Skip to main content
Glama

Get Grade Progression

get_grade_progression
Read-onlyIdempotent

Show how Big Ideas, Competencies, and Content progress across grade levels for a BC subject. Useful for understanding scaffolding, prerequisites, and learning trajectories. When a query is provided, filters to only matching items at each grade — showing a focused vertical thread rather than a full data dump.

Args:

  • subject (string): Subject slug

  • grade_from (integer): Starting grade (0=K, 1-12)

  • grade_to (integer): Ending grade (0=K, 1-12)

  • focus (string, optional): Which element to trace ('big_ideas', 'competencies', 'content', 'all'). Default 'all'.

  • query (string, optional): Focus on a specific concept (e.g., 'evidence', 'multiplication'). Only matching items shown at each grade.

Returns: Grade-by-grade breakdown of curriculum elements showing progression, optionally filtered to a concept thread.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A4.6/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds valuable behavioral context: query filtering produces 'a focused vertical thread rather than a full data dump' and the result is a grade-by-grade breakdown. This goes beyond the annotations without contradicting them.

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 front-loaded with purpose, followed by usage context, a clean Args section with each parameter on its own line, and a Returns line. There is no filler; every sentence earns its place, and the structure makes it easy to scan.

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

Completeness5/5

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

Given the empty input schema and lack of output schema, the description fully compensates by covering purpose, parameter semantics, filtering behavior, and return shape. The 'Returns' line is sufficient, and the tool is a read-only lookup, so the overall information is complete for an agent to invoke it correctly.

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

Parameters5/5

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

Although the input schema exposes zero properties, the description fully documents all five parameters with types, defaults, and examples (e.g., focus enum values and query examples like 'evidence'). This exceeds the baseline for 0 params and makes the tool highly usable.

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 opens with a specific verb and resource: 'Show how Big Ideas, Competencies, and Content progress across grade levels for a BC subject.' This clearly defines the tool's scope and differentiates it from siblings like get_course_curriculum or search_curriculum by focusing on vertical grade-level progression.

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 explicitly states the tool is 'useful for understanding scaffolding, prerequisites, and learning trajectories' and explains when to use the query filter ('when a query is provided...'). However, it doesn't mention when not to use this tool or name specific alternatives, so it falls 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.

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A4/5.0
Disambiguation4/5

Each tool has a distinct primary purpose: listing courses, fetching full curriculum, searching, tracking progression, and finding cross-curricular connections. The only potential overlap is between get_competency_connections and search_cross_curricular, both of which handle cross-subject discovery, but they differ in input and output (one is competency-text-driven, the other is grade-and-subject-comparison-driven), so confusion is unlikely with clear descriptions.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern using snake_case: get_ for retrievals, list_ for enumeration, and search_ for searching. The naming clearly reflects each tool's function, and there are no mixed conventions or vague verbs.

Tool Count5/5

Eight tools is a well-scoped count for a curriculum data server. The set covers the essential needs: discovery (list_courses, search_curriculum), detailed retrieval (get_course_curriculum), cross-curricular analysis (get_competency_connections, search_cross_curricular), progression tracking (get_grade_progression), and change monitoring (get_course_history, get_curriculum_changes). Each tool earns its place without redundancy.

Completeness4/5

The tool surface is quite complete for read-only curriculum access and analysis: it covers listing, full retrieval, search, cross-subject comparison, grade progression, and change/history tracking. A minor gap is that there is no dedicated tool to enumerate subjects or grades independently, though list_courses can filter by subject/grade and indirectly provides that information.