---
title: "Agent Plugins Directory, page 78 of 81"
description: "| Name | Description | Repo |"
canonical: https://agentpluginsdirectory.com/directory/page/78
last-updated: 2026-10-03
---

# Agent Plugins Directory, page 78 of 81

| Name | Description | Repo |
| --- | --- | --- |
| [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 |
| [photonics-scientist](https://agentpluginsdirectory.com/plugins/photonics-scientist) | Reasons from guided-wave dispersion, ring FSR, Q, coupling, and FWM phase matching; designs waveguides, lasers, and modulators with Lumerical MODE/FDTD/CHARGE/INTERCONNECT while treating dispersive FSR mismatch, TPA/FCA/XPM detuning, mesh dispersion, etalon ripples, and thermal bistability as first-class failure modes. | K-Dense-AI/scientific-agents |
| [photovoltaics-solar-cell-scientist](https://agentpluginsdirectory.com/plugins/photovoltaics-solar-cell-scientist) | Reasons from the Shockley-Queisser detailed-balance limit and the diode coupling of Voc, Jsc, FF, and Rs/Rsh through light I-V, Suns-Voc implied Voc, EQE integration, lifetime mapping (QSSPC, μ-PCD, DLTS), and IEC 60904/61215 qualification while treating spectral mismatch, surface-recombination and shunt losses, perovskite hysteresis and ion migration, and PID/LID-LeTID degradation as first-class failure modes. | K-Dense-AI/scientific-agents |
| [phylogeneticist](https://agentpluginsdirectory.com/plugins/phylogeneticist) | Reasons from Hennigian homology and MSC/coalescent-aware species trees through MAFFT/trimAl alignment, IQ-TREE 3 ModelFinder and gCF/sCF/gDF discordance, ASTRAL/ASTRAL-Pro 2/BEAST2 FBD dating, bPP/BFD* delimitation, and MIAPA/TreeBASE provenance while treating LBA, mis-rooting, compositional heterogeneity, gene flow, rogue taxa, and bootstrap-vs-posterior conflation as first-class failure modes. | K-Dense-AI/scientific-agents |
| [physical-chemist](https://agentpluginsdirectory.com/plugins/physical-chemist) | Reasons from state functions, partition functions, rate laws, and selection rules through Eyring and van't Hoff fits, DSC/ITC calorimetry, and stopped-flow spectroscopy anchored to NIST thermochemical data, while treating inner-filter and aggregation artifacts, curved Arrhenius plots from mechanism change, and concentration-for-activity substitution as first-class failure modes. | K-Dense-AI/scientific-agents |
| [physical-oceanographer](https://agentpluginsdirectory.com/plugins/physical-oceanographer) | Reasons from geostrophy, thermal wind, PV, and Ekman/Sverdrup balances; integrates GO-SHIP/CCHDO sections, Argo DMQC, DUACS/CMEMS altimetry, and ROMS/MITgcm/NEMO validation while treating reference-level transport ambiguity, Argo conductivity drift, and MDT/alias artifacts as first-class failure modes. | K-Dense-AI/scientific-agents |
| [physician-scientist](https://agentpluginsdirectory.com/plugins/physician-scientist) | Reasons across the bedside, bench cycle and T0, T4 spectrum; navigates PSTP/ABIM pathways, K08/K23/R01 funding, IRB/IND/IDE sponsor-investigator duties, and CONSORT/SPIRIT reporting while treating protected-time loss and preclinical irreproducibility as first-class failure modes. | K-Dense-AI/scientific-agents |
| [planetary-geologist](https://agentpluginsdirectory.com/plugins/planetary-geologist) | Reasons from stratigraphy and landform genesis through ISIS/GDAL/JMARS/ArcGIS, CraterTools/CSFD Tools/CraterStats2 chronology, CRISM/M3/THEMIS spectroscopy with SPLib/RELAB, and PDS archives while treating secondaries, projection/datums, and production-function choice as first-class failure modes. | K-Dense-AI/scientific-agents |
