---
title: "Agent Plugins Directory, page 72 of 81"
description: "| Name | Description | Repo |"
canonical: https://agentpluginsdirectory.com/directory/page/72
last-updated: 2026-10-03
---

# Agent Plugins Directory, page 72 of 81

| Name | Description | Repo |
| --- | --- | --- |
| [vendor-comparison](https://agentpluginsdirectory.com/plugins/vendor-comparison) | Run a defensible vendor evaluation across requirements, risk, total cost, and implementation fit. | xopcai/xopc-plugins |
| [climate-scientist](https://agentpluginsdirectory.com/plugins/climate-scientist) | Reasons from ERF/EEI energy-budget closure, AR6 forcing (WMGHG vs ERFaci), optimal fingerprinting and FAR event attribution, CMIP6/ScenarioMIP SSP workflows (ESGF, ESMValTool), and paleo proxy physics (PAGES2k, ice-core δD/CO₂, foraminifera Mg/Ca, coral Sr/Ca) while treating aerosol uncertainty, tree-ring divergence, CMIP tuning circularity, and TLS under-coverage as first-class failure modes. | K-Dense-AI/scientific-agents |
| [structured-autonomy](https://agentpluginsdirectory.com/plugins/structured-autonomy) | Premium planning, thrifty implementation | rakthainet-DKH/FormTH-copilot |
| [video-production-brief](https://agentpluginsdirectory.com/plugins/video-production-brief) | Turn a communication goal into a production-ready video brief with story, shots, assets, and approvals. | xopcai/xopc-plugins |
| [climatologist](https://agentpluginsdirectory.com/plugins/climatologist) | Characterizes climate via WMO CLINO baselines (1991 to 2020 vs 1961 to 1990), ETCCDI indices, and teleconnection modes; bridges ERA5 climatology to CMIP6/ScenarioMIP SSP deltas (xsdba/QDM), optimal-fingerprint attribution, AR6 ERF/ECS/TCR, and proxy reconstructions (CPS/EIV, PAGES2k, MXD divergence), distinct from weather forecasting and generic physical-climate narration. | K-Dense-AI/scientific-agents |
| [swift-mcp-development](https://agentpluginsdirectory.com/plugins/swift-mcp-development) | Comprehensive collection for building Model Context Protocol servers in Swift using the official MCP Swift SDK with modern concurrency features. | rakthainet-DKH/FormTH-copilot |
| [weekly-report](https://agentpluginsdirectory.com/plugins/weekly-report) | Convert work updates into a concise outcome-oriented weekly report with risks and next priorities. | xopcai/xopc-plugins |
| [clinical-data-manager](https://agentpluginsdirectory.com/plugins/clinical-data-manager) | Reasons from ALCOA+ data integrity, traceability, and analysis-ready datasets through CDASH/SDTM/ADaM pipelines, edit-check specs, Pinnacle 21 validation, MedDRA/WHO Drug coding, and define.xml under 21 CFR Part 11, treating blinding breaches, SAE-safety reconciliation gaps, mid-study IG/dictionary version drift, and unspecified partial-date imputation as first-class failure modes. | K-Dense-AI/scientific-agents |
| [technical-spike](https://agentpluginsdirectory.com/plugins/technical-spike) | Tools for creation, management and research of technical spikes to reduce unknowns and assumptions before proceeding to specification and implementation of solutions. | rakthainet-DKH/FormTH-copilot |
| [clinical-embryologist](https://agentpluginsdirectory.com/plugins/clinical-embryologist) | Reasons from gamete and embryo biology, manufacturing-quality lab control, and prespecified cycle/oocyte/embryo denominators through Vienna consensus KPIs, Gardner/ASEBIR grading, time-lapse morphokinetics, WHO 6th-edition andrology, and vitrification SOPs while treating media-lot and incubator-gas drift, witness mix-ups, abnormal fertilization (1PN/3PN), and clinical case-mix confounding as first-class failure modes. | K-Dense-AI/scientific-agents |
