---
title: "Other Agent Plugins, page 39 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/39
last-updated: 2026-10-03
---

# Other Agent Plugins, page 39 of 45

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

| Name | Description | Repo |
| --- | --- | --- |
| [epigeneticist](https://agentpluginsdirectory.com/plugins/epigeneticist) | Reasons from chromatin state, DNA methylation, histone marks, accessibility, and 3D genome topology through ChIP/CUT&RUN, ATAC-seq, WGBS/EM-seq, Hi-C, and dCas9-DNMT3A/KRAB perturbation while treating cell-composition shifts, batch confounding, antibody nonspecificity, Tn5 bias, and incomplete bisulfite conversion as first-class failure modes. | K-Dense-AI/scientific-agents |
| [ethologist](https://agentpluginsdirectory.com/plugins/ethologist) | Reasons from Tinbergen's four questions and versioned species vs experimental ethograms; scores with BORIS (Cohen's κ per behavior), Altmann focal/scan budgets, and ARRIVE 2.0/study-plan lab reporting while treating observer expectation, field, lab arena mismatch, habituation, and pseudoreplication as first-class failure modes. | K-Dense-AI/scientific-agents |
| [evolutionary-biologist](https://agentpluginsdirectory.com/plugins/evolutionary-biologist) | Reasons from coalescent demography, MSC gene-tree discordance, and selection, drift nulls; runs IQ-TREE/BEAST/ASTRAL/ANGSD workflows while treating LBA, rogue taxa, batch effects, and uncorrected genome scans as first-class failure modes. | K-Dense-AI/scientific-agents |
| [exercise-physiologist](https://agentpluginsdirectory.com/plugins/exercise-physiologist) | Reason from the Fick principle and verified gas exchange: separate VO2max, VT1/RCP, MLSS, and lactate kinetics before metabolic carts, biopsy, MRS, or periodization prescriptions. | K-Dense-AI/scientific-agents |
| [exoplanet-scientist](https://agentpluginsdirectory.com/plugins/exoplanet-scientist) | Reasons from Keplerian motion, transit and RV geometry, and degenerate retrieval spaces through TLS/BLS searches, centroid and odd-even vetting, RadVel and GP activity models, and petitRADTRANS retrievals while treating eclipsing-binary blends, stellar-rotation-mimicking RV signals, and look-elsewhere completeness cliffs as first-class failure modes. | K-Dense-AI/scientific-agents |
| [experimental-physicist](https://agentpluginsdirectory.com/plugins/experimental-physicist) | Reasons from GUM error budgets, traceable calibration chains, and multiplied signal-chain transfer functions, separating Type A and Type B uncertainty, null runs, and ELN-linked reproducibility before precision or discovery claims. | K-Dense-AI/scientific-agents |
| [extremophile-biologist](https://agentpluginsdirectory.com/plugins/extremophile-biologist) | Reason from physicochemical limits, T, pH, salinity, pressure, and redox, as filters on membrane chemistry, osmoadaptation, chaperones, and cultivation fidelity before astrobiology or extremozyme claims. | K-Dense-AI/scientific-agents |
| [fermentation-scientist](https://agentpluginsdirectory.com/plugins/fermentation-scientist) | Reasons from Monod, Luedeking, Piret kinetics, overflow μcrit, OTR/RQ/RAMOS analytics, DoE media optimization, and 13C-MFA/COBRApy flux bounds while treating stuck-ferment ethanol×T synergy, SSF heat/moisture gradients, and OD-as-biomass red herrings as first-class failure modes. | K-Dense-AI/scientific-agents |
| [finite-element-analyst](https://agentpluginsdirectory.com/plugins/finite-element-analyst) | Reasons from discretization error, element technology, and constraint physics; runs mesh convergence and Richardson studies, Nastran/Abaqus/ANSYS workflows, RBE2/RBE3 and contact discipline, and ASME V&V 10 verification-before-validation reporting on governing QoIs. | K-Dense-AI/scientific-agents |
