cognitive-cell 0.9.2

A context-sensitive cognitive control stack for workflow AI.

Cognitive Cell

Cognitive Cell is a context-sensitive control stack for workflow AI.

Accepted v9 stack:

router-v4 → selector-v5 → finalizer-v9

What it does

The system separates:

1. cognitive routing
2. workflow-vs-direct pathway selection
3. final user-facing rendering

This lets the same input behave differently depending on context, posture, urgency, role, and workflow constraints.

Current evidence

Fresh holdout-v1, 100 cases:

Judge	Architecture preference	Baseline preference
gpt-4.1 primary	0.6200	0.3800
gpt-5.5 second, combined 40+60	0.5575	0.4425
Two-judge mean	0.58875	0.41125

Safe claim:

On a fresh 100-case holdout, the frozen v9 cognitive-cell stack beat a plain strong-model baseline under two standardized Op judges, with mean architecture preference around 0.589.

Caution

This is an engineering validation result, not a universal claim of superiority over frontier models. Larger benchmarks, human evaluation, ablations, and cross-provider validation are still needed.

Install

pip install -e .

Planned usage

from cognitive_cell.lego import CognitiveCellV9, CognitiveCellRequest

cell = CognitiveCellV9()

result = cell.run(
    CognitiveCellRequest(
        statement="The package label shows the wrong city.",
        context_snapshot={
            "world_facts": [
                {
                    "fact_id": "f1",
                    "fact_type": "world_fact",
                    "fact_text": "The package has not left the warehouse yet.",
                }
            ],
            "constraints": ["Optimize for low-cost correction."],
            "active_goals": ["determine the first operational step"],
        },
        metadata={"persona": "ops analyst", "time_pressure": "medium"},
        interaction_mode="workflow_component",
        autonomy_mode="suggest",
    )
)

print(result.response_text)
print(result.trace)

Known weaknesses

• Atomic observation remains weaker because pure logging competes against advice/explanation.
• Contextual observation remains mixed when direct action beats record/analyze behavior.
• Persona shift is weaker under the second judge.
• Writing support is improved but not consistently superior.