| [testing-automation](https://agentpluginsdirectory.com/plugins/testing-automation) | Comprehensive collection for writing tests, test automation, and test-driven development including unit tests, integration tests, and end-to-end testing strategies. | rakthainet-DKH/FormTH-copilot |
| [clinical-epidemiologist](https://agentpluginsdirectory.com/plugins/clinical-epidemiologist) | Clinical epidemiology expert for causal study design, observational bias control, GRADE/EBM synthesis, and principled reporting (CONSORT/STROBE/PRISMA). | K-Dense-AI/scientific-agents |
| [the-workshop](https://agentpluginsdirectory.com/plugins/the-workshop) | Stop being the switchboard between your AI agents, direct a team. The Workshop puts long-running AI agents (desks) in the same room, on the same work, each with its own memory and history, sharing one workspace so you direct the work instead of relaying it. | rakthainet-DKH/FormTH-copilot |
| [clinical-laboratory-scientist](https://agentpluginsdirectory.com/plugins/clinical-laboratory-scientist) | Reasons from pre-analytical, analytical, post-analytical total testing process; EP15/EP09/EP28 validation, Westgard/Sigma IQC, HIL indices (C56), EP23/IQCP, critical-value read-back, type-and-screen/crossmatch, CLSI M100 direct AST, LC-MS/MS C62, and AUTO10 autoverification. | K-Dense-AI/scientific-agents |
| [tiny-tool-town-submitter](https://agentpluginsdirectory.com/plugins/tiny-tool-town-submitter) | Inspect a repository, improve Tiny Tool Town readiness, submit its listing issue, and launch remediation work. | rakthainet-DKH/FormTH-copilot |
| [clinical-microbiologist](https://agentpluginsdirectory.com/plugins/clinical-microbiologist) | Reasons from blood-culture volume and contamination criteria, staged Gram, ID, AST reporting, MALDI-TOF/VITEK/Phoenix and EUCAST RAST, CLSI M100 vs EUCAST breakpoint discipline, WHONET antibiograms, and NHSN MDRO alerts, treating contaminant vs pathogen and VME/ME as first-class failure modes. | K-Dense-AI/scientific-agents |
| [token-pacman](https://agentpluginsdirectory.com/plugins/token-pacman) | Visualizes live session AI-credit usage as a Pac-Man board with pellets, ghosts, fruit milestones, and game-over limits. | rakthainet-DKH/FormTH-copilot |
| [clinical-pharmacologist](https://agentpluginsdirectory.com/plugins/clinical-pharmacologist) | Reasons from exposure: response, popPK (NONMEM), DDI (ICH M12), TDM/NTI windows, and renal/hepatic/allometric adjustment; aligns dose finding with ICH E4 and FDA clinical pharmacology labeling. | K-Dense-AI/scientific-agents |
| [typescript-mcp-development](https://agentpluginsdirectory.com/plugins/typescript-mcp-development) | Complete toolkit for building Model Context Protocol (MCP) servers in TypeScript/Node.js using the official SDK. Includes instructions for best practices, a prompt for generating servers, and an expert chat mode for guidance. | rakthainet-DKH/FormTH-copilot |
| [clinical-trial-scientist](https://agentpluginsdirectory.com/plugins/clinical-trial-scientist) | Reasons from protocol SAPs, ICH-GCP, randomization/blinding, and CDISC SDTM while treating protocol deviations and immortal time as first-class failure modes. | K-Dense-AI/scientific-agents |
| [typespec-m365-copilot](https://agentpluginsdirectory.com/plugins/typespec-m365-copilot) | Comprehensive collection of prompts, instructions, and resources for building declarative agents and API plugins using TypeSpec for Microsoft 365 Copilot extensibility. | rakthainet-DKH/FormTH-copilot |
| [coastal-engineer](https://agentpluginsdirectory.com/plugins/coastal-engineer) | Reasons from joint-probability surge and waves through CEM/EurOtop runup-overtopping, Van der Meer/Rock Manual armor, CERC, Van Rijn sediment budgets, and CMS/XBeach/ADCIRC, SWAN model selection while treating toe scour, armor breakage, datum mismatch (BFE vs MHHW), and downdrift impacts as first-class failure modes. | K-Dense-AI/scientific-agents |
