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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the tool is clearly a safe read. The description adds substantial behavioral detail beyond annotations: it computes arithmetic over the plan (no citations), reads both plan and executed activities, reports them separately, is silent under three weeks, and deliberately omits easy families (repeating endurance is correct). These are non-obvious behaviors essential for correct interpretation and are not present in the annotations.

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 dense and multi-sentence, but every sentence carries unique information: core purpose, per-family scope, plan-vs-execution split, edge cases (target-only climb, plan grew but work didn't, athlete outrunning plan), and limitations (silence below 3 weeks, no easy families). It is front-loaded with the primary purpose. It could be slightly tighter, but the complexity justifies the length.

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 sophisticated analysis tool with no output schema, the description is exceptionally complete. It covers what it evaluates (block progression per family), what data it reads (prescription and executed time), how it reports (two separate views), edge cases (plan grew, athlete outrunning flat plan), and limitations (silent below 3 weeks, excludes easy families). An agent has everything needed to decide when to call it and to interpret its results.

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, 100% coverage), so there are no formal parameters to document. The description compensates by clarifying the implicit inputs: the athlete's calendar, the weekly prescribed shape, working minutes, synced activities, and the plan. This adds meaning beyond the empty schema by telling the agent what data sources the tool relies on, which is exactly what a parameterless tool needs.

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, non-tautological purpose: determining whether an athlete's block is progressing or repeating across quality families (tempo/threshold/vo2/sprint). It distinguishes this tool from siblings like get_interval_progression and get_strength_progression by scope (block-level, per quality family) and by separating plan vs. executed work. No other sibling covers this exact combination.

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 implies clear usage context: you ask this tool when you need block-level progression analysis per quality family, reading both prescription and executed time. It also notes an explicit condition (silent below three weeks of history). However, it does not explicitly name alternatives or state when not to use it (e.g., for single workouts or strength). This is close to a 5 but lacks explicit exclusions.

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