get_recapResume briefing for a returning learner — what they've covered, mastery levels, strong/weak topics, and recall questions to reactivate memory. Call at session start.
| Name | Required | Description | Default |
|---|---|---|---|
| course | Yes | ||
| auth_token | No |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, and the description does not contradict them. It adds helpful behavioral context by specifying the tool is for returning learners and that it includes recall questions to reactivate memory, which goes beyond the safety flags.
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, dense sentence with front-loaded purpose ('Resume briefing') followed by specific deliverables. Every clause adds value, with no wordiness or repetition.
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?
The description covers the tool's purpose, output contents, and a clear usage trigger (session start). Given that an output schema exists and annotations cover safety, the description is sufficiently complete for a relatively simple retrieval 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?
Schema description coverage is 0%, and the description does not mention the 'course' or 'auth_token' parameters at all. While 'course' is reasonably inferable, the description fails to add any semantic meaning or usage detail for the parameters, leaving the agent to guess.
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 starts with a specific verb-phrase 'Resume briefing' and details exactly what it returns: coverage, mastery levels, strong/weak topics, and recall questions. It clearly distinguishes itself from siblings like get_progress or get_lesson by framing it as a returning-learner session-start resume.
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 instruction 'Call at session start' provides an explicit when-to-use signal. It does not explicitly name alternatives or exclusions, but the context is clear enough for an agent to decide when this tool is appropriate versus other retrieval tools.
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.