| [uizze](https://agentpluginsdirectory.com/plugins/uizze--rakthainet-dkh) | Build product-specific interfaces with a focused UIZZE workflow, optional real-screen evidence, and a practical finish check. | rakthainet-DKH/FormTH-copilot |
| [cognitive-neuroscientist](https://agentpluginsdirectory.com/plugins/cognitive-neuroscientist) | Reasons from latent constructs through converging behavior, fMRI/M/EEG, TMS, and lesion evidence; designs factorial and dissociation contrasts, fMRIPrep/GLMsingle/MNE pipelines, MVPA/RSA, and COBIDAS reporting while treating pure insertion, reverse inference, motion confounds, and in-sample decoding as first-class failure modes. | K-Dense-AI/scientific-agents |
| [visual-pr](https://agentpluginsdirectory.com/plugins/visual-pr) | Capture, annotate, and embed screenshots and animated GIF demos in pull request descriptions. Includes Playwright-based UI capture, PIL image annotations, PR embedding workflows for GitHub and Azure DevOps, and screen recording with variable timing. | rakthainet-DKH/FormTH-copilot |
| [cognitive-scientist](https://agentpluginsdirectory.com/plugins/cognitive-scientist) | Reasons from Marr's levels of analysis, latent processes behind RT and accuracy, and strong inference through PsychoPy paradigms, signal-detection d-prime/criterion, sequential-sampling and ACT-R models, and crossed mixed-effects designs while treating speed-accuracy tradeoffs, criterion shifts, item confounds, and underpowered WEIRD samples as first-class failure modes. | K-Dense-AI/scientific-agents |
| [where-was-i](https://agentpluginsdirectory.com/plugins/where-was-i) | Reconstruct your dev context (branch, commits, uncommitted work, PR clues) and trigger a resume prompt to continue quickly. | rakthainet-DKH/FormTH-copilot |
| [colloid-chemist](https://agentpluginsdirectory.com/plugins/colloid-chemist) | Reasons from interfacial thermodynamics, DLVO and non-DLVO forces, zeta-potential, and rheology through orthogonal characterization (DLS, NTA, cryo-TEM, SAXS/SANS S(Q), pendant-drop tensiometry) and accelerated-aging stability tests while treating coalescence, Ostwald ripening, creaming, and flocculation crossing the isoelectric point as first-class failure modes. | K-Dense-AI/scientific-agents |
| [windows-app-storage-inspector-cleanup](https://agentpluginsdirectory.com/plugins/windows-app-storage-inspector-cleanup--rakthainet-dkh) | Inspect Windows application storage, understand local disk usage, and safely move approved cleanup items to the Recycle Bin. | rakthainet-DKH/FormTH-copilot |
| [combinatorialist](https://agentpluginsdirectory.com/plugins/combinatorialist) | Reasons from labelled vs unlabelled enumeration, EGF/OGF and species, bijective and probabilistic proofs, Turán/Ramsey/extremal bounds, and BIBD/OA design parameters through SageMath/GAP/nauty, OEIS, House of Graphs, and Colbourn, Dinitz tables while treating isomorphism double-counting, parity barriers, and OEIS false matches as first-class failure modes. | K-Dense-AI/scientific-agents |
| [work-hub](https://agentpluginsdirectory.com/plugins/work-hub) | Generic cross-repo command center canvas for GitHub Copilot with onboarding, focus planning, repo health, work signals, and session cleanup. | rakthainet-DKH/FormTH-copilot |
| [combustion-engineer](https://agentpluginsdirectory.com/plugins/combustion-engineer) | Reasons from stoichiometry, flame stability, emissions, and CFD-reacted flows while treating blow-off, flashback, and soot formation as first-class failure modes. | K-Dense-AI/scientific-agents |
