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Fix repo URLs to lowercase, add arXiv paper
- Rename all GitHub links from productstein/Holomime to productstein/holomime - Fix hub built-in profile source URLs - Add LaTeX paper and BibTeX references for arXiv submission
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CHANGELOG.md

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@@ -35,5 +35,5 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
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- Support for `.personality.json` profile format
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- CLI with gradient UI and interactive prompts
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[1.1.0]: https://github.com/productstein/Holomime/compare/v1.0.0...v1.1.0
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[1.0.0]: https://github.com/productstein/Holomime/releases/tag/v1.0.0
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[1.1.0]: https://github.com/productstein/holomime/compare/v1.0.0...v1.1.0
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[1.0.0]: https://github.com/productstein/holomime/releases/tag/v1.0.0

CONTRIBUTING.md

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@@ -5,7 +5,7 @@ Thanks for your interest in contributing to holomime. This document covers the b
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## Development Setup
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```bash
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git clone https://github.com/productstein/Holomime.git
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git clone https://github.com/productstein/holomime.git
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cd Holomime
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npm install
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npm run build

README.md

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<p align="center">
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<a href="https://www.npmjs.com/package/holomime"><img src="https://img.shields.io/npm/v/holomime.svg" alt="npm version" /></a>
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<a href="https://github.com/productstein/Holomime/actions/workflows/ci.yml"><img src="https://github.com/productstein/Holomime/actions/workflows/ci.yml/badge.svg" alt="CI" /></a>
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<a href="https://github.com/productstein/Holomime/blob/main/LICENSE"><img src="https://img.shields.io/npm/l/holomime.svg" alt="license" /></a>
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<a href="https://github.com/productstein/holomime/actions/workflows/ci.yml"><img src="https://github.com/productstein/holomime/actions/workflows/ci.yml/badge.svg" alt="CI" /></a>
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<a href="https://github.com/productstein/holomime/blob/main/LICENSE"><img src="https://img.shields.io/npm/l/holomime.svg" alt="license" /></a>
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<a href="https://holomime.dev"><img src="https://img.shields.io/badge/docs-holomime.dev-blue" alt="docs" /></a>
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<a href="https://holomime.dev/blog"><img src="https://img.shields.io/badge/blog-holomime.dev%2Fblog-purple" alt="blog" /></a>
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<a href="https://holomime.dev/research"><img src="https://img.shields.io/badge/research-paper-orange" alt="research" /></a>

package.json

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},
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"repository": {
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"type": "git",
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"url": "git+https://github.com/productstein/Holomime.git"
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"url": "git+https://github.com/productstein/holomime.git"
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},
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"homepage": "https://holomime.dev",
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"bugs": {
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"url": "https://github.com/productstein/Holomime/issues"
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"url": "https://github.com/productstein/holomime/issues"
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},
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"scripts": {
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"build": "tsup",

paper/behavioral-alignment.md

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We present HoloMime, a closed-loop behavioral alignment system for LLM agents that operates at the behavioral boundary rather than the output boundary. By applying structured therapeutic protocols to agent refinement, the system simultaneously corrects behavioral patterns and generates training data. The personality specification format provides a portable, model-agnostic identity layer that accumulates behavioral intelligence across sessions and model generations.
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We release HoloMime as open-source software at `https://github.com/holomime/holomime`, including the full detection suite, therapy protocol, training data extraction, recursive alignment loop, and adversarial benchmark.
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We release HoloMime as open-source software at `https://github.com/productstein/holomime`, including the full detection suite, therapy protocol, training data extraction, recursive alignment loop, and adversarial benchmark.
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paper/behavioral-alignment.tex

