Get detailed info for a specific hedge fund, including its roster.
Args:
fund_id: The fund's ID.
Returns a JSON object with fund details and active roster entries
(bot_id, bot_name, weight, domain, current_pnl).
| Name | Required | Description | Default |
|---|---|---|---|
| fund_id | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of disclosure. It does state the return shape (JSON with fund details and active roster entries including specific fields), which is useful. However, it does not mention error behavior, access requirements, or whether only active funds can be queried.
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 compact, front-loads the main purpose, and uses a clear Args/Returns structure. Every sentence adds meaningful information without fluff.
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 lookup tool with one parameter and an output schema, the description is mostly complete. It names the returned roster fields and the input, but lacks explicit sibling differentiation and edge-case behavior, leaving a small gap.
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?
There is only one parameter and the schema provides no description, so the description must clarify it. Saying 'fund_id: The fund's ID' adds a minimal semantic pointer, but it is largely tautological and does not explain where the ID comes from or how it is used.
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 a specific verb and resource: 'Get detailed info for a specific hedge fund, including its roster.' It clearly distinguishes this from listing tools like list_funds by emphasizing 'specific' and by naming the roster contents.
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 implies usage: call this when you need details for one fund and have a fund_id. It does not explicitly compare against siblings such as list_funds or get_active_fund, nor does it state when not to use it, so guidance is only implied.
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 target a distinct resource and action, but browse_fund_marketplace and get_marketplace_bots are easy to confuse since both surface marketplace bots with performance metrics. The detailed descriptions clarify their different intents, though the naming does not strongly reinforce the distinction.
The set almost uniformly uses snake_case verb_noun names like create_fund, list_funds, and update_fund_weights. Minor inconsistencies exist, such as get_marketplace_bots returning a list instead of a single item and browse_fund_marketplace using a different pattern from the other marketplace tools.
At 26 tools, the server is on the heavy side and above the typical well-scoped range. The broad domain of funds, strategies, marketplaces, and market data helps justify the count, but several overlapping marketplace/list tools inflate the surface and could be consolidated.
The set covers the core fund lifecycle, roster management, strategy validation/deployment, marketplace browsing, and market data reads quite thoroughly. Minor gaps remain, such as no update/delete operations for strategies and no direct tool for publishing a bot to the marketplace, but these are workable within the existing workflow.