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armorwallet
by armorwallet

stake_quote

Generate a stake quote for token swaps by submitting a StakeQuoteRequestContainer, returning a SwapQuoteRequestContainer for blockchain staking operations.

Instructions

Retrieve a stake quote.

Expects a StakeQuoteRequestContainer, returns a SwapQuoteRequestContainer.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
stake_quote_requestsYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
swap_quote_requestsYes

Implementation Reference

  • The MCP tool handler for the 'stake_quote' tool. It validates input, calls the armor_client.stake_quote method, and handles errors.
    @mcp.tool()
    async def stake_quote(stake_quote_requests: StakeQuoteRequestContainer) -> SwapQuoteRequestContainer:
        """
        Retrieve a stake quote.
        
        Expects a StakeQuoteRequestContainer, returns a SwapQuoteRequestContainer.
        """
        if not armor_client:
            return [{"error": "Not logged in"}]
        try:
            result: StakeQuoteRequestContainer = await armor_client.stake_quote(stake_quote_requests)
            return result
        except Exception as e:
            return [{"error": str(e)}]
  • Pydantic model defining the input schema for a single stake quote request.
    class StakeQuoteRequest(BaseModel):
        from_wallet: str = Field(description="The name of the wallet that input_token is in.")
        input_token: str = "So11111111111111111111111111111111111111112"  # Hardcoded SOL token address
        output_token: str = Field(description="the public mint address of the output liquid staking derivative token to stake.") # "jupSoLaHXQiZZTSfEWMTRRgpnyFm8f6sZdosWBjx93v"
        input_amount: float = Field(description="input amount to swap")
  • Pydantic container model for the list of StakeQuoteRequest used as input to the stake_quote tool.
    class StakeQuoteRequestContainer(BaseModel):
        stake_quote_requests: List[StakeQuoteRequest]
  • Helper method in ArmorWalletAPIClient that makes the API call to get stake quote from the backend service.
    async def stake_quote(self, data: StakeQuoteRequestContainer) -> StakeQuoteRequestContainer:
        """Obtain a stake quote."""
        payload = data.model_dump(exclude_none=True)['stake_quote_requests']
        return await self._api_call("POST", "transactions/quote/", payload)
Behavior2/5

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 only states what the tool expects and returns, without mentioning whether this is a read-only operation, if it has side effects, rate limits, authentication requirements, or error conditions. For a financial tool with no annotation coverage, this is a significant gap in behavioral transparency.

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 extremely concise at just two sentences, with zero wasted words. It's front-loaded with the core purpose and efficiently communicates input/output types. Every sentence earns its place, though some might argue it's too terse given the tool's complexity.

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 has an output schema (which handles return value documentation) but zero schema description coverage for inputs, the description provides some value by naming the expected container types. However, for a financial quoting tool with no annotations and complex parameter structures, the description feels incomplete - it doesn't explain what a 'stake quote' actually represents or how it differs from other quote tools.

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?

The description explicitly names the expected input type (StakeQuoteRequestContainer) and return type (SwapQuoteRequestContainer), which provides semantic context beyond the schema's 0% description coverage. While it doesn't detail individual parameter meanings, it gives the agent crucial type information that helps understand the data structure requirements.

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

Purpose3/5

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

The description states the tool 'retrieves a stake quote', which is a clear verb+resource combination. However, it doesn't differentiate from sibling tools like 'swap_quote', 'unstake_quote', or 'calculate_token_conversion', all of which appear to provide similar quote/calculation functionality. The purpose is understandable but lacks sibling 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 about when to use this tool versus alternatives. The description doesn't mention when this tool is appropriate, what prerequisites exist, or how it differs from similar tools like 'swap_quote' or 'unstake_quote'. The agent receives no usage context.

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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