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A7OM-AI

atom-mcp-server

by A7OM-AI

Get Market KPIs

get_kpis
Read-onlyIdempotent

Retrieve 6 AI inference market KPIs including output premiums, caching savings, and open-source advantages. Analyze vendor pricing trends and cost benchmarks using live ATOM Inference Price Index data.

Instructions

ATOM Inference Price Index (AIPI) market-level KPIs.

Returns 6 key performance indicators derived from live pricing data:

  • Output Premium: how much more output tokens cost vs input

  • Caching Savings: average discount for cached input pricing

  • Open Source Advantage: price difference between open-source and proprietary

  • Context Cost Curve: price multiplier for larger context windows

  • Caching Availability: % of models offering cached pricing

  • Size Spread: price ratio between largest and smallest models

These KPIs are available to all tiers — they demonstrate ATOM's market intelligence.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
_atom_api_keyNoYour ATOM API key for full access. Omit for free tier (redacted data).
Behavior4/5

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

Annotations already establish read-only, idempotent, safe behavior. The description adds valuable context beyond annotations: it specifies 'live pricing data' (freshness), explains the semantic meaning of each KPI (e.g., 'Output Premium: how much more output tokens cost vs input'), and clarifies the tiered access model.

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?

Well-structured with zero waste: opening sentence establishes the resource, the bullet list efficiently details the 6 return values with brief explanations, and the final sentence covers access constraints. Every sentence earns its place.

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?

Given no output schema exists, the description compensates effectively by enumerating and explaining all 6 returned KPIs. For a single-parameter tool with full schema coverage, detailing the return values comprehensively provides complete contextual coverage.

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?

With 100% schema coverage, the baseline is 3. The description adds meaningful context by stating KPIs are 'available to all tiers,' reinforcing the schema's guidance that the API key can be omitted for free tier access. This connects the parameter to the broader access model.

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 states it returns '6 key performance indicators derived from live pricing data' and names the specific resource (ATOM Inference Price Index). However, it lacks explicit differentiation from similar siblings like 'get_market_stats' or 'get_index_benchmarks'.

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 notes that 'KPIs are available to all tiers,' hinting at the optional API key usage, but provides no explicit guidance on when to choose this over siblings like 'get_market_stats'. The list of 6 KPIs provides implicit context but no direct when-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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