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verIdyia

AutoEQ MCP Server

by verIdyia

eq_profile

Read-onlyIdempotent

Generate parametric and fixed-band equalization profiles for headphones to adjust frequency response based on measurement data.

Instructions

Get detailed EQ profile for a headphone. Includes parametric EQ, fixed band EQ, and per-band sound analysis.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesHeadphone/IEM model name (e.g., HIFIMAN HE400se, Sony WF-1000XM5)
sourceNoMeasurement source (e.g., oratory1990). Empty = best scored source

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The eq_profile handler function retrieves EQ data for a specific headphone from the database and returns a formatted string profile.
    async def eq_profile(
        name: str = Field(..., description="Headphone/IEM model name (e.g., HIFIMAN HE400se, Sony WF-1000XM5)"),
        source: str = Field(
            default="",
            description="Measurement source (e.g., oratory1990). Empty = best scored source",
        ),
    ) -> str:
        """Get detailed EQ profile for a headphone. Includes parametric EQ, fixed band EQ, and per-band sound analysis."""
        conn = get_db()
        hp = _find_headphone(conn, name, source)
    
        if not hp:
            conn.close()
            return f"'{name}' not found. Try eq_search to find the correct name."
    
        peq = conn.execute(
            "SELECT * FROM parametric_eq WHERE headphone_id = ? ORDER BY filter_num",
            (hp["id"],),
        ).fetchall()
        fbeq = conn.execute(
            "SELECT * FROM fixed_band_eq WHERE headphone_id = ? ORDER BY filter_num",
            (hp["id"],),
        ).fetchall()
        conn.close()
    
        return format_profile(hp, peq, fbeq)
  • autoeq_mcp.py:709-718 (registration)
    The eq_profile tool is registered with the MCP server using the @mcp_server.tool decorator.
    @mcp_server.tool(
        name="eq_profile",
        annotations={
            "title": "Get EQ profile",
            "readOnlyHint": True,
            "destructiveHint": False,
            "idempotentHint": True,
            "openWorldHint": False,
        },
    )
Behavior3/5

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

Annotations already provide clear hints: readOnlyHint=true, destructiveHint=false, idempotentHint=true, and openWorldHint=false. The description adds value by specifying the types of EQ data included (parametric EQ, fixed band EQ, per-band sound analysis), which gives context about the return content. However, it does not disclose additional behavioral traits like rate limits, authentication needs, or error conditions beyond what annotations cover.

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?

The description is a single, efficient sentence that front-loads the core purpose and details the included components without any wasted words. It is appropriately sized for the tool's complexity and provides essential information in a structured manner.

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 the tool's moderate complexity, rich annotations (readOnlyHint, idempotentHint, etc.), and the presence of an output schema, the description is largely complete. It specifies what data is retrieved, though it could benefit from mentioning when to use this tool over siblings. The output schema likely covers return values, reducing the need for detailed output explanation in the description.

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%, with both parameters ('name' and 'source') fully documented in the input schema. The description does not add any meaning beyond the schema, such as examples, constraints, or usage tips for parameters. Baseline score of 3 is appropriate since the schema handles parameter documentation effectively.

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 'Get' and the resource 'detailed EQ profile for a headphone', specifying it includes parametric EQ, fixed band EQ, and per-band sound analysis. However, it does not explicitly differentiate this tool from its six sibling tools (eq_compare, eq_ranking, eq_recommend, eq_search, eq_sync, eq_targets), which likely operate on similar data but for different purposes.

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 provides no guidance on when to use this tool versus alternatives. It does not mention any prerequisites, exclusions, or specific contexts for usage, nor does it reference sibling tools for comparison. This leaves the agent without direction on selecting the appropriate tool among the available options.

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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