---
title: "Other Agent Plugins, page 42 of 45"
description: "Plugins whose purpose does not fit any category above, and plugins whose manifest describes too little to classify honestly."
canonical: https://agentpluginsdirectory.com/categories/other/page/42
last-updated: 2026-10-03
---

# Other Agent Plugins, page 42 of 45

Plugins whose purpose does not fit any category above, and plugins whose manifest describes too little to classify honestly.

| Name | Description | Repo |
| --- | --- | --- |
| [neurologist](https://agentpluginsdirectory.com/plugins/neurologist) | Reasons from anatomic localization, time course, and phenomenology through NIHSS/ASPECTS stroke triage, ILAE 2025 seizure classification, McDonald 2017 and AQP4/MOG cell-based assays, EEG and EMG/NCS, and SNOOP4 red flags, while treating CT-negative early ischemia, ~50%-sensitive routine EEG, MS-versus-NMOSD/MOGAD misdiagnosis, and missed myasthenic-crisis respiratory decline as first-class failure modes. | K-Dense-AI/scientific-agents |
| [neuropharmacologist](https://agentpluginsdirectory.com/plugins/neuropharmacologist) | Reasons from Kp,uu,brain and receptor occupancy, radioligand binding with depletion-aware Ki, biased GPCR/allosteric signaling, PDSP/GtoPdb panels, microdialysis and PET RO, and operant self-administration while treating Cheng-Prusoff error, P-gp efflux, FST validity limits, and patch-clamp Rs artifacts as first-class failure modes. | K-Dense-AI/scientific-agents |
| [neurophysiologist](https://agentpluginsdirectory.com/plugins/neurophysiologist) | Reasons from membrane biophysics, patch clamp Rs/seal quality, Neuropixels AP/LF streams, LFP referencing and spike contamination, Kilosort4/Phy curation, and stimulation-artifact suppression. | K-Dense-AI/scientific-agents |
| [neuroscientist](https://agentpluginsdirectory.com/plugins/neuroscientist) | Reasons from levels of explanation, nested loops, and timescale-matched methods, separating necessary/sufficient/correlated and mapping cell types before regions (Allen CCF, BICCN, PV vs SOM) through Neuropixels and GCaMP calcium imaging, patch-clamp EPSCs, optogenetics and DREADD chemogenetics, fiber photometry, fMRI/EEG/DTI, mixed models for nested n, and BIDS/NWB/ARRIVE 2.0 reporting while treating developmental compensation, reverse inference from BOLD, preparation mismatch (culture to in vivo), pseudoreplication of neurons/trials/voxels, and hidden state-variable confounds as first-class failure modes. | K-Dense-AI/scientific-agents |
| [nonlinear-dynamics-chaos-scientist](https://agentpluginsdirectory.com/plugins/nonlinear-dynamics-chaos-scientist) | Reasons from flows, maps, bifurcations, and invariant sets; continues with MatCont/AUTO/COCO, validates chaos with IAAFT surrogates and embedding convergence, and treats spurious Lyapunov exponents, stiff integrator artifacts, and colored-noise confounds as first-class failure modes. | K-Dense-AI/scientific-agents |
| [nuclear-chemist](https://agentpluginsdirectory.com/plugins/nuclear-chemist) | Reasons from decay-corrected activity ledgers, decay modes and cross sections, and ALARA dose control through Bateman/ORIGEN modeling, extraction-chromatography separations (TRU/Sr/TEVA resins), and HPGe/alpha/LSC spectroscopy while treating daughter ingrowth, generator breakthrough, spectral pile-up and sum peaks, and swipe-test cross-contamination as first-class failure modes. | K-Dense-AI/scientific-agents |
| [nuclear-engineer](https://agentpluginsdirectory.com/plugins/nuclear-engineer) | Reasons from k_eff, DNBR/CHF margins, xenon transients, and defense-in-depth; couples SCALE/MCNP, PARCS, TRACE/RELAP, and MELCOR to 10 CFR and PRA; treats nodalization, nuclear-data, and CHF-correlation uncertainties as first-class failure modes. | K-Dense-AI/scientific-agents |
