atlas

Plugin atlas from marketplace usatlas-marketplace in usatlas/marketplace. Commands read from the repo's manifest — yesterday.

Skills (43)

• acm

  Use when building ATLAS software with acm (AtlasACM): setting up a cmake build environment with acmSetup, compiling packages, cloning or sparse-cloning athena, adding or excluding packages from the build, creating skeleton analysis packages, running ctests, or troubleshooting cmake configuration iss

• analysis-spec-builder

  Use when producing a structured ATLAS analysis specification document: formalizing an analysis design into a specification.md file, documenting signal/control/validation regions, background methods, systematic uncertainties, and statistical model choices, or when the atlas-analysis-architect agent n

• art

  Use when running or writing ART (ATLAS Release Tester) validation tests for ATLAS nightly builds, using art.py to run, list, or compare tests, debugging ART test failures in nightly CI, or understanding ATLAS release validation infrastructure.

• astyle

  Use when creating ATLAS publication-quality plots with the official ATLAS ROOT style macros (atlasrootstyle), applying SetAtlasStyle, placing ATLAS labels (Internal, Preliminary, Simulation), using ATLASLabel or myText helper functions, or following ATLAS publication plotting conventions in ROOT or

• atlantis

  Use when visualizing ATLAS detector events with the Atlantis event display: launching the Atlantis GUI, opening JiveXML event files, producing JiveXML output from Athena reconstruction, or troubleshooting Java runtime issues in containerized environments.

• atlas-containers

  Use when running ATLAS software inside containers via setupATLAS -c, choosing between Apptainer/Docker/Podman/Shifter, setting up containers on macOS or without CVMFS, mounting directories, passing GPU flags, submitting batch jobs from containers, using custom or standalone container images, joining

• atlas-software

  Use when a question involves ATLAS software concepts: Athena framework, event data model, CP algorithms, derivation formats (DAOD), CMake build system, CVMFS software releases, analysis releases, ASG tools, or any ATLAS-internal software infrastructure. This skill routes to the right resource or sub

• awkward

  Use when working with jagged or variable-length arrays in Python HEP analysis: building event records with ak.zip, filtering nested arrays, computing combinatorics (cartesian products or combinations), flattening ragged arrays, using argmin/argmax with keepdims, broadcasting per-event weights to per

• cabinetry

  Use when building an ATLAS statistical analysis with cabinetry: writing a cabinetry config file, building histogram templates from ROOT NTuples, constructing a pyhf workspace, running a profile likelihood fit, visualising pre/post-fit data-MC comparisons, producing pull plots and NP rankings, or com

• centralpage

  Use when searching for ATLAS Monte Carlo or data samples: querying the PMG central sample database for MC datasets by process, generator, or campaign, looking up cross-sections and filter efficiencies, or identifying which centrally produced samples are available for a given physics process.

• coffea

  Use when writing a columnar ATLAS analysis with coffea: defining a NanoEvents or custom processor, running over ROOT files, accumulating histograms with hist, applying scale factors and systematic weights, or migrating a for-loop event analysis to a coffea processor pattern.

• cpp-bindings

  Use when writing Python bindings for C++ HEP code with nanobind or pybind11: exposing a C++ class or function to Python, binding STL containers (vector, map), handling numpy/awkward array interop, choosing between nanobind and pybind11, or setting up a CMake build that produces a Python extension mo

• decaylanguage

  Use when working with particle decay chains in Python: parsing EvtGen or DecFiles `.dec` decay descriptors with DecFileParser, building DecayChain and DecayMode objects programmatically, visualizing decay trees with DecayChainViewer, computing visible branching fractions, or converting AmpGen amplit

• eiclient

  Use when working with the ATLAS Event Index: looking up which dataset contains a specific run/event number, picking events from a list of run/event pairs, tracing event provenance through processing stages (RAW to AOD to DAOD), or listing all events in a dataset.

• fastframes

  Use when you need a supported RDataFrame-based framework to process CP-algorithm NTuples or TopCPToolkit outputs into analysis histograms.

