FortFi Treasury MCP

cancel_hyperliquid_orders

Propose cancelling resting Hyperliquid orders (limit orders and SL/TP triggers) on one market. Pass oids from list_hyperliquid_open_orders, or omit oids to cancel every resting order on that symbol. Moves no money, but cancelling a stop loss removes protection, so it follows the normal confirm_proposal flow.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "walletId": "<walletId>",
      "symbol": "<symbol>"
    },
    "name": "cancel_hyperliquid_orders"
  }
}

Input Schema

Name	Required	Description
`oids`	No	Resting order ids on this symbol (max 50). Omit to cancel all of them.
`symbol`	Yes	e.g. BTC, xyz:TSLA
`walletId`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 3, 2026

TDQS

A4.4/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden and does well: it discloses that no money moves, that cancelling a stop loss removes downside protection, and that the action routes through the confirm_proposal flow (a two-step proposal pattern). It omits permission/auth requirements and return shape, keeping it short of a 5.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three tight sentences, front-loaded with purpose, then the required input source, then the behavioral caveat. Every sentence adds distinct, load-bearing information with no repetition of the schema.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a proposal-based order-cancellation tool with no annotations and no output schema, the description covers the essential behavioral facts (no money movement, loss of stop-loss protection, confirm_proposal follow-up) so an agent can act correctly. It leaves auth/permission details and per-order failure behavior unstated, preventing a 5.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 67%, and the description compensates by explaining both the origin of oids (from list_hyperliquid_open_orders) and the semantic consequence of omitting them (cancel all on the symbol) — meaning the schema alone does not convey. walletId remains unexplained, a minor residual gap.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Propose cancelling resting Hyperliquid orders'), enumerates what counts (limit orders and SL/TP triggers), and scopes it to one market. An agent can distinguish this from sibling proposal tools like propose_hyperliquid_perp_modify or propose_hyperliquid_perp_close without opening a schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives clear usage context: pull oids from list_hyperliquid_open_orders, and omitting oids cancels every resting order on the symbol. It also names the confirm_proposal flow the agent must follow. It does not contrast against modify-style siblings, but the when-to-use direction is unambiguous.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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