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Meteor-Simulation

BULC MCP

Official

Fire timeseries

fire_timeseries
Read-onlyIdempotent

Extract time series from FDS result CSV files by picking hrr, devc, or ctrl, columns, and a time window; reduce long series with time-averaging.

Instructions

Time series from the result CSV files: file = hrr (HRR, Q_RADI, MLR …) | devc (device ids) | ctrl. columns = column names (default the first 6). t0 / t1 limit the time window; maxPoints ≤ 500 (default 300 — longer series are reduced by time-averaging). Read-only. [bulc-mcp rules] FIRE-001, GEN-010 — bulc_knowledge_search ""

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
t0No
t1No
fileYes
columnsNo
fdsPathNoAbsolute .fds path (default: the project deck / last run)
maxPointsNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv4.0.0

TDQS

A3.6/5.0
Behavior4/5

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

Annotations already declare readOnlyHint/openWorldHint/idempotent/destructive, so the description's re-statement of 'Read-only' earns nothing. It does add genuine behavior beyond that: maxPoints caps at 500, defaults to 300, and longer series are silently reduced by time-averaging — an important disclosure that output may be downsampled. The listed bulc rules also hint at governance to consult.

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?

Dense, front-loaded, and compressed with pipe/enum notation, so nearly every clause carries information. The trailing '[bulc-mcp rules]' line is cryptic but short, and no sentence is wasted.

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 6-param read tool with no output schema, the description covers source selection, column selection, time window, and downsampling behavior well enough to call it correctly. It stops short of describing the return shape or how it relates to the summary/detect siblings.

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?

Schema description coverage is only 17%, so the description must compensate, and it largely does: it decodes the file enum (hrr→HRR/Q_RADI/MLR, devc→device ids, ctrl), explains columns (default first 6), the t0/t1 window, and maxPoints cap/default. Only fdsPath is unexplained here, though it carries a schema description of its own.

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 the resource ('time series from the result CSV files') and enumerates the three sources (hrr/devc/ctrl) with what each contains, so an agent understands the deliverable precisely. It does not, however, contrast itself with siblings like fire_results_summary or result_get_state, so the differentiation rests on the reader.

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 when-to-use or when-not-to-use statement, and no alternative tool is named, even though fire_results_summary and results_detect are natural candidates. The parameter meanings implicitly signal 'extract data after a run,' but tool-selection guidance is absent.

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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