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paper/references.bib

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@article{ouyang2022training,
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title={Training language models to follow instructions with human feedback},
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author={Ouyang, Long and Wu, Jeffrey and Jiang, Xu and Almeida, Diogo and Wainwright, Carroll and Mishkin, Pamela and Zhang, Chong and Agarwal, Sandhini and Slama, Katarina and Ray, Alex and others},
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journal={Advances in Neural Information Processing Systems},
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volume={35},
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pages={27730--27744},
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year={2022}
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}
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@article{bai2022constitutional,
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title={Constitutional {AI}: Harmlessness from {AI} Feedback},
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author={Bai, Yuntao and Kadavath, Saurav and Kundu, Sandipan and Askell, Amanda and Kernion, Jackson and Jones, Andy and Chen, Anna and Goldie, Anna and Mirhoseini, Azalia and McKinnon, Cameron and others},
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journal={arXiv preprint arXiv:2212.08073},
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year={2022}
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}
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@article{rafailov2023direct,
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title={Direct Preference Optimization: Your Language Model is Secretly a Reward Model},
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author={Rafailov, Rafael and Sharma, Archit and Mitchell, Eric and Ermon, Stefano and Manning, Christopher D and Finn, Chelsea},
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journal={Advances in Neural Information Processing Systems},
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volume={36},
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pages={53728--53741},
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year={2023}
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}
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@inproceedings{rebedea2023nemo,
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title={{NeMo Guardrails}: A Toolkit for Controllable and Safe {LLM} Applications with Programmable Rails},
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author={Rebedea, Traian and Dinu, Razvan and Sreedhar, Makesh Narsimhan and Parisien, Christopher and Cohen, Jonathan},
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booktitle={Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing: System Demonstrations},
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pages={431--445},
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year={2023}
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}
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@article{perez2023discovering,
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title={Discovering Language Model Behaviors with Model-Written Evaluations},
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author={Perez, Ethan and Ringer, Sam and Luko{\v{s}}i{\=u}t{\.e}, Kamil{\.e} and Nguyen, Karina and Chen, Edwin and Heiner, Scott and Pettit, Craig and Olsson, Catherine and Kundu, Sandipan and Kadavath, Saurav and others},
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journal={Findings of the Association for Computational Linguistics: ACL 2023},
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pages={13387--13434},
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year={2023}
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}
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@article{sharma2023towards,
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title={Towards Understanding Sycophancy in Language Models},
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author={Sharma, Mrinank and Tong, Meg and Korbak, Tomasz and Duvenaud, David and Askell, Amanda and Bowman, Samuel R and Cheng, Newton and Durmus, Esin and Hatfield-Dodds, Zac and Johnston, Scott R and others},
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journal={arXiv preprint arXiv:2310.13548},
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year={2023}
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}
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@article{costa1992revised,
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title={Revised {NEO} Personality Inventory ({NEO-PI-R}) and {NEO} Five-Factor Inventory ({NEO-FFI}) Professional Manual},
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author={Costa, Paul T and McCrae, Robert R},
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journal={Psychological Assessment Resources},
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year={1992},
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address={Odessa, FL}
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}
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@article{safdari2023personality,
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title={Personality Traits in Large Language Models},
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author={Safdari, Mustafa and Serapio-Garc{\'i}a, Greg and Crepy, Cl{\'e}ment and Fitz, Stephen and Romero, Peter and Sun, Luning and Abdulhai, Marwa and Faust, Aleksandra and Matari{\'c}, Maja},
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journal={arXiv preprint arXiv:2307.00184},
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year={2023}
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}
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@article{shao2023character,
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title={Character-{LLM}: A Trainable Agent for Role-Playing},
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author={Shao, Yunfan and Li, Linyang and Dai, Junqi and Qiu, Xipeng},
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journal={Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing},
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pages={13153--13187},
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year={2023}
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}
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@article{zhang2018personalizing,
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title={Personalizing Dialogue Agents: {I} have a dog, do you have pets too?},
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author={Zhang, Saizheng and Dinan, Emily and Urbanek, Jack and Szlam, Arthur and Kiela, Douwe and Weston, Jason},
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journal={Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics},
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pages={2204--2213},
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year={2018}
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}
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@article{lin2022truthfulqa,
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title={{TruthfulQA}: Measuring How Models Mimic Human Falsehoods},
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author={Lin, Stephanie and Hilton, Jacob and Evans, Owain},
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journal={Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics},
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pages={3214--3252},
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year={2022}
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}
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@article{li2023halueval,
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title={{HaluEval}: A Large-Scale Hallucination Evaluation Benchmark for Large Language Models},
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author={Li, Junyi and Cheng, Xiaoxue and Zhao, Wayne Xin and Nie, Jian-Yun and Wen, Ji-Rong},
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journal={Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing},
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pages={6449--6464},
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year={2023}
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}
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@article{jiang2023evaluating,
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title={Evaluating and Inducing Personality in Pre-trained Language Models},
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author={Jiang, Guangyuan and Xu, Manjie and Zhu, Song-Chun and Han, Wenjuan and Zhang, Chi and Zhu, Yixin},
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journal={Advances in Neural Information Processing Systems},
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volume={36},
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pages={10622--10643},
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year={2023}
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}
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@article{burns2023weaktostrong,
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title={Weak-to-Strong Generalization: Eliciting Strong Capabilities With Weak Supervision},
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author={Burns, Collin and Ye, Haotian and Klein, Dan and Steinhardt, Jacob},
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journal={arXiv preprint arXiv:2312.09390},
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year={2023}
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}
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@article{madaan2023selfrefine,
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title={Self-Refine: Iterative Refinement with Self-Feedback},
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author={Madaan, Aman and Tandon, Niket and Gupta, Prakhar and Hallinan, Skyler and Gao, Luyu and Wiegreffe, Sarah and Alon, Uri and Dziri, Nouha and Prabhumoye, Shrimai and Yang, Yiming and others},
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journal={Advances in Neural Information Processing Systems},
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volume={36},
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pages={46534--46594},
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year={2023}
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}
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@article{irving2018ai,
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title={{AI} Safety via Debate},
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author={Irving, Geoffrey and Christiano, Paul and Amodei, Dario},
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journal={arXiv preprint arXiv:1805.00899},
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year={2018}
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}

src/hub/built-in.ts

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signalCount: 7,
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detect: detectApologies,
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tags: ["built-in", "emotional", "confidence", "apology"],
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source: "https://github.com/holomime/holomime",
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source: "https://github.com/productstein/holomime",
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},
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{
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signalCount: 10,
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detect: detectHedging,
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tags: ["built-in", "communication", "confidence", "hedging"],
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source: "https://github.com/holomime/holomime",
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source: "https://github.com/productstein/holomime",
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{
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detect: detectSentiment,
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tags: ["built-in", "emotional", "trust", "sycophancy", "sentiment"],
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source: "https://github.com/holomime/holomime",
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source: "https://github.com/productstein/holomime",
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source: "https://github.com/holomime/holomime",
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source: "https://github.com/productstein/holomime",
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tags: ["built-in", "safety", "trust", "boundary", "scope"],
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source: "https://github.com/holomime/holomime",
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source: "https://github.com/productstein/holomime",
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tags: ["built-in", "resilience", "confidence", "error", "recovery"],
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source: "https://github.com/holomime/holomime",
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source: "https://github.com/holomime/holomime",
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source: "https://github.com/productstein/holomime",
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},
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];
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