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corpusAI Cloud Pricing

Daily spot history

spot_daily
Read-onlyIdempotent

Paid (0.05 USDC per call). Full daily history for one instance type, all eras stitched. One row per UTC day from the earliest data for the type to now. Rows dated before the type's first raw event come from the legacy history (source = pauley: measured 2022-05 to 2024-01 AWS, open/high/low/close present on days the price moved; titans: daily average only, 2024 to 2026). Rows from direct_from on are time-weighted, zone-collapsed bars from the raw event store (source = direct, same method as /spot/hourly; avg equals the public dashboard value). open/high/low/close are null where the source only has an average.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toNoEnd of the window (exclusive), ISO 8601 UTC. Default: now.
fromNoStart of the window (inclusive), ISO 8601 UTC. Default: the earliest row for the type.
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
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`.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.9/5.0
Behavior5/5

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

The description goes far beyond the annotations by disclosing the per-call cost, legacy vs direct data sources, source field values, time-weighted and zone-collapsed methodology, the relationship of avg to the public dashboard, and null OHLC behavior. This is rich, non-obvious behavioral context with no contradiction against 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 dense but well-organized: it front-loads payment, purpose, and row granularity, then details the legacy/direct sources and null behavior. No filler is present, though the single-paragraph structure makes the provenance details slightly heavy.

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 no output schema, the description adequately explains what rows will look like: one per UTC day, source distinctions, OHLC/avg fields, and null semantics. It could name the explicit output columns, but for a complex multi-era tool the coverage is strong.

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 100%, with all five parameters already explained and examples provided. The description adds little parameter-specific meaning beyond reinforcing that from/to span the full daily history; the baseline of 3 is appropriate since the schema does the heavy lifting.

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 as 'full daily history for one instance type, all eras stitched' with one row per UTC day. It conveys daily granularity and distinguishes itself from hourly/monthly/snapshot siblings by scope, though it never names an alternative directly.

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?

Usage context is implied: daily history, one instance type, paid, and same method as /spot/hourly. However, the description does not explicitly state when to choose this tool over spot_hourly, spot_monthly, spot_latest, or spot_snapshot, nor does it provide exclusion criteria.

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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