Skip to main content
Glama
parkyucheol-del

AlphaPipeline

by parkyucheol-del
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

prediction.hip4_snapshot

Fetch real-time probability snapshots for Hyperliquid's HIP-4 prediction markets—crypto binaries, sports winners, Fed decisions—auto-including new market types in one call. Not for Polymarket.

Instructions

Real-time probability snapshot of Hyperliquid's HIP-4 outcome (prediction)
markets - crypto price binaries, sports game winners, tournament winners,
Fed rate decisions, and any other market type Hyperliquid adds, all in one
call. No curated market list: every field under "fields" on each row is
parsed verbatim from Hyperliquid's own "key:value|key2:value2" description
string, so new HIP-4 market types appear automatically without any code
change here. standalone_markets covers two-sided markets (most crypto/
sports games); grouped_questions covers mutually-exclusive multi-outcome
groups (e.g. a league winner) with a fallback price for "none of the
above".

Do NOT use for Polymarket data (use prediction.neg_risk_arbitrage /
prediction.exit_capacity_audit instead). No wallet or API key needed
upstream - always check the response's `notice` field, since the mapping
used to join Hyperliquid's market metadata to its live prices is not
documented by Hyperliquid and was reverse-engineered from live data.

Args:
    template: Optional substring filter on the market's template name
        (e.g. "sportsContestWinner", "priceBinary").
    underlying: Optional asset symbol filter for crypto markets (e.g.
        "BTC", "ETH", "SOL", "HYPE").
    limit: Max rows per list (standalone_markets / grouped_questions
        each). Defaults to 100, max 500.

Returns:
    On success: {"success": true, "standalone_markets", "grouped_questions",
        "standalone_count", "grouped_question_count", ...}
    On failure: {"success": false, "error": {"type", "message"}}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
templateNo
underlyingNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.4.0

TDQS

A4.9/5.0
Behavior5/5

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

With no annotations, the description carries the full burden and does so: it discloses that fields are parsed verbatim from Hyperliquid's own description string, that new market types appear without code changes, the standalone_markets vs grouped_questions semantics including the 'none of the above' fallback, and the critical caveat that the metadata-to-price join is undocumented and reverse-engineered. That reverse-engineering warning is a genuine reliability signal an agent needs.

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?

Dense and front-loaded: purpose first, then the exclusions and caveats, then args, then returns. It is longer than strictly necessary and the market-type enumeration in the opening sentence could be trimmed, but almost every clause carries operational value.

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?

For a three-param, no-output-schema tool, the definition covers purpose, exclusions, parameter meanings, return shape (success/error and the standalone_markets/grouped_questions/count keys), and the reliability caveat. Nothing an agent needs to call it correctly is missing.

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

Parameters5/5

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

Schema description coverage is 0%, so the description must compensate entirely, and it does: template is defined as a substring filter on the template name with example values, underlying as an asset symbol filter with examples (BTC/ETH/SOL/HYPE), and limit as rows per list with default 100 and max 500. All three parameters gain meaning unavailable in the bare schema.

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?

States a specific verb and resource ('real-time probability snapshot of Hyperliquid's HIP-4 outcome markets') and enumerates the market types covered. It explicitly distinguishes itself from the Polymarket siblings, so an agent can route without opening a schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicit exclusions are given ('Do NOT use for Polymarket data (use prediction.neg_risk_arbitrage / prediction.exit_capacity_audit instead)'), plus the note that no wallet or API key is needed and that the response `notice` field must always be checked. This is exactly the when/when-not/alternatives guidance the dimension asks for.

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

Deploy Server

Other Tools