tokmeter_streaks

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered and the bar is lower. The description adds which derived metrics are surfaced, but says nothing about the default scope behavior, aggregation source, or cost of the call. Adequate, not rich.

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?

Two sentences, zero padding, metric list front-loaded before the rationale. Nothing could be removed without losing information.

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, the metric enumeration is doing necessary work telling the agent what comes back, and all three parameters are self-documenting in the schema. The only missing piece is how these metrics differ from tokmeter_heatmap/timeline output.

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 description coverage is 100% — scope's enum values, project substring matching, and provider filtering are all documented in the schema. The description contributes no additional parameter semantics, so baseline 3 applies.

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 ('Analyze') and enumerates the exact metrics produced: active day streaks, weekend vs weekday split, session frequency, and consistency. That is far more concrete than the many overlapping 'usage analytics' siblings, though it never names an alternative (heatmap, timeline, pulse) so the agent must infer the boundary itself.

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?

"Use this to understand how regularly and intensively you use AI coding agents" gives a use context but no exclusions and no alternatives. With 20+ tokmeter_* siblings including tokmeter_heatmap and tokmeter_timeline that plausibly overlap on habit/consistency analysis, the lack of routing guidance is a real gap.

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