• fastjet

  Use when running jet clustering in Python with the Scikit-HEP fastjet package (or migrating from the deprecated pyjet): calling anti-kt or Cambridge/Aachen algorithms on particle four-vectors, accessing jet constituents, computing jet substructure variables (N-subjettiness, soft drop), clustering je

• fsspec-xrootd

  Use when accessing ROOT files on EOS, WLCG grid storage, or any XRootD endpoint from Python: mounting an XRootD path as an fsspec filesystem, passing root:// URIs to uproot or awkward, listing or writing remote directories, multi-site replica access, or troubleshooting XRootD authentication and prox

• hepunits

  Use when writing unit-safe HEP code in Python: converting between MeV and GeV, expressing cross-sections or luminosities with explicit units, computing ctau or decay lengths from particle lifetimes, checking that cut thresholds or histogram ranges carry correct units, or bridging hepunits values wit

• hist

  Use when creating, filling, slicing, or plotting histograms with the scikit-hep hist library: defining axes (Regular, Variable, StrCategory), filling with weighted data, using UHI indexing (loc, rebin, sum), applying mplhep ATLAS style, producing ratio panels for data/MC comparisons, or projecting m

• histfitter

  Use when setting up, running, or debugging a HistFitter statistical analysis: writing config scripts, defining channels/samples/systematics, choosing systematic types, running workspace generation and fits, producing yields or systematics tables, making pull/ranking plots, running hypothesis tests o

• iminuit

  Use when you need to minimize a scalar cost function in Python using MINUIT2 via iminuit (e.g., unbinned likelihood fits or least-squares fits), and you need HESSE/MINOS-style uncertainties or custom cost functions.

• lcgenv

  Use when setting up standalone LCG (CERN SFT) software packages via lcgenv or views: listing available LCG releases and platforms, configuring individual packages from a specific LCG release, setting up an entire LCG release at once with views, or combining LCG packages with other ATLAS tools like R

• managetier3sw

  Use when installing, updating, or removing ATLAS software on a local Tier-3 cluster, laptop, or desktop with manageTier3SW, configuring ATLASLocalRootBase for a non-CVMFS site, running local ATLAS software diagnostics, setting up local post-user scripts, or troubleshooting Tier-3 ATLAS software inst

• mplhep

  Use when creating ATLAS publication-quality plots with matplotlib using mplhep: applying the ATLAS experiment style, placing ATLAS labels (Internal, Preliminary, Simulation), plotting 1D or 2D histograms from hist/uproot/numpy, making data/MC comparison plots with ratio panels, using mplhep comparis

• panda

  Use when submitting ATLAS grid jobs with prun or pathena, monitoring tasks with pbook or BigPanDA, troubleshooting failed grid jobs, choosing between prun and pathena for distributed analysis, or configuring container-based or GPU grid submissions.

• particle

  Use when looking up particle properties (mass, charge, width, PDG ID, lifetime, spin, parity) from the PDG tables in Python: converting between particle names and PDG IDs, filtering decay modes, checking if a particle is stable, querying quantum numbers (J, P, C, G, I), working with MC generator out

• pyhepmc

  Use when reading or writing HepMC3 event records in Python: opening HepMC2, HepMC3, LHEF, or HEPEVT files from a Monte Carlo generator, iterating over events, accessing truth particles and vertices, filtering by status code or PDG ID, traversing decay trees via particle parents/children, using the N

• pyhf

  Use when you need HistFactory statistical modeling, profile-likelihood fits, CLs limits, or workspace manipulation in Python.

• pyhs3

  Use when reading, writing, or validating binned and/or unbinned statistical models in the HS3 (HEP Statistics Serialization Standard) JSON format: loading an HS3 workspace, validating schema compliance, building and evaluating a model (logpdf), serialising a workspace for publication, or working wit

• pylhe

  Use when reading or writing Les Houches Event XML (LHE) or HDF5 (LHEH5) files in Python: reading parton-level events from MadGraph, Powheg, Sherpa, Pythia, or Whizard generators, iterating over initial- and final-state parton four-vectors, accessing event weights and scale/PDF reweighting blocks, co

• quickfit

  Use when fitting a RooWorkspace dataset with quickFit, generating an Asimov dataset with quickAsimov, computing asymptotic CLs limits with quickLimit, generating toy datasets with quickToy, rebinning datasets with quickRebin, or calculating nuisance parameter pulls with quickPull.

