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osick
by osick

submit_playground_run

Create a playground practice run for a competition, specifying the run request with models, solvers, or custom problems.

Instructions

Create a Playground practice run.

Scope: playground.write. run_request's shape depends on the competition's submissionSpec.kind -- read get_competition first. Known shapes today:

  • cheatsheet: {"models": ["", ...], "problems": [{"problemSet": "", "index": 0} | {"custom": {"equation1": "...", "equation2": "...", "goldAnswer": true}}, ...], "configurations": [{"cheatsheet": ""}, ...] (optional, omit for an unconditioned baseline), "repeat": 1 (optional, max 5)}

  • solver-participation: {"solverCode": "<lean 4 source>", "solverName": "" (optional), "problemIds": ["", ...], "allowedModels": ["", ...] (optional)}

  • model-reference: {"modelName": "/", "commitHash": "<40-hex-char sha>", "problemSetId": "", "hfToken": "" (optional, for private/gated repos), "note": "<=500 chars" (optional)}

Returns {"runId": ..., "status": "pending"}. Poll get_playground_run / list_playground_run_results for progress.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
run_requestYes
competition_idYes
Behavior4/5

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

With no annotations, the description carries full burden. It discloses the return value and polling behavior, and mentions scope playground.write. No mention of error states or rate limits, but generally transparent.

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?

Well-structured: summary, scope, dependency, shapes, return value, and polling instructions. Information is front-loaded and each sentence adds value.

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 complexity (nested objects, no output schema, no annotations), the description is comprehensive, covering purpose, usage, parameter shapes, and expected behavior.

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 description must explain parameters. It does so thoroughly, detailing three distinct shapes for run_request based on competition kind, including optional fields and constraints.

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 'Create a Playground practice run.' It uses a specific verb (create) and resource (Playground practice run), and distinguishes from sibling tools like get_playground_run and cancel_playground_run.

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?

Provides guidance to read get_competition first, and gives explicit shapes for different run_request kinds. However, it does not explicitly state when not to use this tool vs alternatives.

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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