| [planetary-scientist](https://agentpluginsdirectory.com/plugins/planetary-scientist) | Reasons from bulk density, moment of inertia, tidal Love numbers, libration, electromagnetic induction, and sample-calibrated impact-flux chronology through NAIF SPICE kernels, PDS4 archives, radio-science gravity with SHTOOLS, PSG/NEMESIS retrievals, gamma-ray/neutron and radar sounding, and COSPAR planetary-protection categories while treating non-hydrostatic shapes, plasma currents mimicking ocean induction, radar clutter and roughness mimicking ice, single-line trace-gas detections, and one-flyby snapshot bias as first-class failure modes. | K-Dense-AI/scientific-agents |
| [plant-breeder](https://agentpluginsdirectory.com/plugins/plant-breeder) | Reasons from genetic variance, selection response (R = h²S), and breeding values through BLUP/GBLUP mixed models, multi-environment alpha-lattice trials with check cultivars, genomic selection validated within relatedness, and DUS/seed-certification standards, while treating linkage drag, G×E and G×management rank inversions, unvalidated GWAS hits, and seed mix-ups or off-type contamination as first-class failure modes. | K-Dense-AI/scientific-agents |
| [plant-pathologist](https://agentpluginsdirectory.com/plugins/plant-pathologist) | Reasons from the disease triangle, sign vs. symptom, and trophic strategy (biotroph/necrotroph/hemibiotroph); runs clinic-to-Koch workflows (TWA isolation, Phytophthora pear baiting, Baermann nematodes, EPPO PM7/qPCR with matrix-specific Ct cutoffs) and epidemic analysis (AUDPC/AUDPS, Vanderplank parameters, GLMMs) while treating abiotic mimicry, saprophyte overgrowth, and late-cycle PCR artifacts as first-class failure modes. | K-Dense-AI/scientific-agents |
| [plant-physiologist](https://agentpluginsdirectory.com/plugins/plant-physiologist) | Reasons from source: sink carbon: water balance, FvCB A, Ci and Ball, Berry gs models, LI-COR/PAM gas exchange, Scholander Ψ, drought, salt, heat signaling, and MIAPPE/Phytozome workflows while treating chamber leakage, pot-bound roots, and Fv/Fm, yield conflation as first-class failure modes. | K-Dense-AI/scientific-agents |
| [plasma-physicist](https://agentpluginsdirectory.com/plugins/plasma-physicist) | Reasons from collective scales (Debye length, plasma frequency), dimensionless regime parameters (beta, collisionality, Lundquist number), and instability drive-versus-dissipation through Grad-Shafranov equilibria (EFIT, VMEC), gyrokinetic and MHD codes (GENE, NIMROD, XGC), PIC simulation (VPIC, OSIRIS), and confinement scalings (IPB98, Greenwald, Troyon) while treating probe sheath distortion, equilibrium-reconstruction error, resolution-limited reconnection rates, and unmatched wall conditioning as first-class failure modes. | K-Dense-AI/scientific-agents |
| [pollution-control-engineer](https://agentpluginsdirectory.com/plugins/pollution-control-engineer) | Reasons from PTE, Title V Part 70, and NPDES limits through scrubber/baghouse/ESP/RTO selection, CEMS and stack-test demonstration, and parametric O&M (ΔP, pH, L/G) while treating synthetic-minor strategy, sulfite-blinded FGD, bag leaks, and WET/TIE toxicity as first-class failure modes. | K-Dense-AI/scientific-agents |
| [polymer-chemist](https://agentpluginsdirectory.com/plugins/polymer-chemist) | Designs and interprets polymer synthesis, characterization, and structure, property relationships from mechanism (chain-growth, step-growth, RDRP, ROMP) through absolute MW verification to application-relevant thermal and rheological data. | K-Dense-AI/scientific-agents |
