Skip to main content
Glama

whats_new

Read-only

Aggregates recent cross-course Canvas activity, unread inbox items, planner tasks, announcements, feedback, and missing work into one catch-up digest so users can review what needs attention.

Instructions

Cross-course 'what is new since last check' digest.

Aggregates activity stream, inbox unread, planner, announcements, recent feedback, and missing work into one typed response with a template-generated summary string. This is the main "catch me up" tool — prefer it over stitching together activity_stream_summary + planner_items + missing work manually.

Input Schema

NameRequiredDescriptionDefault
lookback_daysNo
lookahead_daysNo

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.12.0

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnlyHint true, destructiveHint false, openWorldHint true), so the description need not restate that. It adds genuine context by describing the aggregation scope and the template-generated `summary` string in the typed response. It omits cost or latency implications of an open-world multi-source aggregation, which is the main remaining gap.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The digest purpose is front-loaded in the first line, followed by the source list and the sibling routing advice in a logical order. The sentence about being the 'main catch me up tool' slightly repeats the opening purpose statement, but the description contains no substantial waste.

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

Completeness3/5

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

An output schema exists, so return values need no explanation, and the annotations plus the aggregation list cover behavior well. For a two-parameter tool at 0% schema coverage, however, leaving both time-window parameters undefined is a material omission in an otherwise complete definition.

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

Parameters2/5

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

Schema description coverage is 0%, so the description carries the full burden for `lookback_days` and `lookahead_days`. 'Since last check' loosely implies a backward window, but the description never explains the unit, the default of 14, or what `lookahead_days` (default 7) controls, so an agent must guess whether future planner items are included.

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 states a specific verb-and-resource ('what is new since last check' digest) and enumerates the sources it aggregates: activity stream, inbox unread, planner, announcements, recent feedback, and missing work. It also distinguishes itself from siblings by naming activity_stream_summary and planner_items as things it replaces.

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?

It gives clear positive routing ('the main catch me up tool') and an explicit preference over manually stitching together activity_stream_summary, planner_items, and missing work. It does not state when not to use it, for example when a learner wants a single-course view.

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