Machine-readable news events (crypto + stocks). symbols is comma-separated (NVDA,BTC), event_type: listing|hack|regulation|earnings| etf|partnership|macro|liquidation|stablecoin|general. importance 0-100.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| symbols | No | ||
| event_type | No | ||
| min_importance | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds useful details like event_type values and importance scale (0-100), but does not mention output format, pagination, or limit behavior. This adds some value beyond annotations but is not rich.
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 a single, information-dense sentence. It front-loads the core purpose and packs in parameter formats and value ranges without wasteful prose. Every element contributes to usage understanding.
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?
For a simple read-only list tool, the description covers the essential invocation details: symbols, event types, and importance scale. It lacks information about the response structure (which is machine-readable but undefined) and the effect of limit, but the schema provides defaults. Given annotations handle safety, this is fairly 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?
Schema description coverage is 0%, but the description compensates by explaining symbols (comma-separated with examples), event_type (full enumeration), and importance (0-100). It does not explicitly explain 'limit' or 'min_importance', though their names are self-explanatory. Coverage of 3 out of 4 parameters is strong.
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 states the tool provides 'Machine-readable news events (crypto + stocks)', which clearly identifies its purpose and scope. It distinguishes from siblings by focusing on news events, but the phrasing is a noun phrase rather than a specific verb like 'get' or 'list', so it's slightly less direct.
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 gives no explicit guidance on when to use this tool versus alternatives. It does not mention any exclusions, prerequisites, or comparison to sibling tools like hood_feeds or reddit_alpha_signals. The context is implied by the domain but not clearly articulated.
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.
