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Strava Activity Series

strava_activity_series
Read-onlyIdempotent

Get a bounded time-series for one activity metric, returning exact stats plus a downsampled series capped at 500 points to keep long activities within context limits.

Instructions

Bounded time-series for one activity metric (agent-safe-series/v1). Returns exact stats on full-resolution samples plus a downsampled series capped at 500 points, so a multi-hour ride never blows the context window. Prefer strava_get_activity / zones first; reach for this when you need the shape of the effort. GPS is never returned here. Shared contract with garmin_activity_series / Kindred workout_series.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesStrava activity id.
metricNoWhich sample stream to shape. GPS is never available here; use strava_get_activity_streams with include_gps for latlng.heart_rate
max_pointsNoPoint budget for the returned series. Server hard cap is 500.
response_formatNomarkdown
reference_max_hrNoReference max heart rate for zone math (reference_source=caller_provided). Without it, uses activity max_heartrate when available, else series observed max.
resolution_secondsNoRequested bucket width. Raised automatically when it would exceed max_points; response reports what was used.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
unitYes
notesYes
statsYes
methodYes
metricYes
pointsYes
t_unitYes
start_timeNo
activity_idYes
downsampledYes
data_qualityYes
time_in_zoneNo
source_pointsYes
returned_pointsYes
contract_versionYes
resolution_secondsYes
requested_resolution_secondsYes
Install Server

TDQS

A4.7/5.0
Behavior5/5

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

With readOnlyHint=true, idempotentHint=true, and destructiveHint=false already present, the description still adds real behavioral value: the 500-point cap, full-resolution exact stats plus downsampled series, the 'never blows the context window' guarantee, and the explicit exclusion of GPS. No contradiction with annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Four sentences, each adding distinct information: what it returns, why the cap exists, when to prefer alternatives, and what it never returns. Dense and front-loaded without wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a read-only, idempotent tool with a rich input schema and an output schema, the description covers usage context, behavioral constraints, and an important negative (no GPS). Nothing an agent needs to select and invoke it correctly is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 83%, so the input schema already documents most parameters in detail. The description adds context around the point budget ('capped at 500 points', 'never blows the context window') and the metric constraint (GPS never available), but it does not need to re-explain each parameter.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific, bounded resource — 'time-series for one activity metric' — and states it returns exact stats plus a downsampled series. It also differentiates from related tools by noting GPS is never returned and by naming strava_get_activity / zones as the preferred alternatives for full activity detail.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It gives an explicit routing rule: 'Prefer strava_get_activity / zones first; reach for this when you need the shape of the effort.' This tells the agent both when not to use it and when to reach for it, which is exactly the guidance needed.

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

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