| [communications-engineer](https://agentpluginsdirectory.com/plugins/communications-engineer) | Reasons from Shannon capacity and matched-filter detection through OFDM/MIMO, 3GPP NR LDPC/polar (TS 38.212), TR 38.901 link budgets, Keysight 89600 VSA EVM, ns-3 SLS, and berconfint Monte Carlo while treating CFO/IQ/phase-noise coupling, pre- vs post-FEC BER, and AWGN-only optimism as first-class failure modes. | K-Dense-AI/scientific-agents |
| [community-ecologist](https://agentpluginsdirectory.com/plugins/community-ecologist) | Reasons from Vellend's four processes and Chesson stabilizing/equalizing coexistence through PERMANOVA/betadisper, betapart turnover, nestedness, Gotelli SIM9/C-score null models, and vegan/entropart/picante pipelines while treating compositional closure, dispersion heterogeneity, and pseudoreplicated quadrats as first-class failure modes. | K-Dense-AI/scientific-agents |
| [comparative-medicine-researcher](https://agentpluginsdirectory.com/plugins/comparative-medicine-researcher) | Reasons from species biology, translational validity, and the 3Rs through model-validity frameworks, IACUC protocols, ARRIVE 2.0 reporting, and FELASA/AALAS health surveillance while treating substrain drift, subclinical colony infection (murine norovirus, pinworm, Mycoplasma), analgesia-pathway confounds, and unstated husbandry variables as first-class failure modes. | K-Dense-AI/scientific-agents |
| [comparative-physiologist](https://agentpluginsdirectory.com/plugins/comparative-physiologist) | Reason from the Krogh principle and oxygen cascade through intermittent-flow respirometry, SMR/BMR/MMR scope, Q10 and heterothermy, hemoglobin P50, allometry and PGLS, while treating chamber drift, activity artifacts, phylogenetic pseudoreplication, and SMR definition mismatch as first-class failure modes. | K-Dense-AI/scientific-agents |
| [composites-engineer](https://agentpluginsdirectory.com/plugins/composites-engineer) | Reasons from CLT/ABD laminate mechanics, Halpin: Tsai micromechanics, and CMH-17/NCAMP allowables through autoclave/OOA/RTM process control, ASTM D30 mechanical qualification, ultrasonic C-scan and CAI damage tolerance while treating fiber waviness, void content, under-cure, and quasi-isotropic strength traps as first-class failure modes. | K-Dense-AI/scientific-agents |
| [computational-chemist](https://agentpluginsdirectory.com/plugins/computational-chemist) | Reasons from Kohn: Sham DFT, def2/D4 functional selection, and conformer ensembles through VASP/Gaussian/ORCA, AMBER/GROMACS MD, CREST/CENSO sampling, ONIOM/QM/MM electrostatic embedding, GMTKN55 validation, and SCF convergence escalation while treating B3LYP/6-31G*, BSSE, link-atom artifacts, and force-field mismatch as first-class failure modes. | K-Dense-AI/scientific-agents |
| [computational-linguist](https://agentpluginsdirectory.com/plugins/computational-linguist) | Reasons from UD/PTB formalisms, validate.py/eval.py (LAS/MLAS/ELAS), and evalb.prm settings through Stanza/UDPipe pipelines, PropBank/FrameNet/AMR/UMR layers, IAA (κ, Krippendorff α), CONDA contamination checks, and ARR reproducibility while treating tokenizer mismatch, oracle inflation, train, test leakage, and guideline drift as first-class failure modes. | K-Dense-AI/scientific-agents |
| [computational-neuroscientist](https://agentpluginsdirectory.com/plugins/computational-neuroscientist) | Reasons from encoding/decoding, GLM/LNP spike-train likelihood, mean-field E-I balance, and neural manifolds through NEST/Brian/NEURON/BMTK, GPFA/LFADS, Brain-Score alignment, and trained-RNN reverse engineering while treating spike-sorting contamination, model non-identifiability, nested-CV leakage, and task-optimization≠mechanism as first-class failure modes. | K-Dense-AI/scientific-agents |
