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BULC MCP

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Spr apply to fds

spr_apply_to_fds

Apply calculated sprinkler hydraulics to the FDS model by creating DEVC, PROP, and PART entries for each sprinkler node using its nozzle flow and pressure. Requires running spr_run_calc first.

Instructions

Apply the hydraulic pipe-network sprinklers to the FDS model: for every sprinkler node (with a head and calc results from spr_run_calc), creates/replaces DEVC (SPRINKLER LINK TEMPERATURE) + PROP + PART entries using the calculated nozzle flow and pressure. Run spr_run_calc first. [bulc-mcp rules] DEVC-001, SPR-001, SPR-002 — bulc_knowledge_search ""

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv4.0.0

TDQS

A4.3/5.0
Behavior4/5

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

Annotations cover the safety profile (readOnlyHint=false, destructiveHint=false, openWorldHint=false), and the description adds real value: it discloses the exact objects created/replaced (DEVC/PROP/PART), the data source (calc results), and the prerequisite step. Minor tension: 'creates/replaces' reads as replace-style idempotent behavior while idempotentHint=false, but this is a subtle inference rather than a clear contradiction.

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?

Front-loaded with the action and resource, followed by the concrete side effects and the prerequisite. The trailing '[bulc-mcp rules] ... bulc_knowledge_search' tag is slightly noisy but compact and actionable.

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?

For a zero-parameter, no-output-schema mutation tool this is nearly complete: it says what is modified, from what data, and the ordering prerequisite. It stops short of describing behavior when no sprinkler nodes/calc results exist, which slightly limits completeness.

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, so the schema baseline is 4. The description correctly implies the operation is driven entirely by existing sprinkler nodes and calc results rather than call arguments, so there is no parameter semantics to document.

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: 'Apply the hydraulic pipe-network sprinklers to the FDS model', then clarifies it creates/replaces DEVC (SPRINKLER LINK TEMPERATURE) + PROP + PART entries from calculated flow/pressure. This distinguishes it cleanly from siblings like add_sprinkler (manual sprinkler placement) and hvac_apply_to_fds.

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?

'Run spr_run_calc first' gives an explicit prerequisite and the data dependency is clear. It does not, however, name what to do instead if the network is not yet calculated or how it differs from manually adding devices, so there is clear context but no exclusions/alternatives.

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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