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resolve_prospective_failure

Confirm or deny a predicted failure by providing the node ID and evidence. Mark it as occurred or prevented to update its status.

Instructions

Resolve a prospective failure prediction as TRUE (it happened) or FALSE (prevented/impossible). Args: node_id: The exact node ID of the Prospective_Failure occurred: True if the failure happened, False if prevented evidence: Why this outcome was reached

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
node_idYes
evidenceNo
occurredYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

With no annotations, the description carries full burden. It discloses the Boolean outcome meaning (TRUE for happened, FALSE for prevented/impossible) and records evidence. However, it does not mention side effects (e.g., state changes, persistence), idempotency, permissions, or what happens if the node_id does not exist. Minimal but acceptable.

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?

Concise: one clear sentence for the purpose, followed by a bullet list of arguments. No wasted words. Front-loaded with the key action.

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?

Given the tool's simplicity and the existence of an output schema, the description covers the essential action and parameters. Missing context: whether the node must already exist, and what the output contains. But the output schema likely covers return values. Adequate.

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?

Schema coverage is 0%, so description must compensate. It explains each parameter: node_id (exact ID), occurred (True/False), evidence (why). This adds meaning beyond the schema's bare types and titles. However, it could be more precise about format (e.g., node_id should match a specific pattern).

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 resolves a prospective failure prediction into TRUE (happened) or FALSE (prevented/impossible). It specifies the resource (Prospective_Failure) and the action (resolve), distinguishing it from sibling tools like record_prospective_failure or predictive_prevention.

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

Usage Guidelines2/5

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

No guidance on when to use this tool versus alternatives. It does not mention prerequisites (e.g., the prediction must exist) or exclude cases like already-resolved predictions. The description is purely functional.

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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