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BULC MCP

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Get object properties

get_object_properties
Read-onlyIdempotent

Retrieve an obstacle's complete properties as JSON, including runtime FDS overrides like fire HRRPUA, detector activation temperature, sprinkler k-factor, HVAC airflow and fuel yields.

Instructions

Get one obstacle's full properties as JSON, including ALL Runtime FDS Properties (fds_override: fire HRRPUA/ramp, detector activation_temp/RTI, sprinkler k_factor/flow, HVAC airflow, fuel/REAC yields, etc.). [bulc-mcp rules] GEN-001, GEN-003, GEO-011 — bulc_knowledge_search ""

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesObstacle ID

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv4.0.0

TDQS

B3.1/5.0
Behavior3/5

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

Annotations already fully declare the safety profile (readOnly, idempotent, non-destructive, closed-world), so the description's added value is its disclosure of return format (JSON) and content scope. It usefully signals that runtime FDS overrides are included, but gives no error behavior or structure detail.

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

Conciseness3/5

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

The first sentence is efficient and front-loaded, but the second bracketed rule-reference line is cryptic ('GEN-001, GEN-003, GEO-011' with no explanation) and does not earn its place as prose for the calling agent.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a read-only single-object getter with full annotation coverage and no output schema, the description is adequate: it says what is returned and in what format. It is missing guidance on error cases (invalid id) and remains cluttered by the unexplained rules pointer.

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% with the single 'id' parameter documented as 'Obstacle ID'. The description adds nothing beyond the schema, so the baseline of 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource (get one obstacle's full properties) plus the return format (JSON) and scope (all Runtime FDS Properties). It implicitly distinguishes itself from list_obstacles, but does not explicitly name an alternative to route against.

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

Usage Guidelines2/5

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

There is no explicit statement of when to use this versus update_obstacle, list_obstacles, or shape_get_item_fds_props. The trailing '[bulc-mcp rules]' line points at bulc_knowledge_search, which is a reference to rules, not usage guidance for this tool.

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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