「lia」の検索結果

Design Health — runs 19 deterministic quality checks on HTML output. Use when the user says /reimagine-it audit, "audit this page", "check design quality", or wants to verify craft-floor compliance before shipping. Catches blank plates, missing focus rings, non-compositor motion, off-palette accents, dead motion, fabricated content. No LLM, no API key. CI-ready with --json and exit codes. Part of the reimagine-it Content-Derived Design suite.

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Standardized trade idea template, multi-method price target derivation PE and sales multiple approaches, GAAP to non-GAAP reconciliation, base bull bear scenario construction, investment thesis structuring, Zendesk-style case methodology

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Plan and scope production work with Odyssey's real-time interactive video world models (odyssey.ml — Odyssey-1/Odyssey-2/Starchild-1/Agora-1). Use when a request involves generating video that a user steers live with keyboard, text, speech, or controller input (streamed frames that respond in the moment), or when someone must decide between Odyssey-style interactive generation and offline clip generators (Sora/Veo/Kling) or downloadable 3D / game engines. Covers what is verified versus announced, current access routes, latency and coherence limits, feasible-now versus speculative use cases, pricing/access terms, and content/rights considerations. This is a fast-moving research-stage product; the skill teaches honest scoping, not a promise of production reliability.

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Use when an agent must make TwelveLabs do real video-understanding work: indexing footage, semantic/visual search across an archive, generating descriptions, summaries, chapters, highlights, and tags from video, producing multimodal embeddings, or wiring TwelveLabs into a media-production pipeline (NLE panels, logging, compliance review, metadata). Covers the current model families (Marengo for search/embeddings, Pegasus for video-to-text analysis), the v1.3 Video Understanding API (indexes, assets, tasks, search, analyze, embed), prompt construction for analysis, capability and format limits, pricing/quota math, output quality review (hallucination and timestamp accuracy), and privacy/rights obligations when footage shows real people. Not for generating or editing video pixels — this is analysis and retrieval.

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Generate, remix, edit, inpaint, reframe, background-process, describe, layerize, and upscale images with the Ideogram Developer API. Use when Codex must integrate Ideogram 4.0 or 3.0, render reliable typography or structured layouts, use style or character references, build synchronous or webhook workflows, migrate legacy Ideogram endpoints, or reason about Ideogram API pricing, safety, privacy, and production QA.

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Provider-independent production workflow for AI avatar spokesperson videos, including presenter briefs, consent and likeness rights, disclosure and platform labeling, casting, localization, performance direction, brand fit, claims review, lip-sync/audio QA, accessibility, approvals, and delivery packages. Use when creating synthetic presenter videos, corporate explainers, training modules, sales/support avatars, localization spokespeople, product announcements, compliance videos, or social avatar clips.

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Provider-independent production workflow for AI-assisted fashion campaigns, lookbooks, editorial fashion films, ecommerce/editorial hybrids, social cutdowns, virtual try-on assets, generated model/lifestyle ads, and retouched fashion visuals; use when an agent must plan, prompt, produce, review, localize, or deliver fashion imagery or video while preserving garment truthfulness, model consent, fit representation, claims substantiation, platform compliance, accessibility, and fashion QA.

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Provider-independent production workflow for AI agents creating brand launch films, product reveal videos, manifesto films, campaign hero films, website hero videos, investor/customer launch assets, and social cutdowns. Use when planning, scripting, generating, editing, reviewing, or delivering launch films that must align strategy, claims, brand voice, visual direction, product proof, accessibility, compliance, and multi-platform delivery.

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Provider-independent real estate media production for listing photos, virtual staging, property videos, walkthrough reels, floor-plan explainers, neighborhood clips, renovation concepts, agent ads, and generated or retouched property visuals. Use when creating, editing, reviewing, prompting, packaging, or approving real estate marketing content where property truthfulness, listing/MLS compliance, fair-housing risk, staging disclosure, privacy, accessibility, platform variants, or real-estate QA matter.