| [polymer-scientist](https://agentpluginsdirectory.com/plugins/polymer-scientist) | Reasons from molecular weight distribution, Tg/Tm and crystallinity, viscoelasticity, and phase behavior through GPC/SEC, DSC heat-cool-heat, capillary and oscillatory rheology, WAXD/SAXS, and DMA while treating thermal-history erasure, moisture hydrolysis, incomplete cure, and wrong-grade-lot artifacts as first-class failure modes. | K-Dense-AI/scientific-agents |
| [population-geneticist](https://agentpluginsdirectory.com/plugins/population-geneticist) | Reasons from Wright, Fisher/coalescent demography, Weir, Cockerham FST, EIGENSOFT PCA, ADMIXTURE ancestry, ADMIXTOOLS f-statistics, and selscan XP-EHH/iHS/PBS selection scans while treating batch confounding, LD pruning choices, cryptic relatedness, and admixture-LD artifacts as first-class failure modes. | K-Dense-AI/scientific-agents |
| [poultry-scientist](https://agentpluginsdirectory.com/plugins/poultry-scientist) | Reasons from flock-level feed-to-gain conversion, digestible amino acid balance, and thermal/respiratory/pathogen load through FCR/EPEF and HDEP/HOF metrics, pen-or-house mixed models, coccidiosis lesion scoring, hatchery break-out, and strain management guides while treating subclinical coccidiosis and necrotic enteritis, wet-litter footpad dermatitis, pseudoreplicated subsampling, and woody-breast myopathy as first-class failure modes. | K-Dense-AI/scientific-agents |
| [power-electronics-engineer](https://agentpluginsdirectory.com/plugins/power-electronics-engineer) | Reasons from volt-second and charge balance, switched-mode energy transfer, and small-signal loop gain through PLECS/LTspice/SIMPLIS simulation, Steinmetz and Dowell magnetics loss accounting, Bode injection on hardware, and LISN-based EMI scans while treating shoot-through, RHP-zero subharmonic oscillation, Qrr and ZVS-window loss, and CM-choke saturation as first-class failure modes. | K-Dense-AI/scientific-agents |
| [power-grid-engineer](https://agentpluginsdirectory.com/plugins/power-grid-engineer) | Reasons from AC power flow, N-1 contingency, and relay coordination through PSS/E studies, distance/differential protection, IBR/IEEE 2800 models, COMTRADE event analysis, and NERC TPL/PRC standards while treating EMS topology drift, voltage collapse, and ATC vs nameplate as first-class failure modes. | K-Dense-AI/scientific-agents |
| [power-systems-engineer](https://agentpluginsdirectory.com/plugins/power-systems-engineer) | Reasons from per-unit impedances, symmetrical components, swing equations, and relay reach through PSS/E, OpenDSS, Aspen OneLiner, PSCAD, and NERC TPL/IEEE 1547/IEC 60909 criteria while treating loss of protection selectivity, DER-driven reverse power flow and voltage rise, CT saturation, and voltage collapse as first-class failure modes. | K-Dense-AI/scientific-agents |
| [precision-agriculture-specialist](https://agentpluginsdirectory.com/plugins/precision-agriculture-specialist) | Reasons from management-zone heterogeneity, the spatial 4R (right input, rate, place, time), and per-zone margin maps through SSURGO/ECa zone delineation, NDVI/NDRE indices, RTK-GNSS georeferencing, and ISOBUS Task Controller as-applied logs while treating planned-versus-applied divergence, NDVI saturation, miscalibrated yield-monitor mass-flow and lag, and RTK float passes as first-class failure modes. | K-Dense-AI/scientific-agents |
| [precision-engineering-specialist](https://agentpluginsdirectory.com/plugins/precision-engineering-specialist) | Reasons from ASME Y14.5 GD&T, GUM uncertainty, and micrometer error budgets through CMM programming (ISO 10360), volumetric compensation, UPDT/STS diamond turning, and ISO 14253 decision rules while treating datum mis-simulation, MMC bonus omission, and CMM program drift as first-class failure modes. | K-Dense-AI/scientific-agents |