| [computational-physicist](https://agentpluginsdirectory.com/plugins/computational-physicist) | Reasons from governing equations, discretization, and HPC scaling through code/solution verification, DFT, MD, Monte Carlo, and FEM/FVM workflows (VASP, LAMMPS, COMSOL, OpenFOAM, QE). | K-Dense-AI/scientific-agents |
| [computational-scientist](https://agentpluginsdirectory.com/plugins/computational-scientist) | Reasons from Roache code/solution verification and ASME V&V 10/20/40 credibility through MMS/GCI, UQ ensembles, and Snakemake/Nextflow/CWL pipelines with conda-lock/Apptainer provenance while treating environment drift, workflow cache staleness, and validation-vs-calibration conflation as first-class failure modes. | K-Dense-AI/scientific-agents |
| [computational-social-scientist](https://agentpluginsdirectory.com/plugins/computational-social-scientist) | Reasons from social mechanisms, measurement validity, and sampling frames through DAGs, fixed-effects and IV/DiD/RDD designs, ERGM/SAOM network models, and human-audited text classifiers while treating unobserved homophily, network interference and SUTVA violations, platform-driven selection, bot contamination, and digital-skew unrepresentativeness as first-class failure modes. | K-Dense-AI/scientific-agents |
| [computer-architecture-researcher](https://agentpluginsdirectory.com/plugins/computer-architecture-researcher) | Reasons from ISA semantics, AMAT/CPI, MESI coherence, and branch prediction through gem5/SPEC/MLPerf evaluation, Amdahl and roofline discipline, TPU/GPU dataflow accelerators, DVFS/EDP, and Spectre/Meltdown mitigation overhead at ISCA/MICRO/HPCA rigor. | K-Dense-AI/scientific-agents |
| [computer-graphics-researcher](https://agentpluginsdirectory.com/plugins/computer-graphics-researcher) | Reasons from the rendering equation, Monte Carlo bias/variance, sampling theory, and BSDF energy conservation through pbrt-v4/Mitsuba 3 references, MIS/ReSTIR/path guiding, DXR 1.2 real-time stacks, 3DGS and NerfBaselines protocols, FLIP/ColorVideoVDP evaluation, OpenUSD/MaterialX/OpenPBR interchange, and ACES 2/OCIO color while treating unconverged references, unequal-time comparisons, denoiser and temporal-reuse bias, scene- vs display-referred color errors, and white-furnace energy failures as first-class failure modes. | K-Dense-AI/scientific-agents |
| [computer-hardware-engineer](https://agentpluginsdirectory.com/plugins/computer-hardware-engineer) | Reasons from CPI/AMAT and MESI/MOESI coherence through SystemVerilog RTL, PrimeTime/Design Compiler/Innovus signoff, PCIe LTSSM/TLP, SVA formal, and clock-gating power while treating CDC metastability, false-path abuse, X-optimism, and coherency traffic as first-class failure modes. | K-Dense-AI/scientific-agents |
| [computer-scientist](https://agentpluginsdirectory.com/plugins/computer-scientist) | Reasons from computational models, abstraction contracts, invariants, and measurable complexity through CLRS-grade algorithm analysis, impossibility results (FLP, CAP, NP-hardness), property-based and chaos testing, and formal tools (TLA+, Coq, Z3) while treating partial failure, race conditions, label leakage, and abstraction leaks like GC pauses and clock skew as first-class failure modes. | K-Dense-AI/scientific-agents |
| [computer-security-researcher](https://agentpluginsdirectory.com/plugins/computer-security-researcher) | Reasons from explicit threat models and CIA/STRIDE through AFL++/libFuzzer triage, ASan/KASAN oracles, ProVerif/Tamarin proofs, CVE/CWE/CAPEC taxonomies, CyberGym dual-execution benchmarks, Menlo/CVD ethics, and USENIX open-science artifact norms. | K-Dense-AI/scientific-agents |