「oop」の検索結果

Trains and applies base-resolution deep learning models on ChIP-seq / ChIP-nexus / CUT&RUN data. Uses BPNet (Avsec 2021 Nat Genet 53:354; soft motif syntax from ChIP-nexus), chromBPNet (Pampari A et al 2025 Nat Genet; bias-factorized base-resolution profiles), EnFormer (Avsec 2021 Nat Methods 18:1196; 196 kb input, ~100 kb effective receptive field), DeepSEA (Zhou 2015; multi-task CNN), and JASPAR 2026 deep-learning collection (1259 BPNet ChIP models). Performs in silico mutagenesis for variant-effect prediction, DeepLIFT/Grad attribution, and TF-MoDISco motif discovery from attribution scores. Use when predicting variant effects on TF binding, discovering soft motif syntax / cooperativity, integrating ChIP-seq with sequence-only predictions, or applying precomputed JASPAR Deep Learning models to new variants.

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。

Bulk-query Ensembl BioMart (and other BioMart instances) for cross-database ID mapping, gene/transcript/exon coordinates, and ortholog tables. Use when batch-converting Ensembl IDs to other namespaces (HGNC, RefSeq, UniProt, Entrez), pulling gene coordinate tables for thousands of genes, building ortholog wide-tables across species, or replacing slow Ensembl REST loops with one-shot bulk export. Encodes BioMart's XML query format, R biomaRt vs Python pybiomart trade-off, mart-vs-dataset hierarchy, and the URL endpoint that's BioMart-specific (separate from rest.ensembl.org).

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。

Workflow for Hi-C and related 3D genomics analyses including compartments, loops, TADs, differential contacts, and visualization.

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 after task analysis when a non-trivial Formax repository task needs a structured `docs/todolist.md` with [x]/[ ] items, definitions-before-UI ordering, explicit non-goals, tests, and loop-ready execution slices.

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。

Diagnosis loop for hard bugs and performance regressions. Use when the user says "diagnose"/"debug this", or reports something broken/throwing/failing/slow.

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。

Craft verifiable, tight goal prompts for AI coding agents (Claude Code /goal, Codex Automations, Pi), either from a standalone task interview or from an already-approved to-goal handoff. Use when the user says "给我一个 goal 提示词", "帮我写个 goal", "设置一个自动化任务", "我想让 agent 自动做 X", or asks to turn a task into a self-running loop. Ensures every goal has a checkable completion criterion so the agent knows when it's done.

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。

Grill me about specs for the workflows I want to build, within this workspace.

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。

Turn a vague bug report into a VERIFIED minimal reproduction and then a failing regression test, agent-driven end to end. Covers extracting the implicit repro from a thin report (env, build, steps, data), the reproduce-minimize-isolate-capture loop, git bisect to find the introducing commit, building a deterministic minimal repro (fixed seeds, frozen time, stubbed network), writing the failing regression test BEFORE the fix (red) and confirming the fix flips it green, and writing repro evidence back into the ticket. Distinguishes flaky-not-reproducible from environment-specific. Use when: "reproduce this bug," "minimal reproduction," "repro steps," "find the commit that broke it," "git bisect," "make the repro deterministic," "write a failing test for this bug," "regression test for a defect," "can't reproduce this bug." Not for: Classifying/deduplicating/severity-routing existing failures without reproducing them — that is ai-bug-triage. Generating tests from specs rather than from a defect — that is ai-test-generation. Related: ai-bug-triage, ai-test-generation, test-reliability, systematic-debugging, qa-project-context.

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。

Reviews and adjusts PRD plans based on research findings. Use after completing research to evaluate story modifications. Triggers on: review plan, adjust stories, update prd based on research.

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。

Guides God Committee members through executing interventions. Use for repairs, rollbacks, and emergency actions. Triggers on: intervention, repair, rollback, emergency action.

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。

Defines God Committee member behavior and responsibilities with oversight authority. Use when operating as a committee member. Triggers on: god committee, committee observation, council discussion.

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。

Logs AI thoughts and decisions for human observability. Applies continuously throughout all tasks to maintain transparency.

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。

Reviews and cleans up outdated documentation. Use periodically to maintain documentation health. Triggers on: review docs, clean up documentation, check for stale docs.

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。

Guides God Committee members through consensus-building for collective decisions. Use for proposals, voting, and disagreement resolution. Triggers on: consensus, voting, proposal, committee decision.

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。

Builds project visions through interactive guided conversation. Use when users have vague ideas needing structure. Triggers on: build vision, I have an idea, start new project, new idea.

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。

Creates new Skills following Anthropic best practices. Use when discovering reusable workflows or repetitive patterns. Triggers on: create skill, new workflow, codify this process, standardize 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。

Guides parallel exploration of multiple implementation approaches using git worktrees. Use when facing decisions with multiple valid paths. Triggers on: explore options, compare approaches, parallel exploration.

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。

Generates Product Requirements Documents (PRD) for new features. Use when planning features or starting projects. Triggers on: create prd, write prd, plan feature, requirements, spec out.

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。

Designs system architecture and selects technology stack based on vision analysis. Use after vision analysis for technical decisions. Triggers on: design architecture, select tech stack, choose framework.

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。

Parses and analyzes project vision to extract structured requirements. Use at project start to understand goals, scope, and constraints. Triggers on: analyze vision, parse project goals, understand requirements.

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。

Creates and manages project roadmaps with milestones and PRD queues. Use after architecture is defined for project planning. Triggers on: create roadmap, plan milestones, organize prds.

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。

Execute implementation within EPICs following test-first development, continuous SoT updates, and code traceability during PRD v0.7 Build Execution. Triggers on requests to start building, implement an epic, begin coding, or when user asks "start building", "implement epic", "coding", "development", "build execution", "implementation", "write code". Consumes EPIC- (context), TEST- (acceptance criteria). Updates existing IDs and creates code. Outputs working code with @implements traceability tags.

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。

Define test cases BEFORE implementation, ensuring every API, business rule, and user journey has verifiable acceptance criteria during PRD v0.7 Build Execution. Triggers on requests to define tests, plan test coverage, create test cases, or when user asks "define tests", "test planning", "what to test?", "test cases", "test coverage", "TEST-", "test-first". Consumes EPIC- (scope), API-, DBT-, BR-, UJ-. Outputs TEST- entries with Given-When-Then format. Feeds v0.7 Implementation Loop.

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。

Iterative rubric-based evaluation and self-improvement loop. Builds a scoring rubric interactively, evaluates an artifact with multiple models in parallel (Codex, Gemini, Claude), then autonomously improves the artifact one criterion at a time until a score threshold is met or circuit breaker fires. "/rulph", "rubric evaluate", "rubric score", "multi-model evaluate", "score and improve", "evaluate and iterate", "grade this", "루브릭 루프", "채점 루프", "자율 개선", "개선 루프", "루브릭 평가"

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。