| [nuclear-medicine-scientist](https://agentpluginsdirectory.com/plugins/nuclear-medicine-scientist) | Reasons from radioactive decay, biodistribution kinetics, and detector physics through HPLC/TLC radiochemical-purity QC, dose-calibrator cross-calibration, OSEM/PSF reconstruction, and MIRD/OLINDA dosimetry while treating partial-volume effects, attenuation mismatch, 68Ge breakthrough and other radionuclidic impurity, and unharmonized cross-center SUV as first-class failure modes. | K-Dense-AI/scientific-agents |
| [nuclear-physicist](https://agentpluginsdirectory.com/plugins/nuclear-physicist) | Reasons from shell and collective structure, reaction mechanisms, and ENDF/EXFOR data; matches FRIB, CEBAF, RHIC science to R-matrix, Hauser-Feshbach, chiral ab initio, and GEANT4 tools; treats dead time, normalization, and evaluation covariances as first-class failure modes. | K-Dense-AI/scientific-agents |
| [number-theorist](https://agentpluginsdirectory.com/plugins/number-theorist) | Reasons from primes, congruences, L-functions, and the Langlands web; chooses algebraic, analytic, and sieve methods; validates with SageMath/PARI/LMFDB while treating PARI stack overflows, conditional-proof leaks, and CRT moduli errors as first-class failure modes. | K-Dense-AI/scientific-agents |
| [numerical-analyst](https://agentpluginsdirectory.com/plugins/numerical-analyst) | Reasons from well-posedness, discretization, conditioning, and stability; verifies codes with MMS and convergence studies; treats cancellation, stiffness, and solver tolerance floors as first-class failure modes. | K-Dense-AI/scientific-agents |
| [nutrition-scientist](https://agentpluginsdirectory.com/plugins/nutrition-scientist) | Reasons from intake measurement error, energy balance, and causal triangulation through doubly-labeled-water validation, NCI usual-intake models, DRI (EAR/RDA/UL) frameworks, crossover feeding trials, and Mendelian randomization while treating dietary underreporting, reverse causation (sick-quitter), unadjusted total-energy confounding, and weight-loss-versus-macronutrient attribution as first-class failure modes. | K-Dense-AI/scientific-agents |
| [observational-astronomer](https://agentpluginsdirectory.com/plugins/observational-astronomer) | Reasons from the CCD signal-to-noise equation, sky- versus read-noise-limited scaling, airmass extinction and seeing laws, and a CALSPEC-anchored calibration chain through ETC-backed proposals, ccdproc/PypeIt/DRAGONS and CRDS-pinned JWST reductions, optimal extraction with telluric correction, Gaia-anchored astrometry, ZOGY difference imaging, and Rubin broker-to-TOM-to-TNS follow-up while treating IR persistence and reciprocity failure, fringing and shutter-timing errors, differential-refraction slit losses, difference-image dipoles, and red-noise-inflated light curves as first-class failure modes. | K-Dense-AI/scientific-agents |
| [occupational-health-scientist](https://agentpluginsdirectory.com/plugins/occupational-health-scientist) | Reasons from exposure route and receptor, dose-response, and the hierarchy of controls through SEG-based personal sampling, NIOSH/OSHA analytical methods, AIHA Bayesian exceedance statistics, and SMR cohort analysis, while treating healthy worker effect, below-LOD censoring, fraction-size and OEL mismatch, and JEM misclassification as first-class failure modes. | K-Dense-AI/scientific-agents |
| [oceanographer](https://agentpluginsdirectory.com/plugins/oceanographer) | Reasons from basin-scale budgets, three-dimensional circulation, and forcing-transport-transformation coupling through θ, S and OMP water-mass analysis, transient-tracer ventilation ages (CFC/SF₆/¹⁴C), GO-SHIP/Argo/SOCAT networks, and TEOS-10 thermodynamics while treating mesoscale aliasing of single sections, mixed real-time and delayed-mode QC, and freshwater-driven salinity confounds as first-class failure modes. | K-Dense-AI/scientific-agents |
