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corpusAI Cloud Pricing

Spot price events

spot_events
Read-onlyIdempotent

Paid (0.01 USDC per call). Raw spot price-change events for one instance type. Every price change for the type in the window, with exact timestamp, availability zone and product (OS). Sorted by time. Repeated identical prices are dropped by default (include_repeats=true keeps them). Up to limit rows; when truncated is true, continue with from = next_from.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
azNoRestrict to one availability zone / zone id (for example `use1-az1`). Default: all zones.
toNoEnd of the window (exclusive), ISO 8601 UTC. Default: now.
fromNoStart of the window (inclusive), ISO 8601 UTC. Default: 7 days before `to`.
limitNoMaximum rows to return (1 to 10000). Default 5000.
regionYesRegion slug as listed by /catalog (for example `us-east-1` for AWS, `us-central1` for GCP, `us-east` for Azure). Azure slugs map to `eastus`, `westus2`, `westeurope`. Example: us-east-1
productNoRestrict to one product / OS string (for example `Linux/UNIX`, `Spot`, `Linux`). Default: all.
instanceYesInstance / machine / SKU type name exactly as listed by /instances (for example `c5.large`, `n2-standard-4`, `D2s_v5`). Example: c5.large
providerYesCloud provider. One of `aws`, `gcp`, `azure`.
include_repeatsNoKeep events whose price equals the previous event of the same (az, product) series. Default false.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior5/5

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

Annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior, and the description adds substantial context: cost per call, event granularity, exact returned fields, chronological sorting, deduplication of repeated prices, and pagination via truncated/next_from. It goes well beyond what the annotations or schema alone provide.

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?

Four dense sentences, each contributing needed information: cost, core resource, output contents and ordering, dedup behavior, and pagination. There is no filler, and the most important facts are front-loaded.

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?

For a tool with 9 parameters and no output schema, the description gives the agent enough to call it correctly: what rows contain, how they are ordered, how repeated prices are handled, and how to continue pagination. The absence of an output schema is adequately compensated by the description of the result contract.

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 useful semantic detail beyond the schema, especially the meaning of include_repeats deduplication and the pagination contract involving limit, truncated, from, and next_from. It does not exhaustively restate every parameter, but it does not need to.

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?

The description clearly identifies the resource: raw spot price-change events for one instance type, with exact timestamp, availability zone and product. The phrase "for one instance type" and "raw" help separate it from aggregate or all-instance siblings, though it never states an explicit verb like 'list' or 'get' and does not name a specific sibling tool.

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 conveys that this tool is for raw per-event spot price history and warns about the per-call cost, which implies the intended use case. However, it does not explicitly state when to prefer alternatives like spot_latest, spot_snapshot, or spot_daily, nor does it give when-not-to-use guidance.

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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