Introduction
Practitioners report a recurring failure mode in prompt-composed agentic systems: editing one prompt module can silently shift the behavior of others despite no shared variables or executable dependency. This phenomenon is formalized as compositional behavioral leakage (CBL) and shown to be detectable under targeted probing.
CBL describes interference between modules that share a context window. When multiple prompt modules are concatenated into a single context, one module's changes can influence others without explicit connections in code or state. The effect is silent: behavior shifts occur without an obvious cause visible to standard QA.
The source of CBL is architectural non-isolation: transformer self-attention does not enforce formal boundaries between concatenated modules. Attention allows information to flow across module boundaries, creating a channel for unintended interactions even when modules are logically independent.
The phenomenon was probed on a deployed job-evaluation agent (Claude Sonnet 4.6) across 144 trials. A reusable three-channel protocol perturbed non-focal modules along volume, content, and form. Only the content channel produced a detectable paired effect, with Cohen's d = 0.63 and a bootstrap 95% confidence interval excluding zero. No single recommendation flipped; the effect was sub-threshold and therefore not obvious to standard QA procedures.
Integrators should adopt contextual testing and isolation practices: evaluate modules in the full concatenated context as well as in isolation; apply perturbation protocols that vary volume, content, and form to surface paired effects; pay particular attention to content perturbations which showed measurable influence. Because standard QA may miss sub-threshold shifts, include sensitivity metrics and paired testing to detect compounding interactions across modules.
Compositional behavioral leakage arises from the lack of formal module boundaries in transformer attention and can silently alter behavior across concatenated prompt modules. Empirical probing found a content-driven effect in a deployed agent, underscoring the need for contextual testing and perturbation protocols when integrating prompt-composed systems.
1. What is CBL? CBL is interference between prompt modules that share a context window, causing silent behavior shifts.
2. Why do transformers enable CBL? Self-attention does not enforce formal boundaries between concatenated modules, allowing cross-module influence.
3. How was CBL tested? A three-channel perturbation protocol (volume, content, form) was applied to a Claude Sonnet 4.6 agent across 144 trials.
4. Which perturbation produced an effect? Only the content channel showed a detectable paired effect (Cohen's d = 0.63, bootstrap 95% CI excluding zero).
5. What should integrators do? Test modules in context, use perturbation protocols to surface interference, and monitor for sub-threshold paired effects.
Source: https://arxiv.org/abs/2606.26356