| [oncologist](https://agentpluginsdirectory.com/plugins/oncologist) | Stages with AJCC TNM and molecular prognostic groups, selects biomarker-matched therapy from NCCN guidelines, assesses response with RECIST 1.1/iRECIST, and interprets trial endpoints with calibrated clinical judgment. | K-Dense-AI/scientific-agents |
| [operations-researcher](https://agentpluginsdirectory.com/plugins/operations-researcher) | Reasons from decision structure, integrality and convexity, and explicit uncertainty through LP/MIP solvers (Gurobi, CPLEX, OR-Tools CP-SAT), stochastic and Wasserstein-distributionally-robust formulations, and DES (SimPy, AnyLogic) benchmarked on Solomon/MIPLIB instances, while treating unit inconsistencies, optimality-gap-versus-stale-data trade-offs, infeasibility (IIS) from forgotten labor and fairness constraints, and day-to-day solution oscillation as first-class failure modes. | K-Dense-AI/scientific-agents |
| [ophthalmologist](https://agentpluginsdirectory.com/plugins/ophthalmologist) | Reasons from structure: function pairing (OCT RNFL/CST, HVF MD/VFI, ETDRS BCVA); manages glaucoma IOP targets and anti-VEGF treat-and-extend while treating field learning effect, OCT floor effect, and 15-letter regulatory margins as first-class failure modes. | K-Dense-AI/scientific-agents |
| [optical-physicist](https://agentpluginsdirectory.com/plugins/optical-physicist) | Reasons from square-law detection and Fourier duality, Gaussian-beam and coherence theory, Jones/Mueller polarization, and dispersion and χ⁽²⁾/χ⁽³⁾ phase matching through FROG/SPIDER/d-scan retrieval, phase-shifting and absolute interferometry, Zemax/CODE V/Optiland modeling, SNLO, FTIR/Raman/ellipsometry, and ISO 10110/11146/21254 reporting while treating parasitic etalons, coherent artifacts of unstable pulse trains, thermal lensing mistaken for Kerr nonlinearity, Zernike-convention and retrace errors, and FFT-propagation aliasing as first-class failure modes. | K-Dense-AI/scientific-agents |
| [optimization-scientist](https://agentpluginsdirectory.com/plugins/optimization-scientist) | Reasons from convexity class, KKT/complementarity, and LP/MIP relaxation gaps through interior-point and branch-and-cut (Gurobi, CPLEX, MOSEK, Ipopt) while treating loose big-M, IntegralityTol cheaters, IIS-hidden infeasibility, nonconvex KKT-as-global, and MIPGap-at-TimeLimit-as-optimal as first-class failure modes. | K-Dense-AI/scientific-agents |
| [optoelectronics-engineer](https://agentpluginsdirectory.com/plugins/optoelectronics-engineer) | Reasons from photon: electron conversion, ABC recombination, and IQE/EQE/WPE budgets; runs LIV/pulsed laser, EMVA 1288, and responsivity metrology; designs with Lumerical/Sentaurus/COMSOL TCAD and foundry PDKs while treating efficiency droop, thermal rollover, LIV kinks, and calibration geometry as first-class failure modes. | K-Dense-AI/scientific-agents |
| [oral-biologist](https://agentpluginsdirectory.com/plugins/oral-biologist) | Reasons from biofilm dysbiosis, demineralization-remineralization balance, and host-mineral-microbe partitioning through pH-cycling and ligature models, 16S/shotgun metagenomics (DADA2/QIIME2, HOMD), micro-CT, and ICDAS/AAP-EFP staging, while treating saliva-ignored caries models, low-biomass contamination, probe-force inconsistency, and unconfounded oral-systemic claims as first-class failure modes. | K-Dense-AI/scientific-agents |
| [organic-chemist](https://agentpluginsdirectory.com/plugins/organic-chemist) | Reasons from retrosynthesis, protecting-group strategy, and stereoelectronics; executes air-sensitive chemistry, flash/LC-MS purification, and NMR/IR/MS proof; mines SciFinder/Reaxys and reports ACS-grade experimentals with E-factor/PMI and pyrophoric safety discipline. | K-Dense-AI/scientific-agents |
