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Apply natural-language changes to an existing MCP server. Get the modified path, validation result, and test count.

Instructions

Apply a natural-language modification request to an existing MCP server.

Returns a dict with keys: path, valid (bool), tests_run (int).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelNoclaude-sonnet-4-6
requestYes
providerNoanthropic
server_pathYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.4

TDQS

B3.1/5.0
Behavior2/5

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

With no annotations provided, the description must disclose behavioral consequences itself. It states the return dict keys but does not reveal side effects such as whether files are overwritten, whether tests are actually executed, whether changes are reversible, or what happens on validation failure. The mutating nature is implied but not elaborated.

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 two concise sentences with no filler. The core purpose is front-loaded, and the return contract is stated clearly. Every sentence earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given that this is a mutating operation with no annotations, 0% schema coverage, and a set of overlapping sibling tools, the description is too thin. It covers purpose and return shape but omits usage guidance, side effects, and parameter semantics, making it insufficient for an agent to invoke it with full confidence.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description should compensate by explaining the parameters. It only indirectly alludes to server_path ('existing MCP server') and request ('modification request'), but gives no meaning for model or provider, their defaults, or the relationship between them. The agent must rely on the schema defaults without semantic context.

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 uses a specific verb ('Apply') and resource ('an existing MCP server'), and clarifies the input is a natural-language modification request. This clearly distinguishes the tool from siblings like generate, validate, and inspect by emphasizing modification of an existing server.

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 explicit guidance on when to use this tool versus alternatives such as generate, plan, or doctor. The word 'existing' weakly implies this is not for creation, but there is no exclusionary language or mention of prerequisites like planning or validating first, leaving the agent to infer usage.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.