Perp mark price vs Hood on-chain spot (Chainlink per-share + pool), deviation in bps per ticker. A large |perp_vs_chainlink_bps| means the perp and spot price the same stock differently — a cross-venue opportunity or a stale-oracle signal. Fields are null for markets without a Hood spot.
| Name | Required | Description | Default |
|---|---|---|---|
| min_abs_bps | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and idempotentHint=true, covering the safety profile. The description adds valuable behavioral context: it explains the data sources (Chainlink per-share + pool), the interpretation of high deviation, and that fields are null for markets without a Hood spot. This goes beyond what annotations provide, though it doesn't mention rate limits or pagination.
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?
The description is three sentences, each earning its place: the first defines the metric, the second gives interpretive meaning, and the third handles edge cases (null fields). It is front-loaded with the core purpose, contains no fluff, and remains concise despite its informative density.
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?
Given the tool's low complexity (one parameter, no output schema), the description covers the essential context: the metric, its interpretation, and null handling. However, it omits any explanation of the parameter's behavior and does not specify the exact return structure beyond 'per ticker'. For a simple read-only query, this is almost complete, but the parameter gap prevents a perfect score.
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 only parameter, min_abs_bps, has no description in the schema (0% coverage) and is not mentioned in the description. While the name is somewhat self-explanatory (minimum absolute basis points), the description does not clarify whether it acts as a filter, a threshold, or something else. With zero schema coverage, the description fails to compensate, leaving the agent to guess at the parameter's role.
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 states the tool's purpose: it reports the deviation in bps between perp mark price and Hood on-chain spot per ticker. It uses specific terminology ('Perp mark price vs Hood on-chain spot') and contextualizes the metric as a basis. However, it lacks an explicit verb like 'list' or 'get', making the action slightly implicit, so it doesn't earn a full 5.
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?
The description provides interpretive guidance by noting that a large |perp_vs_chainlink_bps| signals a cross-venue opportunity or stale-oracle signal. This implies when the tool could be useful, but it does not explicitly state when to use it over sibling tools like oracle_deviation or hood_basis_snapshot, nor does it mention exclusions. Thus, guidance is present but not fully developed.
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.
