545 件 ・ 関連度順
概要と使いどころ
Use for parsing structured unit commitment input data from JSON, CSV, benchmark cases, spreadsheets, databases, or nested tables; finding fields for time periods, resources, load, reserve, generator limits, initial conditions, startup data, renewable availability, and production costs without assuming one source-specific schema.
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Comprehensive guide for creating Claude Code agents with proper structure, triggering conditions, system prompts, and validation - combines official Anthropic best practices with proven patterns
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Master Go concurrency with goroutines, channels, sync primitives, and context. Use when building concurrent Go applications, implementing worker pools, or debugging race conditions.
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Genre anatomy from John Truby's The Anatomy of Genres (类型解剖 / 类型节拍 / 混合类型 / 超越类型) — genres as beat systems with a life philosophy underneath; three rules (hit every beat of your genre, mix three or four genres, transcend the primary genre), the ladder and families of twelve genres (Horror 恐怖, Action 动作, Myth 神话, Memoir and Coming-of-Age 回忆录与成长, Science Fiction 科幻, Crime 犯罪, Comedy 喜剧, Western 西部, Gangster 黑帮, Fantasy 奇幻, Detective and Thriller 侦探与惊悚, Love 爱情), each with its hero/opponent/world/plot-shape template, beat list, hard rules with failure conditions, subgenres and transcendent paths, plus a genre-mixing worksheet and a diagnostic. Kept beside sw-truby-anatomy and the Field/Snyder page maps. Use when choosing or confirming a script's genre, when a genre story feels generic or misses the beats its audience expects, when mixing genres, when a horror lacks pressure, an action lacks plot, a love story lacks opposition or a detective story lacks reveals.
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When a real test is too rare, large, or irreversible, run a controlled counterfactual: isolate one variable, fix conditions, trace the mechanistic chain, and bound what the result implies.
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Before rejecting a proposal or reflexively agreeing, build the strongest faithful opposing case, state agreement conditions, then update or reaffirm.
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Build branching dialogue and narrative — a node/choice graph with conditions, variables, and localization hooks — and choose between authoring tools Ink and Yarn Spinner or a custom data-driven runner. Engine-neutral. Use when the user mentions dialogue system, branching dialogue, conversation tree, choices, Ink (.ink), Yarn Spinner (.yarn), or NPC dialogue.
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Build a beginner running plan from wherever you are to a real goal — first nonstop mile, 5K, or 10K — that builds up slowly enough to avoid injury. Use when asked for a couch to 5k plan, help me start running, train for a [distance], or a running plan for beginners. Produces a week-by-week walk/run progression to the goal, session detail, pacing and form basics, rest and cross-training, and an injury-prevention note — with a 'check with a doctor if you have health conditions' flag.
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Detect business logic vulnerabilities in a codebase using a three-phase approach: threat modeling (domain analysis and attack scenarios), batched verify (check exploitable gaps in parallel subagents, 3 scenarios each), and merge (consolidate batch results). Covers price manipulation, workflow bypass, limit violations, race conditions, reward abuse, etc. Requires sast/architecture.md (run sast-analysis first). Outputs findings to sast/businesslogic-results.md. Use when asked to find business logic, logic flaws, or abuse-of-function bugs.
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Build and iterate custom add-ons/templates with tanstack add-on init, add-on compile, add-on dev, and tanstack create --dev-watch, including sync loop preconditions, watch-path validation, and project metadata constraints.
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Apply integrations to existing projects with tanstack add, including add-on id resolution, dependency chains, option prompts, and .cta.json project metadata preconditions.
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Shared loop-engineering reference for COG skills - the agent loop, deterministic verifiers, termination conditions, in-loop context management, and named patterns. Invoke when designing or debugging a skill that iterates (search-verify-retry, scan-until-dry, fetch-retry-gate).
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Use when building the theoretical engine for an Administrative Science Quarterly (ASQ) manuscript — mechanisms, process vs. variance logic, constructs, and boundary conditions. Builds the argument; it does not select methods or run analysis.
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Use when building the actual theory for an Academy of Management Review (AMR) manuscript — turning a positioned puzzle into defined constructs, explicit relationships, propositions, and boundary conditions. Constructs the theory; it does NOT stress-test the argument's logic (that is amr-data-analysis) or design any data collection (AMR has none).
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Use when choosing and applying a theory-construction method for an Academy of Management Review (AMR) manuscript — building constructs, defining their domain, specifying relationships, articulating the underlying logic/mechanisms, and setting boundary conditions. This is the THEORY-CONSTRUCTION craft, NOT empirical method; AMR publishes no datasets, no measures, and no statistical tests.
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Use when an Accounting, Organizations and Society (AOS) revise-and-resubmit arrives — planning revisions that may include recoding field data, new experimental conditions, or deepened theorizing, and drafting the point-by-point response to an interdisciplinary reviewer panel. Drafts the response; it does not run new analysis (aos-data-analysis) or the final preflight (aos-submission).
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Creates and inspects Fabric Activator (Reflex) alerts: rules, their data sources, conditions, and the Teams or email action they fire, plus decoding an existing ReflexEntities definition. Choose it whenever someone wants to be told, or something done, when values cross a threshold. The pipeline delivering those values is eventstream-cli.
