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simulate_future_regrets

Anticipate potential regrets and failures before taking a major action by simulating future outcomes using Monte Carlo Tree Search.

Instructions

TRIGGER: Call this BEFORE a major architectural or strategic action to generate failure predictions. Runs a simulated MCTS (Monte Carlo Tree Search) prompt template for the LLM to imagine futures. Args: proposed_action: The action you are about to take.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
proposed_actionYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It states the tool runs a 'simulated MCTS prompt template' but does not disclose whether it reads/writes to memory, has side effects, or requires specific permissions. The behavioral model remains vague.

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 short and front-loaded with a bold 'TRIGGER' line. However, the phrasing 'Runs a simulated MCTS...' and 'Args:' could be consolidated to a single, more concise sentence.

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?

Despite having an output schema (which covers return values), the description lacks details on the output's structure (e.g., list of failure modes), prerequisites, or how to interpret results. The agent is left guessing about the tool's full value.

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?

The input schema has 0% description coverage, but the description adds meaning to 'proposed_action' by calling it 'The action you are about to take.' This clarifies the parameter's role, though it lacks examples or formatting guidance. It is minimal but adequate.

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 the tool's purpose: to generate failure predictions via simulated MCTS before major actions. It uses a specific verb ('generate failure predictions') and resource ('future regrets via MCTS'), and the explicit 'TRIGGER' line distinguishes it from sibling tools that focus on analysis or audits.

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 description explicitly says to call this tool 'BEFORE a major architectural or strategic action', providing clear context. However, it does not mention when not to use it or offer alternatives among the many sibling tools, such as 'assess_confidence' or 'pre_commit_audit'.

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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