| [organoid-biologist](https://agentpluginsdirectory.com/plugins/organoid-biologist) | Reasons from niche signaling, Matrigel scaffolds, and culture geometry; engineers Wnt/R-spondin expansion, ALI differentiation, and PDO biobanks while treating matrix lot effects and donor-level pseudoreplication as first-class failure modes. | K-Dense-AI/scientific-agents |
| [organometallic-chemist](https://agentpluginsdirectory.com/plugins/organometallic-chemist) | Reasons from electron counting, oxidation states, and elementary catalytic steps through Schlenk/glovebox technique, multinuclear NMR and νCO IR, SCXRD with checkCIF, and TON/TOF kinetics while treating air oxidation to oxo/hydroxo species, paramagnetic line-broadening, and trace or colloidal-metal leaching as first-class failure modes. | K-Dense-AI/scientific-agents |
| [ornithologist](https://agentpluginsdirectory.com/plugins/ornithologist) | Reasons from detectability-limited surveys through BBS/MAPS protocols, distance sampling and unmarked occupancy, eBird/auk hygiene, BirdNET, Raven validation, BBL permitting, Pyle molt scoring, MOTUS/FlightR connectivity, and AviList/Clements taxonomy while treating roadside bias, space-for-time pseudo-replicates, and AI false positives as first-class failure modes. | K-Dense-AI/scientific-agents |
| [orthopedic-biomechanist](https://agentpluginsdirectory.com/plugins/orthopedic-biomechanist) | Reasons from joint kinematics, forces, moments, and tissue stress through optical motion capture with force plates, inverse dynamics with de Leva segment parameters, OpenSim/AnyBody and FEBio/Abaqus models, and ISO 14243 wear testing while treating skin motion artifact, cardan gimbal lock, unnormalized moments, and over-read FEA stress hotspots as first-class failure modes. | K-Dense-AI/scientific-agents |
| [paleobotanist](https://agentpluginsdirectory.com/plugins/paleobotanist) | Reasons from phytotaphonomy and preservation mode (compression, permineralization, palynomorphs); prepares coal-ball peels and cuticle/maceral workflows; applies LMA/CLAMP/DiLP and stomatal/Franks CO₂ proxies; uses PBDB, Neotoma, IFPNI/PFNR, and ICN fossil-taxon nomenclature while treating transport bias, organographic filters, and laboratory acid loss as first-class failure modes. | K-Dense-AI/scientific-agents |
| [paleoceanographer](https://agentpluginsdirectory.com/plugins/paleoceanographer) | Reasons from foraminiferal proxy system science (G. ruber, Cibicidoides, species/size fraction), Barker Mg/Ca cleaning and Anand/Gray calibrations, paired planktic δ¹⁸O, Mg/Ca and LR04 benthic stacks, IODP depth scales and splice ties, and AMOC fingerprints (benthic δ¹³C gradients, εNd, ²³¹Pa/²³⁰Th, sortable silt) while treating clay contamination, orbital-tuning circularity, Pa/Th scavenging, and bioturbation mixing as first-class failure modes. | K-Dense-AI/scientific-agents |
| [paleoclimatologist](https://agentpluginsdirectory.com/plugins/paleoclimatologist) | Reasons from proxy transfer functions, archive integration time, and orbital forcing through Bayesian age-depth modeling (Bacon, OxCal), IntCal20 radiocarbon calibration, PAGES2k compositing, and proxy-equivalent PMIP/DeepMIP comparison while treating age-model uncertainty, non-stationary calibration (CO2 fertilization, divergence), diagenesis, and single-site-as-global-anomaly claims as first-class failure modes. | K-Dense-AI/scientific-agents |
| [paleontologist](https://agentpluginsdirectory.com/plugins/paleontologist) | Reason from **taphonomic filters** first: biostratinomy, diagenesis, time-averaging, and Signor, Lipps before biostratigraphic correlation, morphometrics, or phylogenetic claims. | K-Dense-AI/scientific-agents |
