「pip」の検索結果

Patterns and techniques for evaluating and improving AI agent outputs. Use this skill when: - Implementing self-critique and reflection loops - Building evaluator-optimizer pipelines for quality-critical generation - Creating test-driven code refinement workflows - Designing rubric-based or LLM-as-judge evaluation systems - Adding iterative improvement to agent outputs (code, reports, analysis) - Measuring and improving agent response quality

日本語の概要は準備中です。原文の説明を表示しています。

Enforces baseline comparisons, cross-validation, interpretation, and leakage prevention for ML pipelines

日本語の概要は準備中です。原文の説明を表示しています。

Use when the user wants an end-to-end AI4S research pipeline — broad direction or specific topic in, full research package out (exploration + literature survey + experiment + paper). Meta-skill that chains the four downstream skills in order. Pure markdown, no Python runtime.

日本語の概要は準備中です。原文の説明を表示しています。

Complete CI/CD guide for Cloudflare Workers using GitHub Actions and GitLab CI. Use for automated testing, deployment pipelines, preview environments, secrets management, or encountering deployment failures, workflow errors, environment configuration issues.

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Publishes mobile applications to iOS App Store and Google Play with code signing, versioning, and CI/CD automation. Use when preparing app releases, configuring signing certificates, or setting up automated deployment pipelines.

日本語の概要は準備中です。原文の説明を表示しています。

Use when a user wants a TikZ figure for a paper — an icon, an editable architecture/pipeline/flow template, or an example — and wants you to find, edit, and verify it. The single repo-wide skill for working with the OpenTikZ library.

日本語の概要は準備中です。原文の説明を表示しています。

Systematic review response strategy guide for RebuttalStudio. Use when developing response strategies for reviewer comments, deciding how to classify concerns, or choosing between Accept/Defend/Clarify/Experiment approaches at any stage of the rebuttal pipeline.

日本語の概要は準備中です。原文の説明を表示しています。

Idiomatic Go concurrency - sync primitives, channel semantics, the select statement, and the standard channel patterns (cancellation/done-channel, fan-out/fan-in, pipeline, or-done, context, worker-pool). Use when writing or reviewing Go that spawns goroutines, shares state, or coordinates over channels, even if the user never says "concurrency" - e.g. data races, deadlocks, goroutine leaks, sync/context/select usage, or "make this parallel". Distilled from luk4z7/go-concurrency-guide.

日本語の概要は準備中です。原文の説明を表示しています。

Analyze source code for security vulnerabilities using static analysis tools, custom rules, and CI-integrated scanning pipelines. Use when the user requests static application security testing or provides relevant inputs for this workflow.

日本語の概要は準備中です。原文の説明を表示しています。

Set up a continuous integration and continuous delivery (CI/CD) pipeline for a software project, automating builds, tests, and deployments across environments. Use when the user requests ci cd or provides relevant inputs for this workflow.

日本語の概要は準備中です。原文の説明を表示しています。

Set up and manage data labeling workflows using manual annotation tools, semi-automated pipelines, active learning, and programmatic weak supervision. Use when the user requests data labeling or provides relevant inputs for this workflow.

日本語の概要は準備中です。原文の説明を表示しています。

Think and work like an expert Knowledge Representation Researcher. Use when a task calls for Knowledge Representation Researcher judgment. Reasons from model-theoretic semantics, the expressivity-vs-decidability-vs-scalability tradeoff, and competency questions through OWL 2 profiles, reasoners (HermiT, Pellet, ELK), ROBOT/Protégé pipelines, and SHACL validation while treating unsatisfiable classes, silent OWA-vs-CWA semantic mixing, hallucinated LLM-suggested axioms, and IRI-reuse on bad merges as first-class failure modes.

日本語の概要は準備中です。原文の説明を表示しています。

Think and work like an expert Meteorologist. Use when a task calls for Meteorologist judgment. Reasons from hydrostatic and geostrophic balance, scale-dependent dynamics, and the obs-to-NWP pipeline; works the Snellman funnel, matches HRRR/GFS/ECMWF to scale, and treats spin-up, convective scheme bias, radar AP, and PoP misinterpretation as first-class failure modes.

日本語の概要は準備中です。原文の説明を表示しています。

Think and work like an expert Metabolomics Scientist. Use when a task calls for Metabolomics Scientist judgment. Reasons from MSI annotation levels, pooled-QC RSD and D-ratio gates, MZmine/MS-DIAL/XCMS pipelines, HMDB/GNPS identification, and MetaboAnalyst batch correction (ComBat, QC-RLSC); treats injection-order drift, ComBat over-correction, and Level-5 pathway stories as first-class failure modes.

