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Akari Crypto Intel

akari_hl_market

Hyperliquid perpetuals market snapshot — every active coin (~180) with mark and oracle price, premium in bps, funding rate (8h + annualised APR) and which side collects it, open interest in USD, 24h notional volume, 24h change, and max leverage. Filter with ?coins=BTC,ETH, sort with ?sort=volume|funding|oi|change|name, cap with ?limit=1-300. Includes the top-5 funding extremes and chain-wide OI/volume totals. Live from Hyperliquid /info, cached 30s. Use for funding-harvest sc

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior4/5

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

With no annotations, the description carries the burden well: it discloses the upstream source (Hyperliquid /info), a 30s cache, an approximate dataset size (~180 coins), and that aggregate top-5 funding extremes plus chain-wide totals are appended. It omits failure/auth behavior, keeping it short of a 5.

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?

Densely packed but front-loaded: purpose first, then query modifiers, then provenance and caveats. The text is cut off mid-word, which leaves the final usage sentence incomplete and slightly undermines an otherwise efficient structure.

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

Completeness4/5

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

Return shape is described field-by-field, so the absence of an output schema is covered, and source/cache/aggregates give the agent enough to interpret results. The gap is the unresolved conflict between the advertised query parameters and an empty input schema.

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?

The schema declares zero properties with additionalProperties=false, yet the description instructs the agent to filter via ?coins=, ?sort=, and ?limit=1-300. This invites calls the schema explicitly forbids, which is a real risk of malformed invocation; the baseline of 4 for zero params is undercut by the mismatch.

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 opens with a precise verb+resource ('Hyperliquid perpetuals market snapshot') and enumerates the exact fields returned per coin. It is unmistakably distinct from siblings like akari_ta or akari_market_report because it names the specific venue and data surface.

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?

It advertises concrete filtering/sorting/capping options (?coins, ?sort, ?limit) and begins a use case ('Use for funding-harvest sc...'), but the sentence is truncated and no sibling alternative or exclusion is named. Usage is implied rather than fully specified.

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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