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get_workout_history

Fetch workout history across a date range, defaulting to recent weeks. Get flat summaries for scanning sessions, or include set-level data for detailed review.

Instructions

Get workout history for a date range.

Dates must be YYYY-MM-DD. If omitted, defaults to the last weeks_back weeks. Fetches one day at a time to guarantee the full day's data is returned.

By default (include_sets=False) each item is projected to a flat summary: id, workout_id, program_id, date, workout_title, feed_item_id, saved_workout_id, completed, workout_rating, rpe, notes. Use this for scanning history and finding sessions — it's intentionally small.

Set include_sets=True only when you need set-level exercise data AND you are querying a narrow range (1-3 days). For full set data on a single known session, prefer get_workout_details(program_workout_id, program_id) instead.

Set cache_bust=True to force a fresh API fetch for every day in the range, ignoring and overwriting any cached data regardless of TTL.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
end_dateNo
cache_bustNo
start_dateNo
weeks_backNo
include_setsNo
Behavior5/5

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

With no annotations, the description fully discloses behavior: date format requirements, one-day-at-a-time fetching for completeness, the default projection, and cache_bust's side effect of 'ignoring and overwriting any cached data regardless of TTL.' This goes beyond a simple read operation and is essential context.

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?

The description is organized into clear paragraphs: overview, date/default behavior, default projection, usage guidance, and cache_bust. Each sentence adds necessary information without fluff, making it appropriately sized for the tool's 5 parameters and behavioral nuances.

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?

Given the lack of output schema and annotations, the description is remarkably complete. It explains the return format (flat summary with listed fields), covers all parameter semantics, provides usage boundaries, and presents alternatives. No critical information seems missing for this history-retrieval tool.

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

Parameters5/5

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

Schema coverage is 0%, so the description must compensate. It explains start/end date as a date range with YYYY-MM-DD format, weeks_back as the default fallback, include_sets as a boolean for set-level data with range restrictions, and cache_bust for forcing fresh fetches. All 5 parameters are given meaningful context.

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 clearly states 'Get workout history for a date range' with a specific verb and resource. It distinguishes itself from siblings by positioning the flat summary as for 'scanning history and finding sessions' and explicitly recommending get_workout_details for single known sessions.

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 explicitly guides when to use the tool ('Use this for scanning history and finding sessions'), warns against include_sets=True for broad ranges, and directs users to get_workout_details for full set data on a single session. This meets the 'when/when-not/alternatives' criterion perfectly.

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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