simulation/results). Side effects: none — read-only.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
row_nameNoFilter to a specific row label.
table_nameNoTable name within the report (e.g. 'End Uses', 'Time Setpoint Not Met'). Omit to return all tables in the report.
column_nameNoFilter to a specific column label.
report_nameYesReport name (e.g. 'AnnualBuildingUtilityPerformanceSummary', 'SystemSummary'). Use list_simulation_reports to discover available names.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
rowsYes
row_countYes
table_nameYes
report_nameYes
Behavior4/5

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

Description aligns with annotations (readOnlyHint=true, destructiveHint=false) by stating 'Side effects: none — read-only.' Adds behavioral detail about omitting table_name retrieving all tables. Could mention response format but output schema exists.

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?

Well-structured with purpose first, then usage, parameter guidance, and preconditions. Reasonably concise for the detail provided; could tighten slightly but no fluff.

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?

Complete for a read-only query tool: covers purpose, parameter usage, preconditions, side effects, and example report names. Output schema handles return values.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema covers all parameters with descriptions (100% coverage). Description adds significant value: examples of common report names, guidance on omitting table_name, and referencing list_simulation_reports for discovery.

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?

Description clearly states verb 'Query', resource 'tabular report data from the last simulation's SQL output', and distinguishes purpose from sibling tools by mentioning 'deeper analysis beyond structured diagnostics' and referencing list_simulation_reports.

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?

Provides explicit preconditions (simulation completed with SQL output), context for when to use (deeper analysis), and refers to related tool list_simulation_reports for discovery. No explicit when-not-to-use or alternatives, but contextual guidance is strong.

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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