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Fino-wind

Vaultbeat MCP Server

Metric trend

get_metric_trend
Read-onlyIdempotent

Calculate the daily trend of a metric series using least-squares fit, returning slope per day, endpoints, and spread to assess direction and variability over a chosen data window.

Instructions

Least-squares trend for one daily series: slope per day, endpoints, spread.

series is a name from list_metric_series. days selects the newest N days THAT HAVE DATA, not the last N calendar days — compare n_days with span_days to see whether the history is dense or sparse.

Returns arithmetic only. slope_per_day is in the series' own unit per day and carries no threshold, band or verdict; fewer than 3 days returns a null slope with a reason rather than a number fitted to noise.

Carries a coverage block over the days the arithmetic used: quote coverage.days_covered and coverage.span_days beside any number here, and read coverage.window_satisfied: false as a shorter history than you asked for rather than as a missing kind.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
daysNo
freshNo
ownerNo
seriesYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.8.1

TDQS

A4.1/5.0
Behavior5/5

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

Annotations already mark it read-only, idempotent, and non-destructive. The description adds substantial behavioral detail: days select data-bearing days not calendar days, results are arithmetic-only, fewer than 3 days yields a null slope with a reason, and coverage fields indicate sparse history. This goes well beyond the annotations.

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?

The description is longer than average but almost every sentence adds operational value, with important caveats front-loaded after the core definition. Minor redundancy around 'arithmetic only' and 'no threshold, band or verdict' prevents a perfect score.

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?

With an output schema present and annotations covering safety, the description handles return semantics, edge cases, and coverage interpretation well. It is missing guidance for fresh and owner, which leaves some ambiguity for an agent calling the tool with non-default values.

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 description coverage is 0%, so the description must carry parameter meaning. It thoroughly explains series and days, but leaves fresh and owner entirely unexplained. Since two of four parameters receive strong semantic guidance and the other two receive none, it is partially compensating.

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 operation and resource: 'Least-squares trend for one daily series: slope per day, endpoints, spread.' It also clarifies scope ('one daily series') and what it does not provide ('no threshold, band or verdict'), which distinguishes it from comparison and correlation siblings.

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

Usage Guidelines3/5

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

The description gives clear context about series selection and day-window semantics, and the 'one daily series' wording implies when this tool is appropriate. However, it never explicitly names alternatives such as compare_metric_periods or correlate_metric_series, nor does it state when not to use this tool.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.