List modules
list_modulesThe full curriculum: every track and module with its access level and a link to its overview.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
list_modulesThe full curriculum: every track and module with its access level and a link to its overview.
| 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 declare readOnlyHint=true and destructiveHint=false. The description adds useful context about the tool's completeness ('every track and module') and the fields returned, but does not disclose potential pagination, ordering, or authentication requirements. No contradiction with 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 a single, front-loaded sentence with no filler. It efficiently conveys scope and output content without redundancy.
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 no-parameter, read-only listing tool with no output schema, the description is sufficiently complete: it names the resource, the scope, and the key fields returned. An agent can select and invoke it correctly with the given information.
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 and the schema coverage is 100%, so no parameter documentation is needed. The description compensates by explaining what the returned list contains.
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 clearly states the action ('list') and resource ('modules'), and adds scope ('every track and module') plus return content ('access level', 'link to overview'). It is not a tautology, but it does not explicitly differentiate from siblings like get_module.
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 this tool is for obtaining the full curriculum, but gives no explicit when-to-use or when-not-to-use guidance. It does not mention alternatives such as get_module for a single module or search_curriculum for targeted searches.
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.
Most tools are distinct, but fetch overlaps with read_lesson and read_post since both can return lesson/post markdown, and search/search_curriculum have similar scopes. The descriptions help clarify some boundaries, such as search returning ids for fetch, but an agent could still be uncertain which retrieval tool to use.
Tool names mostly follow a verb_noun pattern like list_modules, read_lesson, and get_module. The main inconsistencies are the bare verbs fetch and search, plus the mixed use of get versus read for similar retrieval actions.
Eight tools is well-scoped for a content platform covering curriculum browsing, lesson reading, blog posts, and search. Each tool has a reasonable place in the workflow without excessive redundancy.
The tool surface covers the full content lifecycle: discovering tracks/modules, listing posts, searching lessons and posts, retrieving module metadata, and reading full lesson or post markdown. Access-level handling is included, so there are no obvious dead ends for the stated purpose.