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serum-gen-mcp

by biogin
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Python
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edit_patch

Modify a Serum preset by changing only specified settings, save a new version, and get a summary of changes without altering the original.

Instructions

Make a Revision of an existing Serum 1 preset: only the settings you list change.

    Writes a new Preset next to the others in User → AI (named <preset>_v2,
    _v3, ...; the original is never changed, and keeps its name) and returns
    a Patch Summary of what you set plus every resulting difference from the
    original.

    Args:
        preset: The preset's name as shown in Serum's browser (a partial name
            works if it's unique), or a full path to its .fxp file.
        changes: Only the settings to change; everything else keeps its current value.
        constraints: Hard requirements to check before writing.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
presetYes
changesYes
constraintsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A3.8/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does well: it discloses the non-destructive write model, the naming scheme (_v2, _v3), that the original keeps its name and is untouched, and that a Patch Summary of changes plus all resulting differences is returned. It does not cover failure behavior when constraints are violated or any auth/permission requirements.

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?

Front-loaded with the core behavior and the non-destructive guarantee, then a compact Args block. Some sentences (the naming-parenthetical, the Patch Summary detail) are dense but each earns its place given the absence of schema descriptions.

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?

An output schema exists, so return-value detail is largely covered, yet the description still usefully names the Patch Summary contents. For a 3-parameter mutation tool with no annotations, the main remaining gap is what happens when a constraint fails and whether the new preset is loaded or activated.

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?

Top-level schema coverage is 0%, so the description's Args block is the main source of meaning for the three parameters: preset accepts a browser name (partial if unique) or a full .fxp path, changes should list only what to set, and constraints are pre-write hard requirements. This adds real value beyond the bare schema, though the constraint enum values themselves are left unexplained.

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 names a specific verb and resource ('Make a Revision of an existing Serum 1 preset') and clarifies scope ('only the settings you list change'). It implicitly distinguishes itself from write_patch by emphasizing that the original is never changed and a new _v2/_v3 preset is written, but it never names the sibling explicitly.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage is implied rather than stated: use this when modifying an existing preset without destroying the original. The mention that constraints are 'Hard requirements to check before writing' gives some context, but there is no when-not guidance and no routing to write_patch or describe_preset for related needs.

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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