• roounfold

  Use when performing statistical unfolding for an ATLAS cross-section measurement: building a response matrix from MC, applying Bayesian iterative unfolding (RooUnfoldBayes), SVD unfolding (RooUnfoldSvd), bin-by-bin correction factors, or any other RooUnfold algorithm; handling detector-level fakes o

• servicex

  Use when querying ATLAS data remotely via ServiceX: fetching branches from ROOT NTuples with the Uproot backend, writing FuncADL queries against DAOD_PHYS or DAOD_PHYSLITE, selecting datasets by Rucio name or EOS path, delivering data as awkward arrays, using servicex_analysis_utils helpers, debuggi

• setupatlas

  Use when setting up the ATLAS software environment with setupATLAS or ATLASLocalRootBase, running asetup to configure an Athena or StatAnalysis release, using lsetup to set up ROOT, rucio, panda, scikit-hep, LCG views, or other ATLAS tools, using acm (AtlasACM) for cmake/git-based package management

• statanalysis

  Use when setting up the ATLAS StatAnalysis software release with asetup, choosing the right StatAnalysis branch for a given ROOT version or OS, running statistical analysis tools included in StatAnalysis (xRooFit, TRExFitter, HistFitter, cabinetry, quickFit, quickstats, workspaceCombiner, xmlAnaWSBu

• topcptoolkit

  Use when using TopCPToolkit (TCT) to produce ATLAS analysis NTuples from DAOD files: setting up the YAML-based analysis configuration (Jets, Electrons, Muons, OverlapRemoval, EventSelection, Output blocks), understanding the single-TTree output format with systematic variations and object selection

• trexfitter

  Use when setting up or running a TRExFitter statistical analysis: writing a TRExFitter config file, defining regions, samples, systematics, and NormFactors, running actions (n/h/w/f/d/p/r/l/s), computing limits or significance, diagnosing fit convergence failures, NP pulls or constraints, or exporti

• uproot

  Use when reading or writing ROOT files in Python without a ROOT installation, or when encountering issues opening TTrees, RNTuples, or histograms.

• vector

  Use when computing 4-vector quantities in Python: invariant mass, deltaR, transverse momentum, boost, or any Lorentz vector arithmetic over collections of particles. Also use when registering scikit-hep vector behaviors on awkward-array records so that ak.zip objects gain Momentum4D methods, or when

• workspacecombiner

  Use when combining multiple RooFit workspaces with workspaceCombiner, editing workspace parameterization with the manager edit command, printing or splitting workspace categories, regulating a workspace, or preparing NP renaming maps for ATLAS Higgs combination workflows.

• xcache

  Use when setting up a local XCache disk caching proxy for XRootD root:// protocol access: starting an xcache instance, caching remote ATLAS files on a laptop or Tier-3 site, using ALRB_XCACHE_PROXY with ROOT or Rucio file replicas, or troubleshooting VOMS proxy and cache directory issues.

• xmlanawsbuilder

  Use when building a RooFit workspace from XML cards with xmlAnaWSBuilder or XMLReader, constructing analytic signal or background models for H→γγ or similar ATLAS analyses, configuring systematic uncertainties in the XML workspace builder, setting up counting experiments, implementing blinded analys

• xroofit

  Use when building RooFit statistical models with xRooFit, constructing workspaces with channels and samples, adding systematics or nuisance parameters, fitting models to data, constructing NLL functions, diagnosing fit convergence failures (status codes, covariance quality), computing profile likeli

Subagents (5)

• atlas-analysis-architect

  Use when designing an ATLAS physics analysis end-to-end: choosing signal and control regions, background estimation strategy, selecting a ntupling framework (TopCPToolkit vs FastFrames vs coffea), selecting a statistical model (pyhf vs cabinetry vs TRExFitter vs HistFitter), verifying dataset availa

• atlas-analysis-coder

  Use when writing Python code to access, process, or plot ATLAS data: reading ROOT files with uproot, querying ATLAS datasets with ServiceX, manipulating event records with awkward-array, filling and styling histograms with hist/mplhep, computing physics quantities (invariant mass, deltaR, MET signif

• atlas-data-explorer

  Use when discovering, locating, or inspecting ATLAS datasets: finding dataset containers by physics process or AMI tag, checking Rucio replica locations and availability, browsing ATLAS Open Data samples, listing branches in a ROOT file, or checking what variables are available in a DAOD. Also use w

• atlas-docs-expert

  Use when answering questions about ATLAS software internals: Athena framework, CP algorithm setup, event data model (EDM), derivation formats (DAOD), ASG tools, CMake/ATLAS build system, CVMFS setup, analysis releases, or any topic covered by the ATLAS software documentation at atlas-software.docs.c

• atlas-stats-expert

  Use when designing or implementing an ATLAS statistical analysis: choosing between pyhf, cabinetry, HistFitter, TRExFitter, or RooUnfold, building a HistFactory workspace, defining nuisance parameters and systematics, running a profile likelihood fit, computing CLs exclusion limits, setting up an un

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