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Audit any Lattice SKILL.md for language compliance — removes rationale prose, converts soft language to imperatives, adds STOP: gates on hard rules, and cuts redundant repetition. Complements skill-review (which finds behavioral gaps) by fixing phrasing that causes agents to skip or underweight instructions at runtime. Use after writing or significantly changing any skill, or when the user says 'tighten this skill', 'clean up the language', 'make this more effective', 'reduce the bloat', 'tighten the language', or 'skill tighten'. Standalone — does not call other skills.

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Enforce architectural rules when generating or modifying code, and validate proposed designs before approval (design mode). Defaults to clean architecture; supports any architecture style via the architecture-refiner. Validates layer responsibilities, dependency direction, and structural constraints using the loaded architecture rules. Use when generating code, reviewing architecture, creating new files, or when the user mentions 'architecture', 'layers', 'structure', 'dependency rules', 'hexagonal architecture', 'ports and adapters', 'modular monolith', or 'onion architecture'. Also use when reviewing generated code for structural compliance.

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Apply test quality principles when generating or reviewing test code. Enforces Arrange-Act-Assert structure, one behavior per test, assertion quality, test isolation, meaningful naming, and test data management. Use when writing tests, reviewing test code, or when the user mentions 'write tests', 'test this', 'test quality', 'test review', 'improve tests', or 'test structure'. Loaded automatically by the code-generating molecules (code-forge, refactor-safely, bug-fix). This skill governs the craft of writing individual test cases -- not what to test (that is driven by the code being implemented) but how to write tests that are reliable, readable, and maintainable.

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Detects somatic mutations in circulating tumor DNA using variant callers optimized for low allele fractions with UMI-based error suppression. Reliably detects mutations at VAF above 0.5 percent using consensus-based approaches. Use when identifying tumor mutations from plasma DNA or tracking specific variants.

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Infer orthologous genes and gene families across species using OrthoFinder3 (HOG-based phylogenetic orthology), SonicParanoid2, Broccoli, ProteinOrtho, OMA / FastOMA hierarchical orthologous groups, eggNOG-mapper, JustOrthologs, and TOGA whole-genome-alignment orthology. Use when building single-copy ortholog sets for phylogenomics, classifying co-orthologs and in/out-paralogs after gene duplication, propagating functional annotation via orthology with awareness of the ortholog conjecture, distinguishing speciation from duplication via gene-tree species-tree reconciliation, computing Quest-for-Orthologs benchmark performance, or running synteny-aware ortholog detection in WGD-affected lineages.

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Detect somatic and germline copy number variants from targeted, exome, and whole-genome sequencing with CNVkit, a read-depth caller that combines on-target and off-target (antitarget) coverage. Covers panel-of-normals construction, flat-reference tumor-only calling, hybrid/amplicon/WGS modes, CBS vs HMM segmentation selection, purity-aware integer calling, and reconciliation against GATK and allele-specific callers. Use when calling CNVs from hybrid-capture panels or exomes, deciding whether CNVkit (depth-only) is the right tool versus an allele-specific caller, building a panel of normals, diagnosing flat-reference false positives, or interpreting log2 ratios into copy-number states.

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End-to-end CLIP-seq pipeline from FASTQ to ENCODE-compliant binding sites, single-nucleotide crosslink maps, annotation, motifs, and (optionally) differential binding. Use when running the full Yeo lab eCLIP / iCLIP / iCLIP2 / iCLIP3 / irCLIP / PAR-CLIP analysis with SMInput control, protocol-specific UMI extraction, ENCODE STAR parameters, CLIPper or Skipper peak calling with stringent log2 FC and -log10 p thresholds, IDR rescue and self-consistency QC, and downstream motif registration with mCross or PEKA.

