Permanently close a hedge fund. Returns all capital to the wallet.
This is irreversible. The fund's performance record is preserved for
reporting and copy-trader settlement.
Args:
user_id: The user's ID (must own the fund).
fund_id: The fund's ID.
Returns success or error.
| Name | Required | Description | Default |
|---|---|---|---|
| fund_id | Yes | ||
| user_id | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It clearly states irreversibility, return of capital to the wallet, and preservation of the performance record for reporting and copy-trader settlement. It does not mention side effects on associated bots or marketplace listing, but the most important destructive behaviors and data-retention policy are disclosed.
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?
Every sentence earns its place: the first combines purpose and outcome, the second adds irreversibility and record preservation, and the Args section is compact yet sufficient. No filler or redundancy. The 'Returns success or error' line is minimal and acceptable.
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 two-parameter mutation tool with no annotations but an output schema, the description covers the operation's purpose, irreversibility, capital return, record preservation, ownership requirement, and return type. It omits details like required fund state or effects on bots, but these are either inferable or secondary for a close operation. The context is sufficient for an agent to call it correctly.
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%, so the description must compensate. It adds real semantics to user_id ('must own the fund') but only restates the schema for fund_id ('The fund's ID'). This is partial compensation: one parameter gains meaningful context, the other adds little beyond the schema title.
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 ('Permanently close a hedge fund') and immediately gives the primary consequence ('Returns all capital to the wallet'). The word 'Permanently' and the explicit 'This is irreversible' distinguish it from sibling tools like deactivate_fund, making the tool's unique role clear.
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 establishes that this is a permanent, irreversible action, which strongly implies it should be chosen over deactivate_fund when the intent is final closure. It also notes the ownership prerequisite for user_id. However, it does not explicitly name alternative tools or state 'use this instead of X when Y', leaving a small inference burden.
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.