timeseries

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

Annotations already cover the safety profile (readOnlyHint=true, openWorldHint=true), so the description's job is to add substance beyond that — and it does, spelling out the rolling-mean behavior and the exact per-metric summary/trend payload. Since there is no output schema, this return-shape disclosure is valuable. Gaps remain on default behavior (days=60, smooth=7), how sparse/unaligned days are handled, and what `end` defaults to.

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, front-loaded with the primary resource and output shape, followed by a compact metric-name list. The list is long (11 items) but earns its place given 0% schema coverage and no enum on `metrics`.

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 read-only data-retrieval tool with no output schema, the description does well on return content, but it omits the time-window parameters (`days`, `end`) that determine what slice of the series is returned, and says nothing about default values. An agent can call it, but only by guessing at the windowing semantics.

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 0% across all four parameters, so the description must carry the load. It explains `smooth` ("optional rolling mean of `smooth` days") and points to `list_metrics` for `metrics`, but `days` and `end` are never mentioned — their meaning, format, and defaults must be inferred from bare property names.

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 opens with a concrete verb+resource: "Aligned daily series for chosen metrics," and enumerates the derived outputs (rolling mean, per-metric last/mean/min/max, weekly linear trend). It gives concrete metric examples (hrv, rhr, sleep_score, load, acwr, ctl, tsb), so an agent knows exactly what data comes back. It stops short of differentiating itself from siblings like `daily` or `chart`, which also return time-ordered data.

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 parenthetical "(see list_metrics)" is genuinely useful routing advice for discovering valid metric names, but there is no guidance on when to pick this over `daily`, `chart`, or `dashboard_data`, and no exclusions. Usage is implied by the described output rather than stated.

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