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horustechltd

horus-flow-mcp

by horustechltd

get_ignitions

Detect volatility ignition events to identify potential explosive price moves. Returns ignition state and directional bias for timing exits or preparing for breakouts.

Instructions

Detect volatility ignition events — potential explosive price moves.

Returns ignition state (DORMANT, RISING, IGNITED) and directional bias.
IGNITED = imminent large move, reduce or exit positions.
RISING = pressure building, prepare for breakout.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The get_ignitions tool handler. Decorated with @mcp.tool(), it fetches volatility ignition event data from the /v1/intelligence/ignitions endpoint and returns JSON. Returns ignition state (DORMANT, RISING, IGNITED) and directional bias.
    # ─── Tool 9: Ignition Detection ──────────────────────────
    @mcp.tool()
    async def get_ignitions() -> str:
        """Detect volatility ignition events — potential explosive price moves.
        
        Returns ignition state (DORMANT, RISING, IGNITED) and directional bias.
        IGNITED = imminent large move, reduce or exit positions.
        RISING = pressure building, prepare for breakout.
        """
        data = await _fetch("/v1/intelligence/ignitions")
        return json.dumps(data, indent=2)
  • The tool is registered via the @mcp.tool() decorator from FastMCP on line 253. The mcp instance is created on line 44.
    @mcp.tool()
  • The _fetch helper function used by get_ignitions to make HTTP requests to the Horus RapidAPI endpoint /v1/intelligence/ignitions.
    async def _fetch(endpoint: str) -> dict:
        """Fetch data from the live RapidAPI endpoint."""
        async with httpx.AsyncClient(timeout=10.0) as client:
            try:
                resp = await client.get(
                    f"{RAPIDAPI_BASE_URL}{endpoint}",
                    headers=HEADERS,
                )
                if resp.status_code == 200:
                    return resp.json()
                elif resp.status_code in [401, 403]:
                    return {
                        "error": True,
                        "signal": "UNAUTHORIZED",
                        "detail": "Invalid or missing RAPIDAPI_KEY. Please verify your RapidAPI subscription."
                    }
                elif resp.status_code == 429:
                    return {
                        "error": True,
                        "signal": "RATE_LIMITED",
                        "detail": "You have exceeded your RapidAPI quota. Please upgrade your plan."
                    }
                return {
                    "error": True,
                    "status_code": resp.status_code,
                    "detail": resp.text,
                }
            except Exception as e:
                return {
                    "error": True,
                    "detail": f"Network Error: {str(e)}"
                }
Behavior4/5

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

With no annotations, the description carries full burden. It discloses outputs (state and bias) and interprets them. It does not mention side effects, which is acceptable for a read-like tool. Lacks explicit read-only hint but is sufficiently transparent.

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 sentences, each adding value: purpose, outputs, interpretation. No unnecessary words.

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 no parameters and presence of output schema, description explains key return fields meaning. Could add more detail on directional bias format, but complete enough for usage.

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?

No parameters exist and schema coverage is 100%, so description need not add param details. Baseline of 4 is appropriate.

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 detects volatility ignition events and returns ignition state and directional bias. It distinguishes itself from sibling tools (flow and intelligence tools) by focusing on explosive price moves.

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 provides usage context by explaining what IGNITED and RISING states imply (reduce positions, prepare for breakout), but does not explicitly state when not to use or mention alternatives.

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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