| [fire-protection-engineer](https://agentpluginsdirectory.com/plugins/fire-protection-engineer) | Reasons from NFPA 13 Hazen-Williams hydraulics (K-factor, remote area, hose stream) and NFPA 101 egress (occupant load, travel distance, capacity factors) through NFPA 92 smoke containment/management, ASET/RSET PBD, and FDS/CFAST/CONTAM/PyroSim modeling while treating breached compartmentation, C-factor/fitting errors, and supply-curve shortfall as first-class failure modes. | K-Dense-AI/scientific-agents |
| [fisheries-scientist](https://agentpluginsdirectory.com/plugins/fisheries-scientist) | Reasons from recruitment, growth, and natural and fishing mortality through state-space assessment models (SS3, SAM, JABBA), CPUE/GLM standardization, and reference points like F_MSY and B_lim under ICES and Magnuson-Stevens frameworks, while treating hyperstability, retrospective bias (Mohn's rho), unaccounted discard mortality, and misspecified M or selectivity as first-class failure modes. | K-Dense-AI/scientific-agents |
| [flavor-fragrance-chemist](https://agentpluginsdirectory.com/plugins/flavor-fragrance-chemist) | Reasons from odor activity values, threshold perception, matrix release, and degradation kinetics through GC-MS with retention indices, GC-O/AEDA, chiral GC authentication, ISO 8586 trained sensory panels, and IFRA/FEMA regulatory limits while treating aldehyde oxidation, citral cyclization, top-note fade, and allergen exceedance as first-class failure modes. | K-Dense-AI/scientific-agents |
| [fluid-dynamicist](https://agentpluginsdirectory.com/plugins/fluid-dynamicist) | Reasons from Navier: Stokes and dimensionless scaling through RANS/LES/DNS selection, mesh/y+ strategy, OpenFOAM/Fluent workflows, and MMS + ASME V&V 20 / PIV validation. | K-Dense-AI/scientific-agents |
| [fluid-mechanics-engineer](https://agentpluginsdirectory.com/plugins/fluid-mechanics-engineer) | Reasons from Navier, Stokes reductions through Darcy, Weisbach/Crane TP-410 pipe networks, pump system curves, NPSH/affinity laws, HI turbomachinery selection, and ASME V&V 20 CFD validation when simulation supports design. | K-Dense-AI/scientific-agents |
| [food-chemist](https://agentpluginsdirectory.com/plugins/food-chemist) | Reasons from food matrix effects, aw and lipid oxidation, AOAC-validated HPLC/GC-MS/LC-MS/MS, FoodData Central/FNDDS, and trained sensory panels while treating matrix suppression, accelerated-shelf-life misuse, and untrained-taster data as first-class failure modes. | K-Dense-AI/scientific-agents |
| [food-engineer](https://agentpluginsdirectory.com/plugins/food-engineer) | Reasons from water activity, thermal microbiology, transport-coupled reaction, and rheology through heat-penetration studies, F0/D/z lethality integration, HACCP with prerequisite programs, and CFR Title 21 LACF/acidified-food rules while treating cold-point under-processing, aw and pH drift, post-process contamination, and unvalidated scale-up as first-class failure modes. | K-Dense-AI/scientific-agents |
| [food-microbiologist](https://agentpluginsdirectory.com/plugins/food-microbiologist) | Reasons from food as a hurdle-governed matrix of water activity, pH, and redox through BAM/ISO reference methods, c/n/m/M sampling plans, PMA-v-qPCR, and ComBase kinetics while treating VBNC and injured cells, post-process contamination, matrix inhibition, and unconfirmed PCR hits as first-class failure modes. | K-Dense-AI/scientific-agents |
| [food-scientist](https://agentpluginsdirectory.com/plugins/food-scientist) | Reasons from a_w and GAB isotherms, Maillard/acrylamide kinetics, HLB emulsions, TPA/rheology, ISO sensory methods, and HACCP/FSMA preventive controls while treating aw, moisture conflation, HLB-only emulsion fixes, and Arrhenius misuse as first-class failure modes. | K-Dense-AI/scientific-agents |
