list_targets
List Bring Your AI target tools. No harness data is accepted or returned.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
List Bring Your AI target tools. No harness data is accepted or returned.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the burden of behavioral disclosure. It adds a useful constraint: 'No harness data is accepted or returned,' clarifying the tool's scope. However, it doesn't explicitly state read-only behavior or return format, though 'List' strongly implies read-only.
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 short sentences, front-loaded with the action and resource. The second sentence adds a significant constraint without redundancy. Every word earns its place.
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?
Given the tool's simplicity (zero parameters, no output schema), the description is mostly complete: it states the purpose and a key behavioral limitation. However, it doesn't describe the return value's format or structure, which could be useful since there is no output schema.
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?
The tool has zero parameters, so the baseline is 4. There is no parameter information to add beyond the schema, which is fully described as empty. The description doesn't need to compensate for missing parameter details.
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 uses a specific verb ('List') and a specific resource ('Bring Your AI target tools'), clearly distinguishing it from sibling tools like list_products. It is unambiguous about what the tool does.
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?
There is no explicit guidance on when to use this tool versus alternatives such as list_products. The sentence 'No harness data is accepted or returned' is a constraint, not usage guidance. The intended use is only implied by the name and description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool targets a distinct resource or action: installation, product listing, target listing, build preview, move preview, license quoting, and checkout. No two tools have overlapping purposes, and the descriptions clearly differentiate these functions.
All tool names follow a consistent snake_case verb_noun pattern (e.g., list_products, preview_build_setup, start_checkout). There are no mixed conventions, vague verbs, or unpredictable nomenclature, making tool selection straightforward.
Seven tools is well within the ideal range for a focused MCP server. Each tool serves a distinct and necessary function in the customer journey from discovery to purchase, with no redundancy or bloat.
The tool set comprehensively covers the server's stated purpose: installation guidance, product and target discovery, previews for both setup and migration, licensing quotes, and checkout. Since the server is designed to be no-data and hands-on work happens via the local CLI, there are no obvious missing operations.