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GardenArena GardenScript

bamboo_training_run

Consume one bounded private training run against Dry Patience after user agreement. GardenScript 0.5 bamboo only, fixed public scenario and budgets. Shared web/MCP quotas; temporary local storage, no official submission or publication, no LLM call. Keep run_token private.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sourceYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.4/5.0
Behavior4/5

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

The annotations declare readOnlyHint=false, openWorldHint=false, idempotentHint=false, and destructiveHint=false, so the agent knows this is a non-destructive write operation with no external side effects. The description adds valuable context beyond annotations: it specifies temporary local storage, no official submission or publication, no LLM call, shared quotas, and that the run_token must be kept private. This goes beyond what annotations provide, though it doesn't detail error handling or rate-limit specifics.

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?

The description is three concise sentences that front-load the core action and constraints. It avoids redundancy and packs multiple behavioral details efficiently. Slight improvement possible by integrating parameter guidance, but overall well-structured.

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

Completeness3/5

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

The tool has an output schema, so return values need not be described. The description covers behavioral traits and constraints adequately, but it omits any explanation of the required 'source' parameter (0% schema coverage) and doesn't clarify what 'Dry Patience' or 'GardenScript 0.5' entail. For a tool with a mandatory parameter and domain-specific context, more information is needed for correct invocation.

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

Parameters2/5

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

Schema description coverage is 0%, meaning the single 'source' parameter has no description in the schema. The tool description mentions 'run_token' but does not explain what the 'source' parameter should contain or its format. With a required parameter and no schema documentation, the description fails to compensate for the coverage gap.

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

Purpose4/5

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

The description states a specific action ('consume one bounded private training run') against a named resource ('Dry Patience') with a clear scope. It differentiates from siblings like coop_workshop_run and farm_autopilot_run by specifying it's a bamboo-only training run. However, 'Dry Patience' and 'GardenScript 0.5 bamboo' are domain-specific terms that an agent may not understand without additional context.

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

Usage Guidelines3/5

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

The description implies usage context ('after user agreement') and constraints ('private training run,' 'no official submission'), but it doesn't explicitly state when to use this tool versus alternatives like coop_workshop_run or farm_autopilot_run. An agent can infer it's for training purposes, but the lack of explicit when/when-not guidance leaves ambiguity.

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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