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cognitive.plan_with_counterfactuals

Synthesize the best verified plan across candidate rollouts, uncertainty tracking, and constraint pruning.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
goalNo
methodNo
horizonNo
current_stateNo
task_structure_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

C2.9/5.0
Behavior3/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It adds some process context ('candidate rollouts', 'uncertainty tracking', 'constraint pruning') and implies a verification step, but does not disclose side effects, permissions, computational cost, or whether any state is modified. This is moderate value but incomplete for a complex cognitive planning tool.

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 a single sentence that front-loads the primary action ('Synthesize the best verified plan') and then efficiently lists the planning components. There is no verbosity or redundant phrasing; every phrase contributes meaning.

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 coverage, no annotations), the description is far from complete. It fails to explain what inputs like task_structure_id, goal, or horizon mean, when to use this tool, or what distinguishes it from sibling planning tools. The high-level process description is not enough for an agent to invoke it correctly without additional knowledge.

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

Parameters1/5

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 for defining the 5 parameters (goal, method, horizon, current_state, task_structure_id). The description mentions none of them and gives no hint about their meaning or how they relate to the planning process. This is a critical gap for a tool with a required task_structure_id.

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 verb ('Synthesize') and resource ('the best verified plan'), and mentions the method ('across candidate rollouts, uncertainty tracking, and constraint pruning'). This distinguishes it from generic planning tools like cognitive.hierarchical_plan, though it does not explicitly name alternatives. It is clear enough for an agent to infer its role as a plan synthesis tool.

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?

The description provides no explicit guidance on when to use this tool versus siblings. It implies usage through the mention of rollouts and pruning, but there is no statement of prerequisites, conditions, or alternatives. An agent is left to guess when this is the appropriate planning tool.

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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