| [precision-medicine-scientist](https://agentpluginsdirectory.com/plugins/precision-medicine-scientist) | Reasons from molecular profiles, tiered actionability, tumor purity, and clonal architecture through OncoKB and AMP/ASCO/CAP tiers, Mutect2/STAR-Fusion calling, IGV review, and CPIC pharmacogenomic guidelines while treating FFPE C-to-T deamination, CHIP mimicking somatic drivers, immortal-time bias in real-world data, and ancestry-skewed polygenic scores as first-class failure modes. | K-Dense-AI/scientific-agents |
| [primatologist](https://agentpluginsdirectory.com/plugins/primatologist) | Reasons from Tinbergen questions, habituation trade-offs, and phylogenetic comparative trees (TimeTree, Craig 2024) through focal/scan ethograms (BORIS, κ), Raven/Praat vocal repertoires, IUCN SSC great-ape surveys (A.P.E.S.), and CITES/IACUC/IPS health protocols while treating pseudoreplication, anthroponotic disease, nest-decay bias, and phylogenetic non-independence as first-class failure modes. | K-Dense-AI/scientific-agents |
| [probabilist](https://agentpluginsdirectory.com/plugins/probabilist) | Reasons from Kolmogorov measure spaces through LLN/CLT, martingales, coupling, concentration/LDP, and Lévy/Feller/Itô calculus; uses Durrett/Kallenberg canon, Sage/NumPy/PyMC simulation, and R̂/ESS/IS diagnostics while treating a.s. vs sure, Borel conditioning, OST misuse, and importance-weight explosion as first-class failure modes. | K-Dense-AI/scientific-agents |
| [process-chemist](https://agentpluginsdirectory.com/plugins/process-chemist) | Reasons from mass and energy balances, impurity fate maps, and supersaturation trajectories through RC1 calorimetry, DoE in JMP/MODDE, FBRM/XRPD crystallization tracking, and ICH Q8/Q9/Q11 control strategy while treating exotherm runaway at plant jacket capacity, ICH M7 genotoxic carry-over, polymorph shifts on scale, and unvalidated PAT release as first-class failure modes. | K-Dense-AI/scientific-agents |
| [process-engineer](https://agentpluginsdirectory.com/plugins/process-engineer) | Reasons from conservation laws, CSTR/PFR selectivity and RTD/Da scale-up through BFD→PFD→P&ID/HAZOP/LOPA/SIL, Aspen Plus/HYSYS HMB, API 520/521 relief and LMTD/F_t exchanger sizing, and lab→pilot→plant commissioning while treating frozen-design violations, simulation-without-data, and BPCS/IPL conflation as first-class failure modes. | K-Dense-AI/scientific-agents |
| [programming-languages-researcher](https://agentpluginsdirectory.com/plugins/programming-languages-researcher) | Reasons from operational semantics, type-theoretic invariants, and soundness as preservation-plus-progress through Ott/LN-defined calculi, Coq/Isabelle/Agda mechanization, Hindley-Milner inference, and abstract-interpretation Galois connections while treating stuck terms, blame escaping onto well-typed pure terms, broken substitution and canonical-forms lemmas, and unsound widening as first-class failure modes. | K-Dense-AI/scientific-agents |
| [propulsion-engineer](https://agentpluginsdirectory.com/plugins/propulsion-engineer) | Reasons from thrust, specific impulse, characteristic velocity c*, thrust coefficient Cf, and NPSH through NASA CEA, RPA and NPSS cycle models, hot-fire thrust stands, and ROCCID/bomb-test stability screening while treating nozzle separation, inducer cavitation, chugging/screech combustion instability, and scramjet unstart as first-class failure modes. | K-Dense-AI/scientific-agents |
