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create_wallet

Generate new cryptocurrency wallets for managing digital assets, enabling secure storage and transaction capabilities within blockchain ecosystems.

Instructions

Create new wallets.

Expects a list of wallet names, returns a list of WalletInfo.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
create_wallet_requestsYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The main MCP tool handler for 'create_wallet'. It is decorated with @mcp.tool(), receives a CreateWalletRequestContainer, checks authentication, calls armor_client.create_wallet(), and handles errors.
    @mcp.tool()
    async def create_wallet(create_wallet_requests: CreateWalletRequestContainer) -> List[WalletInfo]:
        """
        Create new wallets.
        
        Expects a list of wallet names, returns a list of WalletInfo.
        """
        if not armor_client:
            return [{"error": "Not logged in"}]
        try:
            result: List[WalletInfo] = await armor_client.create_wallet(create_wallet_requests)
            return result
        except Exception as e:
            return [{"error": str(e)}]
  • Pydantic schema for a single CreateWalletRequest, defining the 'name' field for the wallet to create.
    class CreateWalletRequest(BaseModel):
        name: str = Field(description="Name of the wallet to create")
  • Pydantic container schema wrapping a list of CreateWalletRequest for batch wallet creation.
    class CreateWalletRequestContainer(BaseModel):
        create_wallet_requests: List[CreateWalletRequest]
  • Helper method in ArmorWalletAPIClient that performs the actual API call to create wallets by POSTing to '/wallets/' endpoint.
    async def create_wallet(self, data: CreateWalletRequestContainer) -> List[WalletInfo]:
        """Create new wallets given a list of wallet names."""
        # payload = json.dumps([{"name": wallet_name} for wallet_name in data.wallet_names])
        payload = data.model_dump(exclude_none=True)['create_wallet_requests']
        return await self._api_call("POST", "wallets/", payload)
  • Pydantic schema for WalletInfo, the return type of the create_wallet operations.
    class WalletInfo(BaseModel):
        id: str = Field(description="wallet id")
        name: str = Field(description="wallet name")
        is_archived: bool = Field(description="whether the wallet is archived")
        public_address: str = Field(description="public address of the wallet")
Behavior2/5

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

No annotations are provided, so the description carries full burden. It states the action ('Create new wallets') and return type ('WalletInfo'), but lacks details on permissions, side effects, error handling, or rate limits. This is inadequate for a mutation tool with zero annotation coverage.

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

Conciseness4/5

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

The description is brief and front-loaded with the core action. Both sentences are relevant, with no wasted words, though it could be slightly more structured (e.g., separating input and output details more clearly).

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

Completeness3/5

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

Given the tool's complexity (mutation with 1 parameter) and no annotations, the description is minimally adequate. It covers input and output at a high level, and an output schema exists, so return values needn't be detailed. However, it lacks behavioral context like error cases or dependencies.

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

Parameters3/5

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 mentions 'a list of wallet names' for the input, which adds meaning beyond the schema's generic 'create_wallet_requests'. However, it doesn't explain the structure of 'WalletInfo' in the output, though an output schema exists, mitigating this gap.

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

Purpose4/5

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

The description clearly states the verb ('Create') and resource ('new wallets'), making the purpose evident. It distinguishes from siblings like 'add_wallets_to_group' or 'rename_wallets' by focusing on initial creation, though it doesn't explicitly mention this differentiation.

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

Usage Guidelines2/5

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

No guidance is provided on when to use this tool versus alternatives. For example, it doesn't specify if this is for initial setup versus modifying existing wallets, or mention prerequisites like required permissions or system state.

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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