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

Annotations already cover safety (readOnlyHint) and world-openness, so the description's job is to say what the evaluation actually produces — and it does, listing every reported metric plus the On track/Behind verdict and the assumption set it reuses. It does not mention error handling for malformed dates or what happens to past-due exams, which keeps it out of the top band.

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 purpose and output list are front-loaded in a single dense sentence, followed by the two pieces of caller guidance that actually matter (from_date, flexible date formats). The example prompt earns its place by demonstrating the natural-language date input, though it slightly elongates an otherwise tight description.

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?

With no output schema and five parameters, the description correctly spends its words describing the returned metrics and the assumptions behind the verdict. An agent could call this correctly from the description plus schema; only edge behavior (past exam dates, malformed date strings) is left implicit.

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 coverage is 100% and every parameter, including the nested topic hours and weekday-hour objects, is already documented in the input schema. The description adds only the consistency constraint that hours_per_day, hours_per_weekday and days_off should match the plan tools, and repeats the plain-text date parsing already stated in the schema — so baseline 3 is right.

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?

States a specific verb and resource — checking whether you are on track for each exam — and enumerates the exact outputs (days left, study days left, hours still to study, hours per study day, On track/Behind verdict). That framing cleanly separates it from the plan-creating siblings like make_study_plan and build_study_plan.

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?

Implies its role as the read-only check that runs against a plan, and tells the agent to pass from_date to count from a fixed day. It stops short of an explicit 'use this after make_study_plan, use X instead if you have no plan yet' routing statement, so the agent must infer the ordering from 'the same hours per day ... as the plan tools'.

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