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pyth_ping

Checks Pyth Hermes API reachability by sending a small live feed catalog request, helping verify connectivity before fetching price feeds.

Instructions

Check Pyth Hermes API reachability with a small live feed catalog request.

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.3

TDQS

A3.6/5.0
Behavior3/5

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

No annotations are present, so the description carries the full burden. It does disclose the meaningful behavior — a live network call to Hermes that hits the feed catalog — which tells an agent about external dependency and likely latency. It does not say whether failure surfaces as an error/exception or a boolean/status payload, which is the single most important behavioral fact for a ping tool.

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?

One front-loaded sentence with no filler; the reachability purpose comes first and the implementation note second.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 0-param health check with no output schema and no annotations, the description is adequate on purpose but leaves the return contract undefined — an agent cannot tell whether a failed ping yields an exception, a false, or a status object. That gap matters more here than for a typical tool because the whole value of a ping is its success/failure signal.

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?

Zero parameters, so there is nothing for the description to disambiguate and the baseline of 4 applies. The description's reference to a 'small' catalog request is the only semantic caveat worth noting.

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?

Specific verb (Check) plus specific resource (Pyth Hermes API reachability), with the implementation detail ('small live feed catalog request') clarifying what the check actually does. It is distinguishable from pyth_list_feeds only by inference — an agent must reason that pyth_ping is a health probe rather than a data-fetch tool — so it stops short of full sibling differentiation.

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 is implied: an agent should call this to verify connectivity before relying on other Pyth tools. However, it never states when to prefer it, when it is unnecessary, or that the other pyth_* tools are the data-bearing alternatives on failure.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.