Skip to main content
Glama
Maheshdayyala

CampusMind-AI

get_review_due

Identify concepts not reviewed within a set number of days. Returns overdue items with confidence and review timing for spaced-repetition study.

Instructions

Proactively find concepts that have not been reviewed in at least N days (spaced-repetition style). Returns overdue concepts with effective confidence and days since review.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
studentIdYesThe student ID
daysThresholdNoMinimum days since last review to count as overdue (default 3)
Behavior3/5

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

With no annotations, the description carries full responsibility for behavioral disclosure. It implicitly indicates a read-only operation by using 'find' and 'returns', and adds context about spaced-repetition logic. However, it does not explicitly state the absence of side effects, permissions needed, or edge cases like empty results, leaving some gaps.

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?

The description is concise, consisting of two sentences that are front-loaded with the core purpose and immediately followed by return details. No unnecessary words or repetition.

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 relatively simple tool with two parameters and no output schema, the description covers the primary purpose and return value. It lacks details on sorting, limits, or meaning of 'effective confidence', but is adequate for the tool's complexity. Sibling tools suggest a broader context, but the description stands on its own.

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

Parameters3/5

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

The schema already describes both parameters (studentId and daysThreshold) with 100% coverage, so the baseline is 3. The description adds minimal extra meaning beyond clarifying that daysThreshold corresponds to 'N days', but does not provide syntax or additional semantics beyond what the schema offers.

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

Purpose5/5

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

The description clearly states the tool finds concepts not reviewed in at least N days, with a specific verb ('find') and resource ('concepts'). It also notes the return of overdue concepts with effective confidence and days since review, distinguishing it from sibling tools like suggest_review_plan by focusing on overdue detection rather than planning.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context for when to use the tool: proactively identifying overdue concepts for spaced repetition. However, it does not explicitly mention alternatives or when not to use it, leaving some ambiguity relative to similar sibling tools like get_daily_briefing or flag_at_risk_topics.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/Maheshdayyala/CampusMind-AI'

If you have feedback or need assistance with the MCP directory API, please join our Discord server