list_artifactsList the learner's saved Library artifacts (titles + metadata, newest first). Use at session start (with get_recap) to reference prior work and continue seamlessly.
| Name | Required | Description | Default |
|---|---|---|---|
| type | No | ||
| course | Yes | ||
| module | No | ||
| auth_token | No |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already convey readOnlyHint=true and destructiveHint=false, so safety is covered. The description adds value by disclosing output shape ('titles + metadata'), ordering ('newest first'), and scope ('the learner's saved Library artifacts'), which are not in the 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 two concise sentences. The first sentence front-loads the core action and output details, and the second gives usage context. There is no redundant or filler content.
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?
Annotations and an output schema reduce the need to describe return values and safety, and the description does give a clear use case. However, the 0% schema coverage combined with no parameter guidance in the description means the tool cannot be reliably invoked without significant inference about the required 'course' and optional filters.
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?
Schema description coverage is 0%, and the description provides no parameter explanations. It does not clarify the required 'course', the optional 'type' and 'module' filters, or 'auth_token'. With four parameters and no schema descriptions, the description fails to compensate, leaving parameter semantics almost entirely unexplained.
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 identifies the exact resource: 'the learner's saved Library artifacts'. It adds output scope ('titles + metadata') and ordering ('newest first'), and it clearly distinguishes from sibling get_artifact, which retrieves a single artifact rather than a list.
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 explicitly states when to use the tool: 'Use at session start (with get_recap) to reference prior work and continue seamlessly.' This provides clear contextual guidance, but it does not explicitly state when not to use it or name alternatives like get_artifact, so it stops short of a 5.
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 have clearly distinct purposes, but a few overlap or share boundaries: get_lesson vs teach_section (lesson vs section), recall_questions vs daily_drill (both spaced recall), and get_recap vs get_progress (both progress summaries). Descriptions generally help, but these pairs could cause misselection.
The vast majority follow a verb_noun snake_case pattern (get_outline, begin_course, submit_exam, etc.). Minor deviations include daily_drill (adjective_noun), interview_prep (noun_noun), login, roast, and whoami (single words), but the overall style is consistent and readable.
24 tools is on the heavy side (16-25 feels bloated), though the platform spans courses, exams, interviews, artifacts, and user management, so the breadth is defensible. Some tools could be consolidated (e.g., recall_questions and daily_drill), making it feel slightly over-scoped.
Core learner workflows are covered: discover, start, learn, assess, track, and resume. However, descriptions reference missing tools like get_review and save_artifact, creating dead ends. There's also no tool for authoring/managing courses, even though list_courses mentions user-authored courses, leaving notable gaps.