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Glama

get_available_actions

Lists the concrete teaching actions an AI tutor can execute, showing the available next steps for the current state.

Instructions

List the concrete teaching actions the host agent may execute.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.0.0

TDQS

A3.5/5.0
Behavior3/5

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

There are no annotations, so the description carries the full burden of behavioral disclosure. The verb 'List' signals a read-only operation, but the description does not explicitly state that nothing is executed or modified, nor does it describe the output shape (names only versus detailed descriptions).

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?

A single sentence front-loads the verb and object with no filler or repetition. Every word earns its place.

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

Completeness4/5

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

For a zero-argument discovery tool, the description is largely sufficient: an agent knows what to expect and that no input is required. The lack of an output schema and the absence of detail about the exact form of the action list are minor gaps for such a simple tool.

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

Parameters4/5

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

The tool takes zero parameters, so the schema fully covers the invocation surface; the baseline is 4. The description adds context about the content of the result but lacks no argument-level information.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a clear verb ('List') and names the resource ('concrete teaching actions the host agent may execute'), so an agent knows what the tool returns. It does not explicitly contrast itself with siblings such as get_available_strategies or get_plugin_info, but the object is specific enough to separate it from most other teaching tools.

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?

No guidance is given about when to call this tool versus alternatives like get_available_strategies or get_plugin_info. The intended use is only implied by the tool name and the generic phrasing 'may execute.'

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