Scaffold a local private-plugin TRMNL project from a natural-language brief, generating all four responsive Framework layouts and data states with no separate AI API needed.
Create a local private-plugin project from a natural-language brief, with all four responsive Framework layouts and data states. The harness model tailors the resulting files; no separate AI API required.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | ||
| brief | No | ||
| title | Yes | ||
| strategy | No |
Changes observed during successful MCP inspections.
v0.2.1Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare this as a non-read-only, non-destructive, non-idempotent, closed-world mutation. The description adds useful behavior context: it creates a local project, generates all four responsive layouts and data states, and relies on the harness model rather than a separate AI API. It does not explain overwrite behavior when the id already exists, but that is a minor gap given the annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loads the action and resource, and every clause adds relevant information about the generated project or the harness model. There is no wasted text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a creation tool with no output schema and annotations covering safety, the description explains the core outcome and generation approach. However, it leaves important call-time details unstated, especially the meaning of id, title, and strategy, so it is only adequately complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate, but it only implicitly references the brief parameter and says nothing about the required id and title fields or the strategy enum values. The agent learns that a natural-language brief is involved, but not how to fill the other three parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb and resource: create a local private-plugin project from a natural-language brief. It is clear what the tool produces, including four responsive Framework layouts and data states, but it does not explicitly distinguish itself from nearby project or plugin-creation siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage is implied by the natural-language brief workflow and the note that no separate AI API is required, but there is no explicit when-to-use guidance, prerequisites, or comparison to alternatives such as creating a platform plugin or saving an existing project.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.