In long-horizon tool use, early-step defects passing per-call checks often propagate silently across dependency chains to cause irreversible late-stage failures—a propagation class accounting for 73.0% of diagnosed Vanilla FC failures. Because these defects are locally valid (stepwise legality) yet manifest differently across tool boundaries (semantic heterogeneity), they easily evade standard per-call guardrails and post-hoc reflection, necessitating proactive pre-execution risk anticipation. To this end, we formalize the pre-execution risk propagation problem and propose RiskGuard, a training-free, dev-calibrated runtime controller. To capture the multi-source, conjunctive dependencies inherent in tool composition, RiskGuard models execution traces via a typed dependency hypergraph. Meanwhile, a Referential/Constraint/Operational (R/C/O) kernel tracks risk transitions across semantic boundaries. Replacing rigid binary blocking, a five-mode intervention rule selects the lowest-commitment feasible response to mitigate risks smoothly. Evaluated on ToolSandbox-hard, pooled τ²-Bench, and ToolHop, RiskGuard achieves absolute gains of +0.133 Sim (0.281 → 0.414), +9.2 pp pass@1, and +4.85 pp accuracy over the baseline, with depth diagnostics showing stronger gains on harder dependency slices.