| [forensic-chemist](https://agentpluginsdirectory.com/plugins/forensic-chemist) | Reasons from chain of custody, validated methods, measurement uncertainty, and class-versus-individual characteristics through GC-MS, LC-MS/MS, FTIR, and SWGDRUG-aligned identification under ISO/IEC 17025, while treating carryover contamination, secondary transfer, isomer co-elution, and upgrading equivocal results into source attribution as first-class failure modes. | K-Dense-AI/scientific-agents |
| [forestry-scientist](https://agentpluginsdirectory.com/plugins/forestry-scientist) | Reasons from silvicultural systems, site index, DGH and DBH increment, and FIA cruise design through FVS/ORGANON calibration, LiDAR area-based inventory with support matching, and IPCC carbon pools while treating site-index misassignment, plot edge effects, and change-of-spatial-support bias as first-class failure modes. | K-Dense-AI/scientific-agents |
| [formal-methods-researcher](https://agentpluginsdirectory.com/plugins/formal-methods-researcher) | Reasons from operational semantics and temporal logics through SPIN/TLA+/PRISM, Coq/Lean/Isabelle, Z3/CVC5, refinement and separation logic, vacuity and false-positive diagnosis, and Dafny/F* versus property-based testing boundaries. | K-Dense-AI/scientific-agents |
| [foundation-engineer](https://agentpluginsdirectory.com/plugins/foundation-engineer) | Reasons from effective stress, ULS versus SLS limit states, and construction-altered soil behavior through CPT/SPT logging, triaxial and oedometer testing, LRFD φ-factor checks, and LPILE/PLAXIS analysis while treating liquefaction-driven lateral spread, negative skin friction downdrag, differential settlement, and scour as first-class failure modes. | K-Dense-AI/scientific-agents |
| [fpga-engineer](https://agentpluginsdirectory.com/plugins/fpga-engineer) | Reasons from metastability budgets, setup/hold margins, and tool-reported WNS/TNS through Vivado/Quartus timing and CDC reports, XDC/SDC constraints, Spyglass/Verilator lint, and ILA/IBERT lab bring-up while treating unsafe clock-domain crossings, reset domain crossings, sim-versus-silicon X mismatches, and unconstrained timing paths as first-class failure modes. | K-Dense-AI/scientific-agents |
| [functional-genomics-scientist](https://agentpluginsdirectory.com/plugins/functional-genomics-scientist) | Reasons from perturbation as causal probe, genotype-to-phenotype linkage, library representation, and effect-size-plus-FDR statistics through MAGeCK/BAGEL/CERES-Chronos, CRISPRcleanR, CRISPResso2, MPRAnalyze, and Perturb-seq pipelines while treating MOI/bottleneck artifacts, copy-number and p53/DSB toxicity, RNAi seed effects, and guide-assignment or gating errors as first-class failure modes. | K-Dense-AI/scientific-agents |
| [fusion-scientist](https://agentpluginsdirectory.com/plugins/fusion-scientist) | Reasons from Lawson triple product and Q through tokamak/stellarator confinement (H-mode, ELMs, RMP), NBI/ICRH/ECRH heating, EFIT/TRANSP/SOLPS-ITER workflows, ITER/JET/DIII-D/W7-X benchmarks, PMI (W/Be PFCs), and tritium breeding blankets. | K-Dense-AI/scientific-agents |
| [galactic-astronomer](https://agentpluginsdirectory.com/plugins/galactic-astronomer) | Reasons from distance ladders, dust extinction, and survey selection functions through Gaia DR3 cross-matches, isochrone and Bayesian SFH fitting (PARSEC/MIST, Starfish), and orbit integration in named potentials (McMillan17, MWPotential2015) via galpy, Agama, and Gala, while treating parallax-S/N and RUWE failures, unresolved binaries and fiber collisions, dust-or-crowding overdensities, and spiral-arm-mimicking-streams as first-class failure modes. | K-Dense-AI/scientific-agents |
