Public leaderboard of Otto's paper trading competition: every participant ranked by return % on the shared $10,000 starting budget, with equity, P&L, open position count, trade count and last activity. No key required. Fills are server-priced from Chainlink, so rankings cannot be gamed with self-reported prices.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark the tool as read-only, idempotent, and non-destructive. The description adds important context beyond annotations: no API key is required, and server-priced Chainlink fills prevent gaming, providing trust and access details not present in the annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Three tightly packed sentences: a clear statement of what the tool returns, a note on access, and a note on data integrity. No redundant or filler wording.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Even without an output schema, the description enumerates returned fields (equity, P&L, open position count, trade count, last activity) and explains the ranking basis. For a simple read-only list tool with one optional parameter, this is fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has one optional 'limit' integer with default 25, but the description provides no parameter semantics (0% coverage). While 'limit' is intuitively the number of leaderboard entries, the description does not confirm this, leaving room for guesswork.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the tool as a public leaderboard for Otto's paper trading competition, ranking participants by return % on the shared $10,000 starting budget. It distinguishes itself from sibling tools like competition_my_portfolio (personal portfolio) and competition_paper_trade (trading action).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
It states 'No key required,' signaling open access, and describes the leaderboard's contents, making it clear this is the tool to use for public competition rankings. It does not explicitly contrast with alternatives or list exclusions, but the context is strong.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools have clearly distinct purposes, with detailed descriptions that separate e.g. hood_basis_snapshot from hood_basis_history and perp_spot_basis. A few clusters like flow_summary vs token_flows and multiple gap/basis tools could still cause slight ambiguity, but the descriptions are strong enough to guide correct selection.
All tool names follow a consistent snake_case pattern with domain prefixes (hood_, agent_, competition_, partner_), and verbs are used predictably (report_, execute_, get_, etc.). There is no mixing of conventions or vague generic names.
39 tools is on the high side, but the server covers a very broad domain (market data, signals, trading execution, competition, partner APIs, agent reporting). While many tools earn their place, a few could be consolidated (e.g., gap/basis variants), making it feel heavier than necessary for typical usage.
The surface covers the core lifecycle: market data, signals, paper/real/partner trading, position tracking, and performance reporting. Minor gaps exist (e.g., no explicit wallet balance or order cancellation), but the core workflows are well-covered and derived endpoints fill most needs.
