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Hyperliquid Trader Profile

hyperliquid_trader_profile

Live Hyperliquid perp positions for an EVM (0x) address, read from HL's public on-chain state. Per-position side, leverage, notional, entry, unrealized PnL, distance-to-liquidation, and risk flags. Account value, directional bias, profile (directional/market-neutral/diversified), and realized+unrealized PnL over week/month/all-time. The building block for HL smart-money tracking.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
addressYesHyperliquid EVM (0x) address

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changed
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
  2. First observed

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations, the description carries the full burden. It discloses that data is live, read from public on-chain state, and provides a comprehensive list of output fields including account-level metrics and historical PnL. It does not mention rate limits or edge cases, but for a read-only public data tool, the behavioral traits are sufficiently conveyed.

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?

The description is three sentences with no wasted words. It front-loads the core purpose, then lists specific output fields, and ends with the strategic role. Each sentence earns its place, making it highly concise and well-structured.

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?

Despite having no output schema, the description thoroughly enumerates what the tool returns (per-position fields, account value, bias, profile, PnL timeframes), which is sufficient for an agent to understand the data. The single-parameter input is simple, and the description gives enough context for usage. It is complete for the tool's complexity.

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

Parameters3/5

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

The schema already provides 100% coverage of the single parameter, with the description 'Hyperliquid EVM (0x) address' being clear. The tool-level description adds context about the address being for perp positions, but does not add parameter-specific details beyond the schema. Baseline of 3 is appropriate.

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 retrieves live Hyperliquid perp positions for an EVM address, and enumerates the specific data points (side, leverage, notional, entry, PnL, etc.). It distinguishes itself from siblings by explicitly mentioning Hyperliquid, EVM (0x) addresses, and positioning as the building block for smart-money tracking, which separates it from tools like hyperliquid_smart_money or perps_trader_profile.

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?

The description provides clear context that this is a lower-level, per-address data tool ('building block for HL smart-money tracking'), implying it should be used when granular per-position data is needed. However, it does not explicitly name alternative tools for when to use them instead, so it lacks explicit exclusions or direct comparisons.

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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TDQS

B3.4/5.0
Disambiguation2/5

Several tools cluster around the same action: trending/discovery tools like feed_latest, trending_signals, runner_scan, trenches_scan, smart_money_trenches, attention_momentum, and consensus_signal heavily overlap, and perps_basis_signal, perps_cross_venue_funding, and perps_venue_comparison all cover similar venue/funding comparisons. An agent can distinguish them only by reading fine print, increasing misselection risk.

Naming Consistency4/5

Most tools follow readable snake_case with strong domain prefixes (perps_*, stonk_*, smart_money_*, hyperliquid_*) and clear verb_noun actions for core operations like enrich_token and compare_wallets. Minor outliers like query, feed_latest, attention_momentum, and new_tokens break the pattern but remain predictable.

Tool Count2/5

41 tools is well over the 25-tool threshold for a coherent agent surface. The set fragments into many micro-specialties—five stonk tools, six perps tools, and several overlapping memecoin scanners—that could be consolidated into broader composite tools without losing capability.

Completeness4/5

For a Solana token/wallet/perps intelligence platform, the surface is exceptionally broad: discovery, enrichment, due diligence, exit signals, wallet history, transaction parsing, protocol profiles, perps, stonk, and composite querying are all covered. Missing pieces are minor, such as general holder lists or raw transaction history, and can be worked around with existing tools.