| [protein-engineer](https://agentpluginsdirectory.com/plugins/protein-engineer) | Reasons from sequence-structure-function relationships, evolutionary constraint, and multiparameter developability through display selection, ProteinMPNN/RFdiffusion and AlphaFold modeling, SPR/BLI kinetics, and SEC/DSF/CE-SDS characterization while treating aggregation, Tm loss, proteolysis, glycoform mismatch, and immunogenic neo-epitopes as first-class failure modes. | K-Dense-AI/scientific-agents |
| [proteomics-scientist](https://agentpluginsdirectory.com/plugins/proteomics-scientist) | Reasons from peptide-to-protein inference, acquisition mode, quantification modality, and missing-value mechanism through MaxQuant, FragPipe/MSFragger, DIA-NN/Spectronaut, Skyline, and MSstats/proDA while treating MNAR missingness, batch confounding, TMT co-isolation ratio compression, and keratin/contaminant signal as first-class failure modes. | K-Dense-AI/scientific-agents |
| [protistologist](https://agentpluginsdirectory.com/plugins/protistologist) | Reasons from eukaryotic microbial diversity, trophic mode, and morphology-molecule integration through Utermöhl counts, SEM, 18S/V4 metabarcoding with PR2/SILVA, and IQ-TREE/MAFFT phylogenies while treating chimeric ASVs, kleptoplastic mixotroph misclassification, dinoflagellate multi-copy rRNA inflation, and reads-as-cell-counts conflation as first-class failure modes. | K-Dense-AI/scientific-agents |
| [psycholinguist](https://agentpluginsdirectory.com/plugins/psycholinguist) | Reasons from incremental parsing, lexical access, and prediction; designs SPR, eyetracking, VWP, and ERP studies with SUBTLEX/CELEX/MRC norms, maximal LMEMs, and OSF preregistration while treating list effects, SAT, spillover, and N400/P600 over-interpretation as first-class failure modes. | K-Dense-AI/scientific-agents |
| [psychophysicist](https://agentpluginsdirectory.com/plugins/psychophysicist) | Reasons from psychometric functions, staircase/MLE threshold procedures, signal-detection theory, and calibrated display/audio transducers while treating timing jitter, adaptation, and criterion/sensitivity conflation as first-class failure modes. | K-Dense-AI/scientific-agents |
| [public-health-scientist](https://agentpluginsdirectory.com/plugins/public-health-scientist) | Reasons from the 10 Essential Public Health Services, epidemiologic triad, and SDOH; runs outbreak field investigations, NSSP syndromic and NNDSS surveillance, BRFSS/WONDER complex-survey analysis, CDC Framework and RE-AIM program evaluation, PAF/PIF policy quantification, and Kass ethics review. | K-Dense-AI/scientific-agents |
| [pure-mathematician](https://agentpluginsdirectory.com/plugins/pure-mathematician) | Reasons from definitions, axioms, and proved theorems through lemma-ladder proof strategies, computer algebra (SageMath, GAP, Magma) and proof assistants (Lean 4/mathlib, Coq, Isabelle/HOL) checked against MathSciNet/zbMATH and OEIS, while treating hidden hypotheses, circular reasoning, unjustified w.l.o.g. steps, and ZFC-independence as first-class failure modes. | K-Dense-AI/scientific-agents |
| [quality-six-sigma-engineer](https://agentpluginsdirectory.com/plugins/quality-six-sigma-engineer) | Reasons from process variation, defect operational definitions, and customer-critical characteristics through Shewhart control charts, Gage R&R (%GRR, ndc), Cp/Cpk and Pp/Ppk capability, DMAIC tollgates, and AIAG PPAP/PFMEA in Minitab or JMP while treating Cpk on unstable processes, attribute data forced as normal, gauge spread consuming tolerance, and unverified projected savings as first-class failure modes. | K-Dense-AI/scientific-agents |