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cost_review_report

Generate a Markdown Databricks cost-review report for a chosen period, covering top cost drivers, waste findings with estimated savings, and proposed read-only fixes.

Instructions

One markdown cost-review report for the last days days (1..365) from cost_summary + top_cost_drivers + find_waste: executive summary, top drivers, waste findings with estimated list-price amounts, and proposed fixes. max_autotermination_minutes / warehouse_idle_pct / max_rows are forwarded to find_waste. Read-only; proposals only — nothing is applied. Returns {days, markdown, measured_saving_usd, projected_30d_usd}.

Input Schema

NameRequiredDescriptionDefault
daysNo
max_rowsNo
warehouse_idle_pctNo
max_autotermination_minutesNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations, the description carries the full load and does well: it discloses read-only semantics, that proposals are never applied, that three parameters are forwarded to find_waste, and the exact return keys. It omits the operational cost of fanning out to three underlying tools and any permission prerequisites.

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

Conciseness5/5

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

Front-loaded with the deliverable and window, then composition, then safety, then return shape. Dense but every clause carries information; no filler.

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?

No output schema, so it correctly inlines the return keys {days, markdown, measured_saving_usd, projected_30d_usd}. All four parameters are optional with defaults, lowering the cost of underspecification, but the forwarded parameters' meanings remain unexplained.

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 compensate. It documents `days` (range 1..365) and says the other three are forwarded to find_waste, but never explains what max_rows limits or what the idle-percentage/autotermination thresholds mean operationally.

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 artifact (a markdown cost-review report), the window, and explicitly the three sibling tools it composes (cost_summary, top_cost_drivers, find_waste). An agent can tell immediately that this is the aggregated one-shot report versus the individual primitives.

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?

The composition statement plus 'Read-only; proposals only — nothing is applied' gives a clear usage context: use this when you want the combined report and aren't applying changes. It stops short of explicit exclusions (e.g. when to call cost_summary alone or whether to call propose_fix afterwards).

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