日本語の概要は準備中です。原文の説明を表示しています。

Think and work like an expert Molecular Ecologist. Use when a task calls for Molecular Ecologist judgment. Reasons from population genetics, eDNA/metabarcoding, and marker choice (microsatellites, SNPs, mtDNA); analyzes with STRUCTURE/ADMIXTURE, hierfstat FST, DADA2 pipelines, and ddPCR; treats null alleles, Wahlund effect, batch effects, and eDNA allelic dropout as first-class failure modes.

日本語の概要は準備中です。原文の説明を表示しています。

Think and work like an expert High-Energy Astrophysicist. Use when a task calls for High-Energy Astrophysicist judgment. Reasons from Compton/synchrotron radiative processes and compact-object energetics through HEASARC/Fermi/Swift/XMM/Chandra/NuSTAR/XRISM pipelines, XSPEC/Sherpa spectral fitting, pile-up and background systematics, blazar/GRB/TDE campaigns, and GCN multi-messenger coordination while treating RMF versioning, soft-proton flares, and look-elsewhere significance as first-class failure modes.

日本語の概要は準備中です。原文の説明を表示しています。

Think and work like an expert High-Performance Computing Specialist. Use when a task calls for High-Performance Computing Specialist judgment. Reasons from NUMA topology and hybrid MPI+OpenMP+CUDA decomposition through Slurm fairshare/backfill job design, strong/weak scaling (Amdahl/Gustafson), Darshan/mpiP/Nsight profiling, and parallel HDF5/MPI-IO on Lustre while treating I/O storms, collectives bottlenecks, and rank-binding mistakes as first-class failure modes.

日本語の概要は準備中です。原文の説明を表示しています。

Think and work like an expert Geographic Information Scientist (GIS). Use when a task calls for Geographic Information Scientist (GIS) judgment. 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.

日本語の概要は準備中です。原文の説明を表示しています。

Think and work like an expert Functional Genomics Scientist. Use when a task calls for Functional Genomics Scientist judgment. 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.

日本語の概要は準備中です。原文の説明を表示しています。

Think and work like an expert Fluid Mechanics Engineer. Use when a task calls for Fluid Mechanics Engineer judgment. 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.

日本語の概要は準備中です。原文の説明を表示しています。

Think and work like an expert Data Scientist. Use when a task calls for Data Scientist judgment. Reasons from CRISP-DM business estimands, leakage-safe sklearn Pipelines and nested CV, SQL/warehouse semantic metrics, A/B power and SRM/AA guardrails, causal DAG covariate discipline, and Model Cards/Datasheets while treating train-test leakage, Simpson's paradox, peeking, and PSI>0.25 drift as first-class failure modes.

日本語の概要は準備中です。原文の説明を表示しています。

Think and work like an expert Computer Vision Scientist. Use when a task calls for Computer Vision Scientist judgment. Reasons from image formation, projective geometry (pinhole intrinsics and extrinsics, epipolar/PnP/bundle adjustment, similarity-scale ambiguity), and COCO/LVIS AP mechanics through DINOv3/SigLIP 2 foundation baselines, RF-DETR/YOLO26/SAM 3 models, COLMAP 4/GLOMAP and VGGT geometry, pycocotools/TrackEval/BOP evaluation, and CVPR reporting and EU AI Act limits while treating train–test and pretraining leakage, AP evaluation-setting gaming, preprocessing mismatches (EXIF, BGR, aliased resizing), label noise, and camera-convention and scale errors as first-class failure modes.

日本語の概要は準備中です。原文の説明を表示しています。

Think and work like an expert Computational Scientist. Use when a task calls for Computational Scientist judgment. 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.

日本語の概要は準備中です。原文の説明を表示しています。

Think and work like an expert Cosmologist. Use when a task calls for Cosmologist judgment. Reasons from Friedmann/ΛCDM, r_s and transfer functions, and multi-probe inference (Planck CMB, DESI BAO, lensing, Pantheon+ SNe) through CAMB/CLASS, Cobaya, and GetDist while treating photo-z–IA coupling, CMB foreground pipelines, H0/S8 tensions, and emulator extrapolation as first-class failure modes.

日本語の概要は準備中です。原文の説明を表示しています。