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Hunter Killer

Engine read

get_engine_read
Read-only

Returns unvalidated directional context for a symbol and horizon from the customer engine read payload as descriptive context, not a forecast.

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": {
      "symbol": "<symbol>"
    },
    "name": "get_engine_read"
  }
}

Input Schema

NameRequiredDescriptionDefault
symbolYesPerp symbol, e.g. BTCUSDT.
horizonNoOptional: 1h | 4h | 24h | 168h | 720h (default 1h).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.4/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnly, non-destructive, closed-world), so the bar is lower; the description nonetheless discloses two non-obvious traits: the data is "unvalidated" and is explicitly "not a forecast." That is real value beyond structured fields, though it omits anything about freshness, failure modes, or what a null/empty payload means.

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?

A single sentence with no filler, and the key qualifier ("unvalidated" ... "not a forecast") is placed where it will be read. Slightly dense jargon ("customer engine read payload") blunts the front-loading of the actual purpose.

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?

For a two-parameter read-only tool with full schema coverage and no output schema, the essentials are present. However, "engine read payload" is undefined internal jargon, and with no output schema the description should hint at what the response shape or confidence signals look like.

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 100% and the horizon enum values are spelled out in the schema, so the description is not required to document parameters. It adds nothing about the symbol/horizon semantics, which is acceptable but leaves it at the baseline.

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?

States a specific verb ("Returns") and a specific resource ("directional context for a symbol and horizon"), plus a scope qualifier ("from the customer engine read payload"). It does not differentiate itself from plausible siblings such as desk_read or get_decision_packet, so an agent cannot fully disambiguate from the text alone.

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?

The description names no alternative and gives no condition for choosing this over desk_read or get_decision_packet. The only guidance is interpretive ("as descriptive context, not a forecast"), which tells the agent how to read the output, not when to call the tool.

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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