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Get current weather and forecasts using free APIs (no API key required). Use when asked about weather, temperature, forecasts, or climate conditions for any location.
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Detects TAD boundaries from balanced Hi-C contact matrices via the diamond-window insulation score (cooltools insulation) and HiCExplorer hicFindTADs, returning a continuous log2 insulation track, valley-prominence boundary_strength, and Li/Otsu-thresholded is_boundary flags across a list of window sizes. Covers the multi-scale window sweep (sub-TAD to compartment-domain), why the boundary is reproducible but the domain partition is not, cross-condition comparison via differential SCORE not differential partition, and the insulation-vs-compartment orthogonality. Use when calling TADs or domain boundaries, computing insulation scores, choosing a window size, ranking boundary strength, comparing boundaries across conditions, or annotating CTCF-backed boundaries; route domain rendering to hic-visualization and boundary-feature overlap to genome-intervals.
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Compare cell-type composition and spatial features across conditions in IMC/MIBI cohorts with the patient as the experimental unit, covering pseudoreplication, per-patient aggregation, mixed models, compositional (Dirichlet/scCODA) differential abundance, diffcyt, per-image-to-patient spatial differential testing (SpaceANOVA), batch covariates, and FDR. Use when testing whether a cell type or spatial niche differs between groups, avoiding cell-level pseudoreplication, choosing a differential-abundance method, or correctly powering an IMC cohort comparison.
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Detects focal chromatin loops (point interactions / corner-dots) in balanced Hi-C and Micro-C contact maps and aggregates/validates a loop set. Covers de-novo calling with cooltools dots (HiCCUPS-style 4-background local enrichment with lambda-chunked FDR), chromosight (template-correlation), and Mustache (scale-space blob detection); aggregate peak analysis (APA) via cooltools pileup for confirmation; the depth/resolution prerequisite (de-novo needs ~5-10kb resolution = hundreds of millions to billions of valid pairs); consensus across callers and convergent-CTCF support as validation; and differential loops via union anchors plus chromosight quantify. Use when calling chromatin loops or dots from a cooler, deciding whether a map is deep enough to call de-novo vs running APA on known CTCF/cohesin anchors, building an aggregate peak pileup, comparing loops across conditions, or validating loop calls. For HiChIP/PLAC-seq/PCHi-C protein-anchored data use FitHiChIP/MAPS, not dots.
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Calls significant loops from protein-directed and targeted 3C assays (HiChIP, PLAC-seq, Capture Hi-C/PCHi-C, ChIA-PET) where the contact background is peak-anchored and coverage-biased, so generic Hi-C loop callers (cooltools dots, Juicer HiCCUPS) use the wrong null. Covers FitHiChIP (config-driven coverage+distance-decay spline regression, peak-to-peak vs peak-to-all foreground, loose vs stringent background, coverage vs ICE bias), MAPS (positive Poisson regression on bias factors for PLAC-seq/HiChIP), hichipper (restriction-site-distance bias model + library QC), CHiCAGO (Delaporte two-component Brownian+technical background for asymmetric bait x other-end Capture Hi-C), the with/without separate-ChIP anchor decision, and differential loops via diffloop. Use when calling loops from HiChIP/PLAC-seq/Capture Hi-C, choosing FitHiChIP/MAPS/CHiCAGO, picking peak-to-all vs peak-to-peak, setting the loop FDR, supplying ChIP peaks as anchors, QCing a HiChIP library, or comparing loops between conditions.
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Compares Hi-C contact maps between conditions across the right scale -- differential bin-pair contacts (multiHiCcompare, diffHic), differential A/B compartments (dcHiC), differential TAD boundaries (delta insulation), and differential loops (diffloop, DiffHiChIP) -- with distance-stratified between-sample normalization, replicate-aware NB-GLM FDR, HiCRep SCC reproducibility gating, and CNV correction for cancer/aneuploid samples. Use when comparing Hi-C between treatment and control, finding differential contacts/compartments/boundaries/loops, normalizing two maps of unequal depth, choosing a replicate-aware test, gating replicates with SCC, or correcting copy-number artifacts before a tumor-vs-normal comparison.
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Renders Hi-C contact matrices honestly and reproducibly with matplotlib, cooltools, HiCExplorer, pyGenomeTracks, FAN-C, CoolBox, and plotgardener. Covers the raw/ICE-balanced/observed-over-expected transform choice, LogNorm vs symmetric-diverging colormaps with vmax/percentile clipping, resolution-to-feature matching (compartments 100-500kb, TADs 10-40kb, loops 5-10kb), square vs rotated-triangle track-stacking, NaN/white-stripe handling, virtual 4C, APA/saddle/on-diagonal pileups, two-condition side-by-side and log2-ratio maps, and interactive (HiGlass) vs scripted-static publication figures. Use when plotting a contact matrix, choosing a normalization or color scale, building a multi-track Hi-C figure, making a virtual 4C profile, piling up loops/boundaries, or comparing two conditions.
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