toolkit_info
Returns the current toolkit state: installed MCPs, their connection status, the accounts connected to each one, and how many catalog tools each exposes.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Returns the current toolkit state: installed MCPs, their connection status, the accounts connected to each one, and how many catalog tools each exposes.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds useful context by enumerating exactly what aspects of state are exposed (installed MCPs, connection status, accounts, catalog counts), going beyond what annotations alone convey. It does not contradict any 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 entire description is a single, well-structured sentence that front-loads the purpose ('Returns the current toolkit state') and follows with a colon-delimited list of components. No words are wasted, and the structure makes it easy to parse the tool's output capabilities at a glance.
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 zero-parameter, read-only informational tool, the description fully covers the necessary information: what the tool does and what it returns, with a clear breakdown of the data included. There is no output schema, but none is needed given the simplicity. The description is completely sufficient for an agent to decide whether to call it.
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 of 4 applies. The description correctly adds no parameter-related information, which is entirely appropriate since there is nothing to explain. Schema coverage is 100% (vacuously), and no compensation is needed.
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 ('Returns') and clearly defines the resource ('current toolkit state') followed by a list of contents: installed MCPs, connection status, accounts, and catalog tool counts. It distinctly differentiates itself from sibling tools like 'show_version' by focusing on the entire state rather than just version info.
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?
The description implies clear usage context—when an agent needs to understand the toolkit's current state—by directly stating what information is returned. It does not explicitly provide when-not-to-use guidance or mention alternatives, but for a simple state-query tool, the context is sufficiently clear.
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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