Costory: Your Finops MCP

preview_alert

Read-only

Backtest a cost-alert condition BEFORE creating it: replays the condition against the last lookbackDays (default 45) of data and reports how many times it would have fired. Takes the same queries + condition + dedup as create_alert (no notification channel needed). The dedup window is per groupBy value; delivery stays one message listing newly eligible groups. Returns the evaluation window, firingDays (distinct days the condition held), firingRows (per-group fires), notificationsCount (days on which at least one newly eligible group would notify) and a sample of firing dates with per-group state. Use this to sanity-check a condition/threshold (and tune dedup) before calling create_alert. EXAMPLE: "Would 'alert if 7-day AWS spend tops $50k' have fired this month?" → { queries: [{ type: "cost", name: "a", metricId: "cost", currency: "USD", filterCel: "cos_provider in ["AWS"]" }], condition: "rollingSum(a, 7, DAY) > 50000", dedup: { kind: "CALENDAR", calendarUnit: "WEEK" }, lookbackDays: 30 }

Input Schema

TableJSON Schema

Name	Required	Description
`slug`	No	Organization slug. Omit to auto-detect from your account (fails if you belong to multiple orgs).
`dedup`	No	Deduplication config controlling how often a still-firing group notifies. The window is per groupBy value; delivery stays one message listing newly eligible groups. Either CALENDAR (kind: CALENDAR, calendarUnit: WEEK \| MONTH) = at most once per current ISO week / calendar month, or ROLLING (kind: ROLLING, windowDays: N) = at most once every N days. Optional here: when provided the result also reports how many notifications would actually be sent after dedup.
`queries`	No	Same series objects as the `query` tool `queries` array (referenced by `condition`).
`condition`	Yes	Alerts v3 firing rule: a single boolean expression over the query names (`name` field of each query). Supports arithmetic (+ - * /), comparisons (> >= < <= == !=), logical and/or/not, parentheses, and these window functions: rollingSum(a, N, UNIT) (trailing sum over the last N units, UNIT ∈ DAY\|WEEK\|MONTH, inclusive of today), weekToDateSum(a) (Monday-to-date), monthToDateSum(a) (1st-of-month-to-date), and timeShift(a, N, UNIT) (value shifted back N units; may wrap a window function). Examples: `a > 1000`, `rollingSum(a, 7, DAY) > 1000`, `(a - timeShift(a, 1, DAY)) / timeShift(a, 1, DAY) > 0.2`, `a > 10000 or rollingSum(a, 7, DAY) > 50000`.
`lookbackDays`	No	Trailing window length in days to replay the condition over (default 45).

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedSep 21, 2026

changedInput schema / properties / dedup / description

Previous value: -"Deduplication config controlling how often a still-firing alert notifies. Either CALENDAR (kind: CALENDAR, calendarUnit: WEEK | MONTH) = at most once per current ISO week / calendar month, or ROLLING (kind: ROLLING, windowDays: N) = at most once every N days. Optional here: when provided the result also reports how many notifications would actually be sent after dedup."New value: +"Deduplication config controlling how often a still-firing group notifies. The window is per groupBy value; delivery stays one message listing newly eligible groups. Either CALENDAR (kind: CALENDAR, calendarUnit: WEEK | MONTH) = at most once per current ISO week / calendar month, or ROLLING (kind: ROLLING, windowDays: N) = at most once every N days. Optional here: when provided the result also reports how many notifications would actually be sent after dedup."

First observedAug 19, 2026

TDQS

A4.8/5.0

Behavior5/5

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

Annotations already flag this as read-only, and the description adds behavior well beyond that: it replays a condition, reports firing days/rows, applies dedup semantics per groupBy value, and describes the notification count computation. It also discloses the default lookback window and returns a sample of firing dates with state, giving the agent a clear model of what execution will do.

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 front-loaded with the core purpose and is organized clearly: what it does, what it takes, what it returns, and when to use it. It is somewhat long and repeats dedup details that also appear in the schema, but the example and return-field listing earn their place for such a complex tool.

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

Completeness5/5

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

With no output schema, the description compensates by enumerating the return values (`firingDays`, `firingRows`, `notificationsCount`, sample dates with `state`), which is essential for the agent to interpret results. The schema handles parameter syntax fully, the annotations handle safety, and the description provides workflow context and a realistic invocation example. Nothing critical is missing.

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 coverage is 100%, so the baseline is 3. The description adds value by explaining how parameters combine with a concrete example ('alert if 7-day AWS spend tops $50k') and by tying queries/condition/dedup to create_alert semantics. It also clarifies that dedup affects the returned notification counts, which is not explicit in the schema.

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?

The description opens with a specific verb and resource ('Backtest a cost-alert condition') and explicitly distinguishes itself from create_alert by saying it runs BEFORE creation and needs no notification channel. This makes the tool's role unmistakable even among many sibling tools.

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

Usage Guidelines5/5

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

It explicitly says to use this to 'sanity-check a condition/threshold (and tune dedup) before calling create_alert,' naming the closely related sibling and the intended workflow. It also communicates that notification-channel setup is not needed here, reinforcing the boundary between previewing and creating.

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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