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Comprehensive quality control for CLIP-seq libraries (eCLIP, iCLIP, iCLIP2, PAR-CLIP) covering library complexity (preseq), FRiP, IDR replicate reproducibility, read-distribution metagene, SMInput vs IgG control rationale, rRNA / snoRNA contamination, fragment-length distribution, and ENCODE-compliance thresholds. Use when assessing whether a CLIP library passed, deciding lenient vs stringent peak thresholds, comparing replicates with IDR rescue and self-consistency ratios, or distinguishing failed IP from over-amplified library.

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Infer cell-cell communication networks from scRNA-seq data using CellChat, NicheNet, and LIANA for ligand-receptor interaction analysis. Use when inferring ligand-receptor interactions between cell types.

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End-to-end clinical trial analysis workflow from CDISC SDTM/ADaM loading through ICH E9(R1) estimand-driven primary analysis to CONSORT 2025 regulatory-compliant reporting. Covers data preparation, FDA 2023 marginal vs conditional logistic regression, categorical tests with Boschloo, modern HTE/subgroup methods, missing-data sensitivity (MMRM, reference-based MI, Permutt tipping point), graphical multiplicity (Bretz-Maurer), survival analysis (Cox/RMST/competing risks) when applicable, and Table 1. Use when performing a complete analysis of clinical trial data.

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Trim multiple sequence alignments using ClipKIT, trimAl, BMGE, Divvier, or HMMcleaner with mode selection guidance per downstream goal. Use when removing unreliable columns or contaminating residues before phylogenetic inference, HMM building, or selection analysis.

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Reconstruct ancestral states at internal phylogenetic nodes for sequences (PAML codeml, IQ-TREE --ancestral, GRASP, FastML), discrete traits (corHMM hidden-rate Markov, ape::ace, phytools::make.simmap stochastic mapping, BayesTraits), and continuous traits (phytools::fastAnc, geiger Brownian/OU, RPANDA). Use when designing constructs for ancestral protein resurrection, tracing trait evolution along a tree, performing stochastic character mapping, testing models of trait evolution (BM vs OU vs EB), inferring ancestral genome content via Dollo or DTL reconciliation, or quantifying ancestral-state uncertainty for downstream comparative analyses.

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Infer integer allele-specific copy number, tumor purity, and ploidy from tumor sequencing by jointly modeling read depth (logR) and B-allele frequency (BAF) with ASCAT, Sequenza, FACETS, PURPLE, and PureCN (tumor-only). Covers the purity-ploidy identifiability problem, the diploid-baseline (dipLogR) anchor, major/minor copy number, loss of heterozygosity, sunrise/contour fit diagnostics, and reconciliation of conflicting fits. Use when tumor analysis needs absolute copy number rather than relative log2, when estimating purity and ploidy, calling LOH or copy-neutral LOH, resolving whole-genome doubling, running tumor-only allele-specific calling, or choosing among ASCAT, Sequenza, FACETS, and PureCN.

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Identify direct miRNA-target interactions from AGO HITS-CLIP, AGO-CLEAR-CLIP (chimeric reads), HEAP (Halo-Ago2 mouse), chimeric eCLIP / miR-eCLIP (deep miRNA-target profiling), or CLASH using chimeric-read processing pipelines, seed-pairing analysis, and 3' auxiliary pairing rules. Use when distinguishing direct miRNA targets from indirect, integrating CLIP-derived target maps with TargetScan / miRDB / DIANA predictions, applying canonical 7mer-8mer seed matching with 3' UTR context, or recovering miRNA-mRNA chimeras at scale.

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Protein design quality control, filtering thresholds, and ranking guidance. Use this skill when: (1) Evaluating design quality for binding, expression, or structure, (2) Setting filtering thresholds for pLDDT, ipTM, PAE, (3) Checking sequence liabilities (cysteines, deamidation, polybasic clusters), (4) Creating multi-stage filtering pipelines, (5) Computing PyRosetta interface metrics (dG, SC, dSASA), (6) Checking biophysical properties (instability, GRAVY, pI), (7) Ranking designs with composite scoring. This skill provides research-backed thresholds from binder design competitions and published benchmarks.

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