List framework targets
list_targetsThe frameworks get_prompt can write a layer for, with the id to pass as target.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
list_targetsThe frameworks get_prompt can write a layer for, with the id to pass as target.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, openWorldHint=false, so the safety and determinism profile is covered. The description adds a small amount of context about what the returned values are for (feeding get_prompt's target), but says nothing about the response shape, whether all frameworks are returned, or any auth/scope constraints.
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?
A single short sentence with no filler, and the most useful signal (the id to pass as target) lands early. The phrasing as a sentence fragment without an action verb costs it a point against a clean front-loaded statement.
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?
With no input parameters and no output schema, the description must carry the return-shape burden; it conveys that entries are frameworks paired with an id but not whether it is a flat list, what other fields appear, or whether the list is exhaustive. Adequate but with clear gaps for a discovery tool.
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 takes zero parameters, so there is nothing for the description to disambiguate; the baseline applies. The description instead clarifies what the *returned* id is consumed by, which is useful but belongs to a different concern.
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 identifies the resource (frameworks that get_prompt can write a layer for) and the key return value (the id to pass as target), but it is a noun phrase with no verb — it never states that this tool *lists* those frameworks. An agent can infer the purpose from the name/title, but the description itself does not deliver a specific verb+resource statement.
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 rather than stated: the phrase 'with the id to pass as target' hints that this is a lookup step feeding get_prompt's target parameter, and it names that sibling. However, there is no explicit when-to-use, when-not-to-use, or comparison against search_layers or get_layer.
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.