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chaandannn

nable (finops-mcp)

get_view

Execute pre-built cost views by name to share standard reports across your team. Filter by tag, provider, or time window to quickly analyze cloud costs.

Instructions

Run a pre-built cost view by name. These are standard reports your whole team can share.

Args: view: View ID from list_views(). Required. tag_key: Tag key to group by (required for 'by_tag' view, e.g. 'team', 'env'). tag_value: Optional filter to a single tag value within by_tag. provider: Optional provider filter (aws, azure, gcp, datadog, etc.). days: Override the default lookback window for time-series views.

Examples: - "Show me the month over month view" - "Run the by_tag view for the team tag" - "Get the anomalies view for AWS" - "What does the top_spenders view show?" - "Run daily_trend for the last 7 days"

Tip: Share these view names in your team's Slack or Claude Project so everyone runs the same report instead of writing queries from scratch each time.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
daysNo
viewYes
tag_keyNo
providerNo
tag_valueNo
Behavior3/5

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

Without annotations, the description explains that the tool runs a view and accepts filtering parameters, but does not disclose error behavior, side effects, or performance implications. It implies a read-only query but is not explicit.

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?

The description is concise and well-structured: a one-sentence overview, a bullet list of parameters, usage examples, and a practical tip. Every part adds value without redundancy.

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?

Given the parameter count and lack of output schema, the description covers the tool's function and parameters adequately. It could mention the output format or highlight that views are from list_views, but examples compensate.

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 'Args' section explains each parameter's purpose beyond the schema's type definitions (e.g., view ID from list_views(), tag_key required for 'by_tag' view). This compensates for the 0% schema description coverage.

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 clearly states it runs a pre-built cost view by name, which distinguishes it from sibling tools that generate ad-hoc or custom reports. The verb 'run' and resource 'pre-built cost view' are specific.

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 description provides clear context for when to use this tool (running a pre-built view) and includes examples. However, it lacks explicit exclusion of alternatives or conditions under which to use a different tool.

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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