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List runs in a date range

ourpr_list_runs
Read-onlyIdempotent

Training history between two dates, newest first: date, local start, name, type, miles, pace, time, elevation, average heart rate, and on a runs-only list Friel's efficiency factor and the heartbeats each mile took. Start here for totals, streaks, trends, or finding a run. For one run's splits, use ourpr_get_run with an id from here.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMost rows to return. The answer says what it left out.
end_dateYesLast day to include, YYYY-MM-DD. Example: 2026-06-30
start_dateYesFirst day to include, YYYY-MM-DD. Example: 2026-01-01
include_non_runsNoInclude rides, gym and other types. Runs only by default.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
runsYes
returnedYes
truncatedYes
total_in_windowYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.9/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so safety profile is covered. The description adds useful behavioral context: default runs-only filtering, newest-first ordering, and the extra fields on runs-only lists. Does not mention default limit or pagination behavior, which would be valuable. With annotations covering safety, a 3 is appropriate.

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

Conciseness4/5

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

Front-loaded with scope and content, followed by usage guidance and the sibling reference. Fairly dense and efficient, though the field enumeration is long. Every sentence adds value.

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

Completeness4/5

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

Covers what the tool does, what it returns (fields listed), when to use it vs. a sibling, and default filtering behavior. Output schema exists so return values needn't be explained. Minor gaps: default limit and pagination behavior aren't mentioned, but annotations cover safety.

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 100%, so all four parameters are documented in the schema (including limit, date formats, and include_non_runs behavior). The description adds nothing about parameter syntax or semantics. Baseline 3 is correct when schema does the heavy lifting.

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?

States a specific verb (list) and resource (runs) with a clear scope (date range, newest first) and enumerates the fields returned. An agent can immediately distinguish this from ourpr_get_run or ourpr_run_laps.

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

Usage Guidelines4/5

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

Gives clear usage guidance ('Start here for totals, streaks, trends, or finding a run') and explicitly names the alternative ('For one run's splits, use ourpr_get_run with an id from here'). Missing only explicit when-NOT-to-use exclusions, but the routing is clear.

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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