| [gene-therapy-scientist](https://agentpluginsdirectory.com/plugins/gene-therapy-scientist) | Reasons from vector biology, biodistribution, linked potency, and integration risk through ddPCR titer, empty/full analytics, ISA and off-target NGS (GUIDE-seq, CIRCLE-seq), and ICH S12 nonclinical design while treating pre-existing capsid neutralizing antibodies, RCV/RCA/RCR positivity, gonadal vector genome, and oligoclonal VCN expansion as first-class failure modes. | K-Dense-AI/scientific-agents |
| [genetic-counselor](https://agentpluginsdirectory.com/plugins/genetic-counselor) | Reasons from probabilistic penetrance, Bayesian pretest probability, and patient autonomy through three-generation pedigrees, ACMG/AMP variant criteria, ClinVar/ClinGen/gnomAD, NCCN and CPIC guidelines, and cascade-testing protocols while treating VUS over-upgraded to pathogenic, screening-versus-diagnostic confusion (NIPT vs amnio/CVS), and unaddressed psychosocial and GINA discrimination risk as first-class failure modes. | K-Dense-AI/scientific-agents |
| [geneticist](https://agentpluginsdirectory.com/plugins/geneticist) | Reasons from particulate inheritance, segregation, recombination, allele frequency, and genotype-phenotype evidence through ACMG/AMP-ClinGen classification, gnomAD/ClinVar/OMIM, HPO phenotyping, and PLINK/GATK/VEP QC while treating sample swaps, cryptic relatedness, population stratification, LD tagging, phenocopies, winner's curse, and build/transcript mismatch as first-class failure modes. | K-Dense-AI/scientific-agents |
| [genome-engineering-crispr-scientist](https://agentpluginsdirectory.com/plugins/genome-engineering-crispr-scientist) | Reasons from NHEJ/HDR/MMEJ competition and editor modality choice through CRISPick/CRISPResso2 guide design, LOCK/lssDNA and RNP HDR, base and prime editing (PE4/PE5, epegRNA), CAST-Seq/UDiTaS on-target SV assessment, clonal genotyping, and FDA/IBC-bound off-target and genome-integrity analytics. | K-Dense-AI/scientific-agents |
| [genomicist](https://agentpluginsdirectory.com/plugins/genomicist) | Reasons from reference-relative coordinates, haplotypes, variant classes, and sequencing-as-measurement through GATK/DeepVariant, VEP/ClinVar/gnomAD, GIAB/hap.py benchmarking, and ACMG/AMP-ClinGen frameworks while treating build mismatches, paralog/pseudogene and GC dropout artifacts, contamination and index hopping, batch effects, and annotation drift as first-class failure modes. | K-Dense-AI/scientific-agents |
| [geobiologist](https://agentpluginsdirectory.com/plugins/geobiologist) | Reasons from metabolism, redox geochemistry, microbe-mineral interactions, and diagenetic filters through stromatolite microfabric petrography, CSIA and clumped-isotopologue analysis, nanoSIMS-FISH mapping, and NASA's Ladder of Life Detection while treating Fischer-Tropsch-type synthesis, serpentinization, Rayleigh distillation, drilling-fluid contamination, and epigenetic overprint as first-class failure modes. | K-Dense-AI/scientific-agents |
| [geochemist](https://agentpluginsdirectory.com/plugins/geochemist) | Reasons from Gibbs equilibria, mass and isotope balance, and fluid, rock interaction through stable (δ) and radiogenic (ε, isochron) systems, ICP-MS/LA-ICP-MS/TIMS/MC-ICP-MS/IRMS, PHREEQC/Perple_X phase modeling, and EarthChem/GeoReM workflows while treating alteration, matrix effects, Pb loss, mixing arrays, and Fretwell's Law violations as first-class failure modes. | K-Dense-AI/scientific-agents |
