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hl_vault_leaderboard

Retrieve Hyperliquid vault leaderboard data including NAV, 30d return, max drawdown, and follower count. Real-time scrape of HL info API provides composite score for ranking.

Instructions

Hyperliquid vault leaderboard with NAV, 30d return, max drawdown, follower count, composite score. Real-time scrape of HL info API.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
sort_byNoscore

Implementation Reference

  • Tool definition/registration for hl_vault_leaderboard in the TOOLS list, with input schema (limit, sort_by).
    TOOLS = [
        {
            "name": "top_yield_farms",
            "description": "Latest 24h top DeFi yield farm picks with realistic "
                           "APY (emissions stripped), risk notes, TVL, protocol. "
                           "Sourced from FalsifyLab daily aggregator.",
            "inputSchema": {
                "type": "object",
                "properties": {
                    "limit": {"type": "integer", "default": 10,
                               "description": "max results (1-50)"},
                    "min_apy": {"type": "number", "default": 0,
                                 "description": "filter floor in pct"},
                    "asset": {"type": "string",
                               "description": "filter by asset symbol (BTC, ETH, SOL, etc.)"},
                },
            },
        },
        {
            "name": "hl_vault_leaderboard",
            "description": "Hyperliquid vault leaderboard with NAV, 30d return, "
                           "max drawdown, follower count, composite score. "
                           "Real-time scrape of HL info API.",
            "inputSchema": {
                "type": "object",
                "properties": {
                    "limit": {"type": "integer", "default": 10},
                    "sort_by": {"type": "string",
                                  "enum": ["score", "tvl", "return_30d", "followers"],
                                  "default": "score"},
                },
            },
        },
  • Handler dispatch for hl_vault_leaderboard — calls backend API endpoint /api/hl_vaults via _api_get helper.
    def call_tool(name: str, args: dict) -> dict:
        if name == "top_yield_farms":
            return _api_get("/api/yield/top", args)
        if name == "hl_vault_leaderboard":
            return _api_get("/api/hl_vaults", args)
  • Helper function _api_get that makes the actual HTTP GET request to the backend API; used by all tool handlers including hl_vault_leaderboard.
    def _api_get(path: str, params: dict | None = None) -> dict:
        if params:
            from urllib.parse import urlencode
            path = f"{path}?{urlencode(params)}"
        req = urllib.request.Request(
            f"{API_BASE}{path}",
            headers={
                "User-Agent": USER_AGENT,
                "Accept": "application/json",
                **({"Authorization": f"Bearer {API_KEY}"} if API_KEY else {}),
            },
        )
        try:
            with urllib.request.urlopen(req, timeout=20) as r:
                return json.loads(r.read())
        except urllib.error.HTTPError as e:
            body = e.read().decode(errors="ignore")[:400]
            return {"error": f"HTTP {e.code}: {body}"}
        except Exception as e:
            return {"error": str(e)[:200]}
Behavior3/5

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

With no annotations, the description carries full burden. It mentions 'real-time scrape of HL info API', implying a live data fetch, but doesn't disclose potential rate limits, caching, or error handling. Some transparency, but not comprehensive.

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 very concise: two sentences that front-load the key content and data source. No unnecessary words.

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

Completeness3/5

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

For a simple leaderboard tool with two optional parameters and no output schema, the description covers what data it returns but lacks detail on parameter behavior and error scenarios. Adequate but with gaps.

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

Parameters1/5

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

Schema coverage is 0% (no descriptions for parameters). The description does not explain the purpose or effect of 'limit' or 'sort_by' beyond what the schema's enum and default values implicitly show.

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 a Hyperliquid vault leaderboard, listing specific metrics (NAV, 30d return, etc.). This distinguishes it from sibling tools which cover different financial topics like airdrop farms or ETF flow.

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

Usage Guidelines2/5

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

No guidance on when to use this tool versus alternatives. The description only states what it does, not the context or any exclusions.

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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