General agents
AuraScore 79/100

BIM Clash Detection and Autonomous RFI Routing Matrix

Coordinate autonomous agents to detect 3D BIM model clashes, evaluate severity, and automatically route RFIs to trade contractors.

Apply this template when operationalizing AI agents to streamline Virtual Design and Construction (VDC) workflows. It provides a structured matrix for clash categorization, autonomous RFI authoring, and trade contractor response tracking.

Template

Role: Senior Virtual Design and Construction (VDC) Automation Lead specializing in multi-agent building information model coordination.

Context

  • BIM model scope and scale: {{bim_model_scale}}
  • Involved trade disciplines: {{trade_disciplines}}
  • Clash severity tolerances: {{clash_severity_thresholds}}
  • Common Data Environment: {{cde_platform_env}}
  • RFI approval hierarchy: {{rfi_approval_chain}}
  • Historical clash database: {{historical_resolution_data}}

Task

Construct an autonomous BIM clash detection and RFI resolution matrix that coordinates model-checking agents, spatial reasoning subroutines, and automated RFI distribution across {{trade_disciplines}} within {{cde_platform_env}}.

Method

  1. Establish geometric collision parameters using tolerances defined in {{clash_severity_thresholds}} for {{bim_model_scale}}.
  2. Assign agent responsibilities across trade intersections (e.g., MEP vs. Structural, Fire Protection vs. Architectural).
  3. Map automated conflict analysis against {{historical_resolution_data}} to identify standard engineering solutions.
  4. Define criteria for autonomous clash clearance without human intervention for minor geometric overlaps.
  5. Standardize automated RFI generation schemas, including 3D viewport generation, parameter extraction, and cost impact estimation.
  6. Establish routing workflows matching {{rfi_approval_chain}} for high-severity spatial conflicts.
  7. Build agent tracking rules for contractor response times, model revision ingestion, and automated clash close-out.

Constraints

  • High-severity structural clashes MUST NOT be resolved without sign-off from {{rfi_approval_chain}}.
  • Agents MUST reference historical precedents from {{historical_resolution_data}} before drafting new RFIs.
  • All generated RFIs and model snapshots must reside exclusively in {{cde_platform_env}}.
  • Keep trade categorizations strictly aligned with {{trade_disciplines}}.

Output format

  • VDC Multi-Agent Workflow Overview (max 120 words)
  • Clash Triage & RFI Routing Matrix (Markdown table with columns: Trade Conflict, Severity Level, Agent Task, Resolution Logic, Generated Artifact, Escalation Role, SLA)
  • Autonomous RFI Schema & Metadata Template
  • Agent Failure and Human Override Protocols

Self-review

  • Ensure every trade listed in {{trade_disciplines}} is represented in the clash matrix.
  • Verify clash thresholds strictly match {{clash_severity_thresholds}}.
  • Check that RFI routing paths conform to {{rfi_approval_chain}}.
AuraScore breakdown
79/100Provisional
Instruction clarity15/15 · Strong

Explicit role, a named task, and discrete steps the model can follow.

Context architecture12/12 · Strong

Background, inputs and variables the model needs before it starts.

Constraint engineering10/12 · Adequate

Hard boundaries — what the model must and must not do.

Output specification6/14 · Thin

A named, field-level shape for the response.

Reasoning structure10/10 · Strong

Ordered work items that force analysis before an answer.

Model compatibility10/10 · Strong

Length and structure that travel across frontier models.

Token efficiency5/10 · Thin

Signal density — instruction weight without padding.

Reusability7/7 · Strong

Documented variables so the scaffold adapts to new inputs.

Robustness3/5 · Adequate

Quality bar, assumptions and behaviour when inputs are thin.

Observed performance1/5 · Thin

How much real usage the template has behind it.

ai-agents
agents-general
real-estate-construction
vdc
bim
clash-detection