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Octodamus

Octodamus Market Intelligence

Official

get_identity

Retrieve the Octodamus identity, including oracle coverage, tracked assets, API access methods (free tier and x402 micropayments on Base), and links to documentation and social accounts.

Instructions

Get Octodamus identity and capabilities: what the oracle covers, which assets it tracks, how to access the API (free tier and x402 micropayments on Base), and links to the MCP server, X account, and API documentation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYesOracle response text with signal data, analysis, or confirmation

Implementation Reference

  • The get_identity function that executes the tool logic. Returns a TextResult containing Octodamus identity, capabilities (27 live feeds, 11-signal consensus, Polymarket edges, tokenized NYSE stocks), and API access info.
    def get_identity() -> TextResult:
        return TextResult(result=(
            "Octodamus -- autonomous AI market oracle. @octodamusai on X.\n"
            "27 live feeds. 11-signal BUY/SELL/HOLD consensus for BTC, ETH, SOL.\n"
            "Polymarket edges with EV + Kelly sizing. Congressional trading signals.\n"
            "Cross-asset macro regime (yield curve, DXY, VIX, M2).\n"
            "Tokenized NYSE stocks: AAPL, MSFT, SPY, NVDA, TSLA on Base.\n\n"
            "Access:\n"
            "- Free: 500 req/day at api.octodamus.com\n"
            "- x402: $0.01/call on Base (no account needed)\n"
            "- Annual: $29/yr at api.octodamus.com/v1/signup\n"
            "- MCP: smithery.ai/server/octodamusai/market-intelligence"
        ))
  • The TextResult schema used as the return type for get_identity (and other tools). Defines a single 'result' string field.
    class TextResult(BaseModel):
        result: str = Field(description="Oracle response text with signal data, analysis, or confirmation")
  • server.py:240-246 (registration)
    The @mcp.tool decorator that registers get_identity as an MCP tool with a description of its purpose.
    @mcp.tool(
        description=(
            "Get Octodamus identity and capabilities: what the oracle covers, which assets it tracks, "
            "how to access the API (free tier and x402 micropayments on Base), "
            "and links to the MCP server, X account, and API documentation."
        )
    )
Behavior4/5

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

No annotations are provided, so the description carries full burden. It thoroughly describes the returned information (identity, capabilities, assets, API details, links) without contradicting any implicit side effects. It is transparent about the tool's nature.

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 a single sentence that front-loads key information. While somewhat lengthy, every part adds value, making it appropriately concise for the content.

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?

Given zero parameters and an existing output schema (not shown), the description provides sufficient context by enumerating the types of information returned. It is complete enough for an AI agent to understand the tool's purpose and output.

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 input schema has no parameters, so the description does not need to add parameter-level detail. It adds context by specifying what the output covers, which is beyond the empty schema.

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?

The description clearly states the tool returns identity and capabilities of Octodamus, including coverage, assets, API access, and links. It effectively distinguishes itself from sibling tools by being a meta-discovery tool.

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?

The description implies this tool should be used first to understand the oracle's capabilities, but does not explicitly state when not to use it or mention alternatives. The context is clear enough for selection.

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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