| [palliative-care-researcher](https://agentpluginsdirectory.com/plugins/palliative-care-researcher) | Reasons from serious-illness trajectories, multidimensional symptom burden, goals-of-care concordance, and caregiver dyad outcomes through validated PROMs (ESAS-r, IPOS, FACIT-Pal), prespecified MCID responder analysis, mixed-effects and joint survival-QoL models, and CONSORT-PRO/SPIRIT/PCORI reporting while treating death-related attrition, unjustified proxy substitution, inconsistent palliative-care exposure definitions, and hospice-versus-consult conflation as first-class failure modes. | K-Dense-AI/scientific-agents |
| [parasitologist](https://agentpluginsdirectory.com/plugins/parasitologist) | Reasons from parasite life cycles, WHO NTD program logic, and diagnostic performance (Kato-Katz, qPCR/MIQE, RDTs); troubleshoots microscopy artifacts, MDA surveillance, and anthelmintic resistance. | K-Dense-AI/scientific-agents |
| [particle-physicist](https://agentpluginsdirectory.com/plugins/particle-physicist) | Reasons from SM gauge structure, parton PDFs, and detector response through ATLAS/CMS/LHCb/Belle II/DUNE workflows, Geant4+Pythia/MG5 simulation, HistFactory/Combine/pyhf likelihoods, and HEPData/Rivet preservation while treating LEE/global significance, JES/pile-up, fake leptons, and flux×cross-section systematics as first-class failure modes. | K-Dense-AI/scientific-agents |
| [pathologist](https://agentpluginsdirectory.com/plugins/pathologist) | Reasons from H&E morphology, pretest-probability differentials, and pre-analytic integrity through CAP synoptic protocols, staged IHC and FISH panels, WHO/AJCC grading and staging, and Bethesda/Paris/Milan cytology systems while treating crush artifact, fixation/decalcification failure, single-frozen-section overcall, and IHC-without-morphology as first-class failure modes. | K-Dense-AI/scientific-agents |
| [pavement-engineer](https://agentpluginsdirectory.com/plugins/pavement-engineer) | Reasons from layered-elastic stress/strain, traffic spectra, climate, and material temperature-dependence through AASHTOWare Pavement ME (MEPDG) hierarchical inputs, FWD deflection-basin backcalculation with GPR/core thickness, binder PG selection, and LTPP-calibrated transfer functions, while treating mis-specified traffic, seasonal moisture-weakened subgrade, reflective cracking, and construction segregation as first-class failure modes. | K-Dense-AI/scientific-agents |
| [pedologist](https://agentpluginsdirectory.com/plugins/pedologist) | Reasons from CLORPT factors, genetic horizons, and catenary position through the USDA Field Book, Soil Taxonomy and WRB 2022 keys, XRD clay mineralogy, micromorphology, and NASIS/SSURGO correlation while treating colluvial-versus-illuvial Bt confusion, lithologic discontinuities, surface-color-alone drainage calls, and digital-map covariate leakage as first-class failure modes. | K-Dense-AI/scientific-agents |
| [petrochemist](https://agentpluginsdirectory.com/plugins/petrochemist) | Reasons from boiling range, hydrocarbon class, sulfur/nitrogen speciation, and octane/cetane drivers through SimDist and PIONA/SARA group-type analysis, CFR-engine RON/MON and cetane testing, refinery LP models, and ASTM/EN spec methods, while treating light-ends loss, assay mismatch versus plant yields, catalyst end-of-run deactivation, and asphaltene instability as first-class failure modes. | K-Dense-AI/scientific-agents |
| [petroleum-geologist](https://agentpluginsdirectory.com/plugins/petroleum-geologist) | Reasons from petroleum-system elements (kerogen I, IV, kitchens, critical moment), trap/spill-point and SGR fault seal, AVO/DHI and inversion QC, Archie/Simandoux/NMR petrophysics with Monte Carlo STOIIP, and PetroMod 1D, 3D charge migration; treats tuning flat spots, post-trap charge, and uncorrected Archie Sw as first-class failure modes. | K-Dense-AI/scientific-agents |
| [petroleum-reservoir-engineer](https://agentpluginsdirectory.com/plugins/petroleum-reservoir-engineer) | Reasons from Darcy flow, Havlena, Odeh MBE, Fetkovich/VEH aquifers, Horner/derivative PTA, Buckley, Leverett/Welge floods, Eclipse/CMG/tNavigator history match, PRMS/SEC reserves (P90/P50/P10), and SPE11 CO₂ benchmarks; treats transient Arps b>1, negative-skin grid artifacts, and microseismic≠SRV as first-class failure modes. | K-Dense-AI/scientific-agents |
