Results for “mfe”

Molecular featurization for ML (100+ featurizers). ECFP, MACCS, descriptors, pretrained models (ChemBERTa), convert SMILES to features, for QSAR and molecular ML.

Featurização molecular para ML (100+ featurizadores). ECFP, MACCS, descritores, modelos pré-treinados (ChemBERTa), converter SMILES em features, para QSAR e ML molecular.

Molecular featurization for ML (100+ featurizers). ECFP, MACCS, descriptors, pretrained models (ChemBERTa), convert SMILES to features, for QSAR and molecular ML.

Generates frontend source code files and a PR description from BA, TechLead, PM, and BE artifacts, following a level-based implementation plan.

Generates frontend source code and a PR description from BA, TechLead, PM, and BE artifacts, following a level-based implementation plan.

Molecular featurization for ML (100+ featurizers). ECFP, MACCS, descriptors, pretrained models (ChemBERTa), convert SMILES to features, for QSAR and molecular ML.

Molecular featurization for ML (100+ featurizers). ECFP, MACCS, descriptors, pretrained models (ChemBERTa), convert SMILES to features, for QSAR and molecular ML.

Fetch design context, screenshots, variables, and assets from Figma, and translate Figma nodes into production code using the Figma MCP server.

Generate a complete PHP Model Context Protocol server project with tools, resources, prompts, and tests using the official PHP SDK.

Detect NTFS timestamp manipulation (MITRE T1070.006) by comparing $STANDARD_INFORMATION vs $FILE_NAME timestamps in the MFT using analyzeMFT and Python.

Kernel-Mode Driver Framework (KMDF), the Microsoft-recommended way to write Windows kernel-mode drivers. Covers DriverEntry, EvtDeviceAdd, IRPs and IOCTLs, I/O queues, PnP and Power state machines, IRQL discipline, memory pools, WPP tracing, SAL annotations, and Driver Verifier. USE WHEN: user mentions "KMDF", "WDF kernel", "Windows kernel driver", "DriverEntry", "WdfDriverCreate", "EvtDeviceAdd", "IRP", "IOCTL", "DISPATCH_LEVEL", "PASSIVE_LEVEL", "NTSTATUS", "PoolTag", "WdfRequestComplete" DO NOT USE FOR: UMDF v2 (use `wdf-umdf`), classic WDM-only drivers, file-system filters (FltMgr is a separate framework)

Mass spectrometry analysis. Process mzML/MGF/MSP, spectral similarity (cosine, modified cosine), metadata harmonization, compound ID, for metabolomics and MS data processing.

Mass spectrometry analysis. Process mzML/MGF/MSP, spectral similarity (cosine, modified cosine), metadata harmonization, compound ID, for metabolomics and MS data processing.

Use when annotating VCF files with flanking sequence information (INFO/FS tag) or masking regions/variants in flanking sequences.

Use when a carrier asks about fuel-card vendor selection (Comdata, EFS, WEX, RTS, Pilot Flying J, Love's Connect), discount levels, fraud control, driver authorization PINs, IFTA reporting features, cash advance, money codes, or how the card fits into payroll/settlement workflows.

Expert framework for assessing and achieving product-market fit. Combines PMF measurement methodologies, Sean Ellis survey, retention analysis, segment-specific PMF, and post-PMF scaling strategy. Use when determining if product has PMF, measuring user engagement, running PMF surveys, or deciding whether to scale or keep iterating.

Detect and respond to Adversary-in-the-Middle (AiTM) phishing attacks that use reverse proxy kits like EvilProxy, Evilginx, and Tycoon 2FA to bypass MFA and steal session tokens.

Integrates on-device and cloud machine learning into Flutter apps with TensorFlow Lite and Firebase ML Kit, covering image classification, object detection, OCR, face detection, and barcode scanning.

Process and analyze mass spectrometry data: import spectra from MGF, mzML, MSP, and JSON formats; apply 40+ filters for metadata harmonization and peak cleaning; compute spectral similarities (cosine, modified cosine) for compound identification; build reproducible processing pipelines.

Convert chemical structures (SMILES or RDKit molecules) into numerical representations for machine learning using 100+ featurizers, including ECFP, MACCS, descriptors, and pretrained models like ChemBERTa.

Cost-reimbursement IGCE scaffold for CPFF, CPAF, and CPIF with fee caps and estimated-cost structure (BLS + CALC+ + per diem MCPs). USE WHEN the user asks to "build a CPFF IGCE", "cost reimbursement estimate", "CPAF fee cap", "CPIF incentive structure", "CR IGCE", or "estimated cost plus fee". DO NOT USE FOR FFP (`igce-builder-ffp`) or T&M (`igce-builder-lh-tm`).

Imported skill dmmono_ofl from anthropic

Create foliage types and place/scatter foliage instances on landscapes and meshes (FoliageService). Use when the user asks to add trees/grass/bushes/rocks as foliage, create a foliage type from a mesh, scatter or paint foliage instances, or query/remove foliage on a surface.

Python interface to OpenMS for mass spectrometry data analysis. Use for LC-MS/MS proteomics and metabolomics workflows including file handling (mzML, mzXML, mzTab, FASTA, pepXML, protXML, mzIdentML), signal processing, feature detection, peptide identification, and quantitative analysis. Apply when working with mass spectrometry data, analyzing proteomics experiments, or processing metabolomics datasets.

Análise de espectrometria de massas. Processa mzML/MGF/MSP, similaridade espectral (cosine, modified cosine), harmonização de metadados, identificação de compostos, para metabolômica e processamento de dados MS.

Mass spectrometry analysis. Process mzML/MGF/MSP, spectral similarity (cosine, modified cosine), metadata harmonization, compound ID, for metabolomics and MS data processing.

Drafts evaluation-ready U.S. federal RFP responses across all standard proposal volumes (cover letter, technical, cost/price, reps and certs). Enforces FAR compliance, CPARS references, and Section L/M alignment. Use when preparing federal solicitation submissions, responding to government RFPs, or drafting procurement bids.

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KOMODO v1.0 — Momentum Event Consensus. Uses leaderboard_get_momentum_events (real-time threshold crossings) to detect when 2+ quality SM traders cross momentum thresholds on the same asset/direction within 60 minutes. Confirmed by market concentration + volume. Enters with the momentum. Replaces MANTIS v1.0 and SCORPION v1.1 (both used stale position data).

Track investment theses across their lifecycle — from screening idea to closed position with postmortem. Register theses from screener outputs, manage state transitions, attach position sizing, review due dates, and generate postmortem reports with P&L and MAE/MFE analysis.