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pythia-the-oracle

pythia-oracle-mcp

Official

check_oracle_health

Verify the reliability of Pythia's oracle system before integration. Returns per-token 30-day uptime, daily history, and data source health.

Instructions

Check the reliability and uptime of Pythia's oracle system.

Returns per-token 30-day uptime (sorted worst-first so problems surface immediately), recent daily status history, data source health, and infrastructure status. Use this to verify Pythia's reliability before integrating or relying on its data.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations, the description bears full responsibility. It discloses key behavioral traits: returns per-token 30-day uptime sorted worst-first, daily history, data source health, and infrastructure status. No contradictions present.

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?

Two sentences with zero waste: first sentence states core purpose, second lists what is returned. Front-loaded and efficient, 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 zero parameters, presence of output schema, and the tool's simple nature, the description provides all necessary context: what it checks, what data it returns, and when to use it. Complete and sufficient.

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 input schema has no parameters, so description does not need to explain them. It adds value by detailing the output components, effectively compensating for the lack of parameters. Baseline is 4 due to high schema coverage (100%).

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 the tool checks the reliability and uptime of Pythia's oracle system, using specific verbs and a distinct resource. It differentiates from sibling tools which focus on contracts, events, feeds, etc., leaving no ambiguity about its role as a health check.

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?

Explicitly advises using this tool to verify reliability before integrating or relying on data. While it does not give when-not-to-use or alternative tools, the context is clear and sufficient for the agent to decide.

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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