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local trajectory reduction and deterministic analysis for Dharma Agent Fabric","maintainers":[{"name":"diannt","email":"nikita@dharma-ai.io"}],"readme":"# `@dharma-ai-labs/agent-fabric-evidence-reduction`\n\nPolicy-bound local reduction for provider trajectories. It creates bounded,\nredacted capsules plus deterministic coverage, completion, runtime, and\ntool-discipline signals while keeping complete evidence in the encrypted local\nvault by default.\n\nThese signals select sessions for deeper review. They cannot determine factual\ngrounding, inference validity, sycophancy, or a semantic remediation without\napproved content evidence.\n\n- [Evidence boundary](https://github.com/dharma-ai-labs/dharma-agent-fabric#cognitive-integrity-evidence-ladder)\n- [Security and privacy](https://github.com/dharma-ai-labs/dharma-agent-fabric/blob/main/docs/10-security-privacy-and-threat-model.md)\n- [Source](https://github.com/dharma-ai-labs/dharma-agent-fabric/tree/main/packages/evidence-reduction)\n- [Dharma AI](https://www.dharma-ai.io)\n\nLicensed under MIT.\n","readmeFilename":"README.md"}