Skip to main content
Glama

pyth_get_prices

Fetch Pyth Network price feeds for up to 100 symbols or feed IDs, with per-feed caching and controls for stale data or forced refresh.

Instructions

Get latest Pyth prices for up to 100 symbols or feed ids, using independent per-feed cache entries.

Input Schema

NameRequiredDescriptionDefault
feedsYes
cache_ttlNo
allow_staleNo
force_refreshNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.3

TDQS

C2.9/5.0
Behavior2/5

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

No annotations exist, so the description carries the full burden, yet it only offers a vague caching note ('independent per-feed cache entries') without explaining staleness behavior, refresh semantics, failure modes for unknown feeds, or rate limits. For a market-data read tool with zero structured safety/behavior metadata, this leaves key operational traits undisclosed.

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?

A single front-loaded sentence with no filler or repetition. It is efficient, though its brevity is partly under-specification rather than disciplined trimming.

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

Completeness2/5

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

With no annotations, no output schema, and 0% parameter description coverage, the description should explain cache/refresh behavior and the return shape (e.g., per-feed price and publish time). It covers only the resource and item limit, leaving significant gaps for a 4-parameter tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% across 4 parameters, so the description must compensate. It clarifies that `feeds` accepts symbols or feed ids, but says nothing about `cache_ttl`, `allow_stale`, or `force_refresh` — the three parameters whose semantics an agent most needs explained.

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?

States a specific verb and resource ('Get latest Pyth prices') plus scope ('up to 100 symbols or feed ids'), which implicitly separates it from the singular pyth_get_price. It does not explicitly name the sibling, so differentiation relies on the plural noun alone.

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 only implied: the 'up to 100' batch framing suggests this is the multi-feed fetch versus pyth_get_price, and the cache mention hints at repeated polling. No explicit when-to-use, when-not-to-use, or named alternatives (pyth_get_price, pyth_stream_prices, pyth_resolve_feed) are given.

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