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Get runner profile requirements

get_runner_profile_requirements

Use this when runner input is missing or unclear. Explains how to obtain or generate runner input, what USRProf/evidence files should contain, whether GPX/FIT activities are enough, and how hosted MCP clients should upload artifacts.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
warningsYes
workflowYes
recommendedNo
upload_flowYes
accepted_inputsYes
profile_purposeNo
required_fieldsNo
evidence_guidanceYes
how_to_get_usrprofYes
ask_before_generatingNo

TDQS

A4.4/5.0
Behavior4/5

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

With no annotations provided, the description carries full behavioral disclosure. It goes beyond a vague 'explains requirements' by listing specific content areas (file contents, activity types, upload processes). It does not explicitly state whether the tool is read-only, but for an informational requirements tool this is sufficient.

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?

Two sentences with no wasted words. The first sentence gives the when-to-use trigger; the second packs the tool's coverage into a compact, readable list. Front-loaded and efficient.

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?

The description covers the core user scenarios and an output schema exists to document return values. It could improve by linking to sibling tools like generate_runner_profile or validate_runner_profile, but it is complete enough for an informational tool.

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

Parameters4/5

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

The tool accepts zero parameters, so there is nothing for the description to add beyond the schema. The baseline for 0-parameter tools is 4.

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 uses a specific trigger ('when runner input is missing or unclear') and enumerates the exact topics covered (USRProf/evidence files, GPX/FIT sufficiency, hosted MCP uploads). This clearly distinguishes it from sibling 'requirements' tools like get_race_plan_requirements or get_course_submission_requirements.

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?

The first sentence explicitly states when to use the tool. However, it does not mention alternatives or explicitly exclude cases; it could name what the user should do instead when runner input is not the issue.

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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TDQS

A4.1/5.0
Disambiguation4/5

Each tool targets a distinct step in the course/race-planning workflow, and descriptions carefully separate concerns like importing, enriching, segmenting, and generating a plan. The main ambiguity is among the multiple get_*_requirements helpers, but their target phases are clear enough to avoid persistent misselection.

Naming Consistency5/5

All tool names follow a consistent verb_noun snake_case pattern (create_, enrich_, export_, generate_, get_, import_, search_, submit_, validate_). There is no mixing of camelCase or inconsistent verb styles, making the API predictable and easy to navigate.

Tool Count4/5

With 16 tools, the server is at the upper edge of the ideal range but each tool serves a distinct purpose in a complex pipeline covering course import, enrichment, segmentation, runner profiling, plan creation, PDF export, validation, and catalog submission. The count feels justified for the domain rather than bloated.

Completeness4/5

The toolset covers the full lifecycle from course discovery/import through enrichment, segmentation, runner profiling, race plan generation, PDF export, and catalog submission. Minor gaps exist, such as lack of artifact list/delete/update tools and no direct race-plan editing, but agents can work around these via get_artifact and get_job.

Resources