| [petrologist](https://agentpluginsdirectory.com/plugins/petrologist) | Reasons from Gibbs free energy minimization, the phase rule, and protolith-specific facies assemblages through petrography, EPMA/LA-ICP-MS microanalysis, pseudosections (Perple_X, THERMOCALC, MELTS), and classical thermobarometry while treating retrograde overprinting, serpentinization, propylitic alteration mimicking grade, and EPMA analytical scatter mistaken for P-T trends as first-class failure modes. | K-Dense-AI/scientific-agents |
| [phage-biologist](https://agentpluginsdirectory.com/plugins/phage-biologist) | Reasons from lytic vs lysogenic cycles, PFU/MOI/Poisson kinetics, one-step growth and EOP host-range matrices, PhagesDB/Phamerator/Pharokka genomics, and CRISPR/restriction escape, treating prophage immunity, defective particles, and therapy integrase scans as first-class failure modes. | K-Dense-AI/scientific-agents |
| [pharmaceutical-formulation-scientist](https://agentpluginsdirectory.com/plugins/pharmaceutical-formulation-scientist) | Anchor every decision in the QTPP and critical quality attributes (CQAs): assay, Classify the API before choosing a technology path. Use BCS (solubility vs. | K-Dense-AI/scientific-agents |
| [pharmacokineticist](https://agentpluginsdirectory.com/plugins/pharmacokineticist) | Reasons from mass balance, exposure-response, and separation of structural from statistical models through NCA in Phoenix WinNonlin, mixed-effects popPK in NONMEM, PBPK in Simcyp/GastroPlus, and VPC diagnostics while treating BLQ mishandling, ETA shrinkage, over-parameterization for small n, and unit/analyte/matrix errors as first-class failure modes. | K-Dense-AI/scientific-agents |
| [pharmacologist](https://agentpluginsdirectory.com/plugins/pharmacologist) | Reasons from receptor occupancy, Black, Leff τ, EC50/IC50/Kd/Ki distinctions, Schild/Cheng, Prusoff antagonism, allosteric PAM/NAM cooperativity, GPCR bias, and PK/PD linkage; interprets binding/functional/HTS via GtoPdb/ChEMBL while treating spare receptors, radioligand depletion, and assay autofluorescence as first-class failure modes. | K-Dense-AI/scientific-agents |
| [pharmacovigilance-scientist](https://agentpluginsdirectory.com/plugins/pharmacovigilance-scientist) | Reasons from ICSR validity, MedDRA/SMQ coding, seriousness/expectedness/listedness, WHO-UMC causality, and PRR/ROR/IC/EBGM signal workflows through E2B(R3), EudraVigilance/FAERS/VigiBase, GVP Modules VI, IX, and PSUR/PBRER/RMP while treating duplicates, MLM scope, innocent-bystander confounding, and Weber/stimulated reporting as first-class failure modes. | K-Dense-AI/scientific-agents |
| [photochemist](https://agentpluginsdirectory.com/plugins/photochemist) | Reasons from Jablonski diagrams, quantum yields, and excited-state potential energy surfaces through ferrioxalate actinometry, TCSPC and transient-absorption flash photolysis, Stern, Volmer quenching, and TDDFT/CASPT2 calculations while treating inner-filter distortion, oxygen-sensitive triplet pathways, photodegradation mistaken for reaction, and emission from impurities as first-class failure modes. | K-Dense-AI/scientific-agents |
| [photonics-engineer](https://agentpluginsdirectory.com/plugins/photonics-engineer) | Reasons from Maxwell modes, FSR: Q: coupling trade-offs, and optical power/loss budgets; designs PICs and free-space systems with FDTD/INTERCONNECT/Zemax/GDSFactory and certifies links with OLTS/OTDR/M² while treating mesh dispersion errors, TE/TM birefringence, APC/PC connector mismatch, OTDR ghost/gainer events, and Fabry, Pérot convolution artifacts as first-class failure modes. | K-Dense-AI/scientific-agents |