Results for “cross-functional-alignment”

Alignment

Use when performing multiple sequence alignment of FASTA inputs, generating alignment ensembles, or calculating alignment confidence metrics.

Use when masking columns or coordinate ranges in multiple-sequence alignments before downstream HMMER or alignment-processing steps.

Use when performing multiple sequence alignment on nucleotide or protein sequences, such as preparing alignments for phylogenetic analysis or comparative genomics.

当寻求个人行动或项目在更宏大系统中的意义，或需要将日常工作与长远价值连接时

Provides a structured reasoning protocol for diagnosing complex relationships, organizations, institutions, public disputes, or long-term evolution using the CrossFrame framework, with explicit invocation required.

Use when performing multiple sequence alignments on protein or nucleotide sequences, generating phylogenetic trees, or producing alignment output in various formats.

当设定新目标或检视现有目标时，确保目标能通过高效的行为系统自动达成

Applies TRIZ cross-domain analogical reasoning to find solutions from adjacent fields. Use when stuck on a problem and needing inventive perspectives.

COCO: Microsoft COCO: Common Objects in Context

Pose-conditioned generation on RunComfy via the `runcomfy` CLI. Routes across Kling 2-6 Motion Control Pro / Standard (transfer the motion / blocking of a reference video onto a target character), community Wan 2-2 Animate (audio-driven character animation with pose conditioning), and Z-Image Turbo ControlNet LoRA (pose-conditioned image generation from an OpenPose / DWPose / canny / depth control image). Picks the right route based on video vs still and stylized vs photoreal. Triggers on "controlnet", "control net", "pose control", "openpose", "DWPose", "transfer pose", "motion control", "pose driven", "character pose", "depth control", "canny edge", "use this pose", or any explicit ask to condition generation on a pose / skeleton / motion / depth / canny reference.

CogVLM: Visual Expert for Pretrained Language Models

Mantis: Interleaved Multi-Image Instruction Tuning

Specialist orchestrating codex exec / Antigravity CLI through dual paradigms — COMPETE (multi-variant comparison, select best) and COLLABORATE (decompose tasks across engines, integrate). Supports Solo/Team/Quick execution modes.

Find deepening opportunities in a codebase, informed by the domain language in CONTEXT.md and the decisions in docs/adr/. Use when the user wants to improve architecture, find refactoring opportunities, consolidate tightly-coupled modules, or make a codebase more testable and AI-navigable.

Use when aligning RNA-seq reads to a reference genome using graph-based indexing for fast and sensitive spliced alignment.

Quick feasibility and novelty check — go/no-go decision for this week's build

Chameleon: Mixed-Modal Early-Fusion Foundation Models

Strategic patterns for solving intractable problems through cascading approximation, self-improvement, and heterogeneous evaluation from DeepMind's AlphaGo system

Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md. Identifying inconsistencies, duplications, ambiguities, and underspecified items.

AutoAugment: Learning Augmentation Strategies from Data

Pose-conditioned generation on RunComfy via the `runcomfy` CLI. Routes across Kling 2-6 Motion Control Pro / Standard (transfer the motion / blocking of a reference video onto a target character), community Wan 2-2 Animate (audio-driven character animation with pose conditioning), and Z-Image Turbo ControlNet LoRA (pose-conditioned image generation from an OpenPose / DWPose / canny / depth control image). Picks the right route based on video vs still and stylized vs photoreal. Triggers on "controlnet", "control net", "pose control", "openpose", "DWPose", "transfer pose", "motion control", "pose driven", "character pose", "depth control", "canny edge", "use this pose", or any explicit ask to condition generation on a pose / skeleton / motion / depth / canny reference.

MaxFuse parameter tuning when protein panel size changes (26 → 59+ markers)

Use when performing genome arithmetic on interval files (BED, BAM, BEDGRAPH), including intersection, merging, coverage, format conversion, or sequence extraction.

Multimodal Neurons in Artificial Neural Networks

对两家及以上上市公司或股票进行横向研究，覆盖大盘与板块、外围市场、供应链、重要新闻与监管、商业模式、经营财务、成长、预期、估值、股价、组合以及 A/H 股与跨上市地相对价值。适用于公司比较、选股、财报或估值对比、股价与事件复盘、供应链或监管分析、组合适配、配对交易、H 股相对价值，以及需要飞书文档、高级金融图表或可复核多维报告的任务。

Turn "is this account a real fit?" into a stacked verdict. A composite 0-100 fit score built from every signal you have, a breakdown by source, override flags for when a scoring tool is wrong, a channel classification, and a written rationale. Built for reps, marketers, and RevOps, customizable to your CRM and whatever scoring you use. Trigger on "is {account} a real fit?", "score this list against our profile", "find lookalikes to our best customers", "why is the score wrong on {account}?", "validate this prospect list", "what's our coverage in {segment}?", or any account or list qualification.

Orchestrate parallel scientist agents for comprehensive analysis with AUTO mode

Create a customer journey map across stages, touchpoints, actions, emotions, and metrics to diagnose broken experiences and align teams on the full customer flow.