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parkyucheol-del

AlphaPipeline

by parkyucheol-del
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Python
Remote

prediction.hip4_price_ladder

Retrieve a strike-sorted ladder of Hyperliquid HIP-4 price-binary markets with live Yes probabilities to gauge the market's implied price distribution for an underlying.

Instructions

One underlying's Hyperliquid HIP-4 "above $X" price-binary markets laid
out as a strike-sorted ladder, each rung with its live Yes probability -
e.g. to read the market's implied BTC price distribution at a glance.
Reuses the same cached data as prediction.hip4_snapshot - no new upstream
call. No volume field: Hyperliquid's public API does not expose
per-outcome trading volume for HIP-4 markets.

Do NOT use for mutually-exclusive multi-outcome groups (use
prediction.hip4_snapshot's grouped_questions instead) or for Polymarket
data. Always check the response's `notice` field - same
reverse-engineered-mapping caveat as prediction.hip4_snapshot.

Args:
    underlying: Asset symbol for crypto price-binary markets (e.g. "BTC",
        "ETH", "SOL", "HYPE").
    limit: Max rungs returned. Defaults to 100, max 500.

Returns:
    On success: {"success": true, "underlying", "rung_count",
        "skipped_unparsable_count", "rungs", ...}
    On failure: {"success": false, "error": {"type", "message"}}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
underlyingYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.5.0

TDQS

A4.7/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does well: it discloses that data is cached and reuses the hip4_snapshot upstream call, that no volume field exists because the API doesn't expose it, and that a reverse-engineered-mapping caveat lives in `notice`. It omits auth/permission needs and any rate-limit or freshness guarantees, but the read-only nature is implicit and the disclosed caveats are substantive.

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?

Front-loaded with the core purpose, then clearly sectioned into caveats, exclusions, Args and Returns. Every sentence is informative, though the volume-field note and the repeated reference to hip4_snapshot add mild redundancy.

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?

No output schema exists, yet the description supplies the success and failure response shapes (rung_count, skipped_unparsable_count, error object) plus the caveat field. Combined with the param docs and exclusions, an agent has everything needed to call and interpret this tool.

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 and does: `underlying` is explained as an asset symbol with concrete examples (BTC, ETH, SOL, HYPE), and `limit` is described as max rungs with a default of 100 and a hard cap of 500 — the 500 cap is not in the schema at all.

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+resource: Hyperliquid HIP-4 'above $X' price-binary markets for one underlying, laid out as a strike-sorted ladder with live Yes probabilities. It explicitly distinguishes itself from prediction.hip4_snapshot and Polymarket data, so an agent can route correctly 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?

Gives an explicit negative case ('Do NOT use for mutually-exclusive multi-outcome groups') and names the alternative (prediction.hip4_snapshot's grouped_questions). It also rules out Polymarket use and points the agent at the `notice` field, leaving nothing to inference.

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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