| [geodesist](https://agentpluginsdirectory.com/plugins/geodesist) | Reasons from coordinates as four-dimensional objects with epoch, velocity, and frame realization (ITRS vs. ITRF2020, WGS84) through GAMIT/GLOBK and Bernese PPP-AR, SBAS/PS-InSAR with GACOS atmospheric correction, IERS Conventions, and 14-parameter Helmert transforms while treating ITRF-realization switches, undocumented APC/ATX mismatches, monument motion, and unscreened seasonal loading as first-class failure modes. | K-Dense-AI/scientific-agents |
| [geodynamics-tectonics-scientist](https://agentpluginsdirectory.com/plugins/geodynamics-tectonics-scientist) | Reasons from plate kinematics, lithospheric rheology, and interseismic-versus-coseismic strain partitioning through GAMIT/GLOBK and MintPy geodesy, Okada/viscoelastic slip inversion, OxCal paleoseismic chronologies, ASPECT mantle modeling, and OpenQuake/USGS NSHM hazard while treating InSAR atmospheric delay, monument instability, unmodeled postseismic afterslip, and incompatible-timescale rate stacking as first-class failure modes. | K-Dense-AI/scientific-agents |
| [geographic-information-scientist-gis](https://agentpluginsdirectory.com/plugins/geographic-information-scientist-gis) | Reasons from location, topology, scale, and positional uncertainty through PostGIS/GDAL pipelines, explicit EPSG/datum choices, kriging with cross-validated variograms, and ISO 19115/FGDC metadata while treating MAUP and ecological fallacy, Web Mercator area statistics, floating-point slivers and broken topology, and spatial-autocorrelation-inflated significance as first-class failure modes. | K-Dense-AI/scientific-agents |
| [geological-oceanographer](https://agentpluginsdirectory.com/plugins/geological-oceanographer) | Reasons from sediment transport mechanics, stratigraphic context, and accommodation through multibeam (EM122/EM712) and sub-bottom/seismic imaging, gravity and piston cores with XRF/X-ray CT, CTD tow-yo ORP/Mn/CH4 plume surveys, and Bouma/Lowe facies analysis, while treating bathymetry-mimicking multipath artifacts, bioturbation homogenizing event beds, glacial isostasy mistaken for eustasy, and single-core turbidite extrapolation as first-class failure modes. | K-Dense-AI/scientific-agents |
| [geologist](https://agentpluginsdirectory.com/plugins/geologist) | Reasons from Steno's principles and Walther's Law through Brunton strike/dip, measured sections, hand-lens rock ID (QAPF/Folk/Dunham), thin-section petrography (PPL/XPL, Michel-Lévy, point counting), FGDC/GeMS geologic maps, NGMDB/Geolex/Macrostrat, and stereonet structural analysis while treating weathering, float, and map-as-hypothesis as first-class failure modes. | K-Dense-AI/scientific-agents |
| [geomagnetist](https://agentpluginsdirectory.com/plugins/geomagnetist) | Reasons from spherical-harmonic main-field theory and remanence physics through IGRF-14/WMM2025 vs CHAOS-8 SV, INTERMAGNET baseline adoption (IBFV2.00), Swarm quiet-time modeling, stepwise AF/thermal demagnetization with PCA/Fisher, GEOMAGIA50/MagIC archaeomagnetic SVCs, and GFZ Kp/ap indices while treating geomagnetic jerks, IGRF epoch mismatch, VRM/CRM overprints, and Day-diagram mixed-carrier traps as first-class failure modes. | K-Dense-AI/scientific-agents |
| [geomorphologist](https://agentpluginsdirectory.com/plugins/geomorphologist) | Reasons from coupled form, process, and time and from rates, thresholds, and lag times through field mapping, lidar/SfM DEM morphometry (chi profiles, Ksn in LSDTopoTools/Landlab), cosmogenic nuclide dating (CRONUS-Earth, OSL, U-Th), and landscape-evolution models, while treating equifinality, inheritance, DEM artifacts, and steady-state assumed over transient response as first-class failure modes. | K-Dense-AI/scientific-agents |
| [geophysicist](https://agentpluginsdirectory.com/plugins/geophysicist) | Reasons from wavelength and skin-depth limits through earthquake catalogs (USGS ComCat, ObsPy/FDSN), Bouguer/IGRF gravity-magnetics, MT distortion and dimensionality, and SEG-Y reflection processing (NMO, migration) while treating statics, galvanic distortion, velocity ambiguity, and header mis-mapping as first-class failure modes. | K-Dense-AI/scientific-agents |
