Get Grade Progression

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds useful behavioral detail beyond annotations: the focus default ('all'), the query-filtering behavior, and what the return contains. With annotations carrying the safety burden, a 3 is fair — it adds context but not deep behavioral disclosure like ordering or edge cases.

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 well structured with a front-loaded purpose, a clear Args section, and a Returns line. There is minor redundancy — the query-filtering behavior is described twice (once in the intro, once in the Args) — but the organization makes it easy to scan, and no sentence is wasted.

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?

For a 4-parameter tool with an empty schema and no output schema, the description is remarkably complete: it covers every parameter with defaults and enums, and states the return shape (grade-by-grade breakdown, optionally filtered). Minor gaps include unspecified grade ordering (K→12 vs 12→K) and error behavior, but nothing an agent critically needs to call it correctly is missing.

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?

The input schema is empty (0 parameters), so the description carries the full burden — and it does so excellently. The Args block documents all four parameters with types, ranges, default values, and enum options ('big_ideas', 'competencies', 'content', 'all'), plus the behavior of the query filter with a concrete example. This fully compensates for the empty schema and exceeds the baseline-4 expectation for a 0-param schema.

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 states a specific verb+resource ('Show how Big Ideas, Competencies, and Content progress across grade levels for a BC subject'), which is clear and unambiguous. It distinguishes itself from siblings by its grade-progression angle, though it never names any sibling directly. The core purpose is evident and not a tautology.

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 gives clear context for when to use it ('Useful for understanding scaffolding, prerequisites, and learning trajectories'), and explains the query-filtering behavior that makes it preferable over a full dump. However, it does not explicitly name alternatives or state when not to use it versus siblings like get_course_curriculum or get_competency_connections.

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