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renforge_control

Execute runtime actions on a running Ren'Py game, including advance, rollback, quick save/load, and toggles. Optionally wait for the corresponding business event to confirm completion.

Instructions

Run a runtime action: advance, rollback, toggle_skip, toggle_auto, toggle_afm, game_menu, hide_windows, quick_save, quick_load, reload_script, restart_interaction, or quit.

Emits correlated business events (quick_save.completed, skip.stopped, …). Set wait_for_effect=true to block until the matching event appears.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
actionYes
project_pathYes
effect_timeoutNo
interaction_idNo
wait_for_effectNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

With no annotations, the description carries the burden of behavioral disclosure. It adds value by revealing that the tool emits correlated business events and that wait_for_effect blocks until the matching event appears. However, it does not disclose potential side effects of disruptive actions like quit, reload_script, or quick_save/quick_load, nor does it mention permissions or prerequisites.

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 concise—three sentences that front-load the action list and provide only essential usage details. Every sentence contributes unique information without repetition or fluff.

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

Completeness2/5

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

Given the tool's complexity (5 parameters, 0% schema description coverage, no annotations), the description is insufficiently complete. It covers the core action list and wait_for_effect, but omits meaning for effect_timeout and interaction_id, and lacks caveats for the more disruptive actions, leaving the agent with important gaps 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%, so the description must compensate by explaining parameters. It explains 'action' by listing valid values and 'wait_for_effect' through blocking semantics, but it leaves 'effect_timeout', 'interaction_id', and 'project_path' completely unexplained, relying only on schema defaults and parameter names.

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 clearly states what the tool does with a specific verb ('Run') and resource ('runtime action'), and enumerates all supported actions, making the scope unambiguous. However, it does not explicitly differentiate from sibling tools like renforge_advance or renforge_jump that may overlap with specific listed actions, so it stops short of full sibling distinction.

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?

It provides clear context for use: execute this tool when you need to perform one of the listed runtime actions, and it gives explicit guidance on wait_for_effect. However, it does not discuss when to prefer a more specific sibling tool (e.g., renforge_advance) or mention any exclusions, leaving alternative selection implied rather than explicit.

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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