| [geotechnical-engineer](https://agentpluginsdirectory.com/plugins/geotechnical-engineer) | Reasons from effective stress and LRFD/EC7 limit states through GDR/GBR/FDR deliverables, shallow and deep foundations (GEC 6/10/12), excavation support (DeepEX, LPILE), ground improvement, ASCE 7 liquefaction, observational-method triggers, and FHWA pile acceptance while treating DSC claims, setup vs. blow count, and GBR-vs-design conflation as first-class failure modes. | K-Dense-AI/scientific-agents |
| [geotechnical-scientist](https://agentpluginsdirectory.com/plugins/geotechnical-scientist) | Reasons from Terzaghi effective stress, Mohr: Coulomb/CSSM, and consolidation/seepage through SPT/CPTU (Robertson SBT), triaxial/oedometer (ASTM D-series), Boulanger, Idriss liquefaction, Hoek, Brown/GSI rock mass, EC7 characteristic values, and PLAXIS/Slide2/RS2/GeoStudio workflows while treating sample disturbance, N-value correction chains, spatial variability, and LEM-vs-FEM mismatch as first-class failure modes. | K-Dense-AI/scientific-agents |
| [gerontologist](https://agentpluginsdirectory.com/plugins/gerontologist) | Reasons from senescence hallmarks, frailty, multi-morbidity, and life-course exposures through validated instruments (Fried phenotype, Rockwood CFS, SPPB/gait speed), epigenetic clocks (Horvath, PhenoAge, GrimAge), competing-risk survival (Fine-Gray), and NIA cohorts (HRS, NHATS, ITP) while treating survivor bias, differential attrition, healthy-volunteer bias, and frail-subset toxicity as first-class failure modes. | K-Dense-AI/scientific-agents |
| [glaciologist](https://agentpluginsdirectory.com/plugins/glaciologist) | Reasons from mass-budget closure (SMB, dynamic discharge, calving), Glen flow law, and subglacial effective pressure through WGMS/GlaMBIE stake networks, ICESat-2/CryoSat altimetry with firn and radar-penetration corrections, ITS_LIVE velocities, ApRES basal melt, RES/MCoRDS bed picks, RGI/BedMachine inventories, OGGM mountain-glacier projections, and PISM/ISSM ISMIP6/7 protocols while treating firn-compaction aliasing, DEM penetration bias, GRACE leakage/GIA, and tidal InSAR artifacts as first-class failure modes. | K-Dense-AI/scientific-agents |
| [global-health-researcher](https://agentpluginsdirectory.com/plugins/global-health-researcher) | Reasons from burden, equity, and health-system building blocks through DHS/MICS/DHIS2/GBD triangulation, cluster and stepped-wedge designs, RE-AIM/CFIR implementation science, and CIOMS-fair partnership while treating survey weights, HMIS completeness, and GBD smoothing as first-class failure modes. | K-Dense-AI/scientific-agents |
| [glycobiologist](https://agentpluginsdirectory.com/plugins/glycobiologist) | Reasons from N-/O-glycan biosynthesis, O-GlcNAc cycling (OGT/OGA), LC-MS glycomics, exoglycosidase sequencing, and lectin microarrays; uses GlyTouCan/SNFG/MIRAGE, pGlyco/GlycoWorkbench, and treats PNGase F limits, isomer collapse, and ER-stress high-mannose as first-class failure modes. | K-Dense-AI/scientific-agents |
| [gravitational-physicist](https://agentpluginsdirectory.com/plugins/gravitational-physicist) | Reasons from calibrated strain, colored non-stationary noise PSDs, matched-filter SNR, and Bayesian posteriors through PyCBC/GstLAL/cWB searches, Bilby/LALInference PE with NRSur/SEOBNR/IMRPhenom waveforms, and FAR/p_astro significance while treating glitch contamination, waveform-approximant mismatch, mass-spin and distance-inclination degeneracies, and unmodeled selection effects as first-class failure modes. | K-Dense-AI/scientific-agents |