「diff」の検索結果

Think and work like an expert Crystallographer. Use when a task calls for Crystallographer judgment. Reasons from reciprocal-space diffraction data, Bragg's law, and space-group symmetry through XDS/DIALS scaling, Phaser/SHELX phasing, Coot/Olex2 building, and MolProbity/checkCIF validation while treating merohedral twinning, wrong space groups, model-bias density unsupported by omit/polder maps, and R_free overfitting as first-class failure modes.

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Think and work like an expert Cellular Neuroscientist. Use when a task calls for Cellular Neuroscientist judgment. Treat the neuron as a cable with active channels, not a point integrator unless you have shown it is one for your question. Separate voltage, calcium, and fluorescence observables. GCaMP reports Ca²⁺-driven fluorescence with indicator kinetics; it is not membrane potential. FRET sensors (ArcLight, ASAP) trade speed and dynamic range differently.

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Think and work like an expert Civil Engineer. Use when a task calls for Civil Engineer judgment. Reasons from load paths, factored load combinations, soil-structure interaction, and governing limit states through ASCE 7, ACI 318, AISC 360, and tools like SAP2000/ETABS, PLAXIS, and HEC-RAS while treating missing load paths, connection and foundation failures, differential settlement, and unvalidated FEA as first-class failure modes.

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Think and work like an expert Catalysis Scientist. Use when a task calls for Catalysis Scientist judgment. Reasons from active-site structure, turnover frequency, selectivity, and the Sabatier principle through CO/H2 chemisorption site-counting, Weisz-Prater and Mears transport checks, Langmuir-Hinshelwood/Mars-van Krevelen kinetics, and operando DRIFTS/XAS while treating diffusion-limited apparent rates, DRIFTS spectator species, mercury-test false positives for leached Pd, sintering, coking, and selectivity collapse at high conversion as first-class failure modes.

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Think and work like an expert Applied Mathematician. Use when a task calls for Applied Mathematician judgment. Reasons from formulation-first modeling, Buckingham scaling, and asymptotics (matched expansions, boundary layers) through FEM/FVM numerics (FEniCS, PETSc, LAPACK), Tikhonov inverse problems, and ASME/Sandia V&V while treating ill-posed inversion, stiffness, and numerical diffusion as first-class failure modes.

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Think and work like an expert Astronomical Instrumentation Scientist. Use when a task calls for Astronomical Instrumentation Scientist judgment. Reasons from system-level error budgets, the diffraction limit and Strehl ratio, detector figures of merit, and resolving power through Zemax/Code V tolerancing, ETC radiometry, AO modeling, and on-sky standard-star commissioning while treating flexure drift, IR persistence, ghosts, and quasi-static speckles as first-class failure modes.

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Think and work like an expert Acoustics Physicist. Use when a task calls for Acoustics Physicist judgment. Reasons from impedance Z=p/u, Helmholtz number kL regime, and the sonar equation SL-TL-NL+DI+PG through impedance tubes (ISO 10534), anechoic and reverberation rooms, laser vibrometry, and k-Wave/COMSOL simulation while treating edge diffraction inflating absorption above one, near-field versus far-field confusion, flanking and multipath paths, and amplifier clipping mistaken for nonlinearity as first-class failure modes.

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Think and work like an expert Anesthesiologist. Use when a task calls for Anesthesiologist judgment. Reasons from control of consciousness, analgesia, autonomic response, and oxygen delivery through the ASA Difficult Airway Algorithm, capnography and arterial-waveform trends, quantitative TOF monitoring, and ASRA/ERAS protocols while treating cannot-ventilate airways, local anesthetic systemic toxicity, malignant hyperthermia, and residual neuromuscular blockade as first-class failure modes.

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Captions living in 3D space around a talking head: a camera flies between the speaker and the words (whip-in, parallax truck, push), caption groups sit at different depths so camera moves pull them apart, hero words hide BEHIND the speaker through an alpha matte, a ring of words wraps round the speaker and turns in front of them, focus racks between depths, and text steps at 15 fps with ghost motion blur. Works in any type style (editorial serif, bold sans) or hand-drawn (p5.brush write-on). Trigger on: "3D text", "3D camera captions", "text around / behind the speaker", "camera moves through the text", "depth captions on my avatar video". Covers prep (portion, padded plate, matte, word clock, font metrics), the shot grammar, depth rules, QC, and limits.

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Pixel Path turns any two places (optionally via waypoints) into a pixel-art fly-through of the real road. It routes the trip, bakes the real buildings, land cover, landmarks, hills and horizon from OpenStreetMap and elevation data, generates scenery art with RetroDiffusion at a chosen level of detail (sparse, moderate or detailed; estimated up front, quoted exactly for free, budget-capped; free placeholder art also works), builds a page where you zoom along the route and scroll to go faster or slower, and runs a self-check that screenshots the result. Use when someone asks for a "pixel path", a "pixel road trip", to "drive" or "fly" from X to Y in pixel art, or a retro first-person view along a real route.

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Design DNA capture — extracts palette, type stack, motifs, motion, and 3D signatures from a shipped HTML file and saves them as a reusable reference pack. Use when the user says /reimagine-it lock, "lock this design", "save design DNA", "capture this look", or wants to reuse a shipped design on a different target. Locks capture palette, type, motif, and motion from a shipped HTML file. Part of the reimagine-it Content-Derived Design suite.

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Decompose the plan into research tasks — one task per ticker × skill × mode, grouped by pillar, [P]-marked by the different-files-and-no-incomplete-deps rule, with source-refs. mode: all expands to N tasks at generation, never exists as one task (Q79).

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Medicines pipeline analysis over structured universes: Phase I-III assets with probability-of-success discipline (unadjusted peak x POS = modeled value; POS changes logged with reasons), trial status-diff tracking, and mechanism/competitor mapping via drug-knowledge lookups.

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Select, integrate, and operate multi-model video-generation gateways — hosted inference aggregators such as fal.ai, Replicate, and WaveSpeed that expose many third-party video (and video-adjacent audio) models behind one account, one API surface, and one bill. Use when deciding whether to route video generation through a gateway versus a direct model-provider API; when comparing gateways on catalog, async/queue job design, webhooks, pricing, schema discovery, and version pinning; and when operating gateway workloads in production — spend controls, retries, cross-gateway failover, content- safety differences, data retention, and commercial-rights passthrough of the underlying model. Not for direct model-provider APIs, local/self-hosted inference, model training/fine-tuning, or image-only gateway use.

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Produce speech and clone voices with Fish Audio — its hosted TTS API (S2.1-Pro / S2-Pro / S1 model lineup, REST + WebSocket streaming, instant and persistent voice cloning) and its open-weight OpenAudio S1-mini / Fish-Speech models for self-hosting. Use this skill when an agent must generate narration or dialogue through Fish Audio, choose between Fish Audio's hosted models and open weights, clone a voice from reference audio, author emotion/tone/special markers for expressive delivery, estimate cost from UTF-8 bytes, wire real-time streaming for a voice agent, decide whether self-hosting beats the API, or review Fish Audio TTS output for production. Do not use it to pick a different provider — it covers Fish Audio specifically.

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Operate Stability AI image generation, image-to-image, edit, control, background, and upscale APIs safely and reproducibly. Use when selecting or calling Stable Image Ultra, Core, Stable Diffusion 3.5, v2beta image edit/control services, or Stability open-weight image models; when debugging schemas, moderation, rate limits, cost, lifecycle, licenses, privacy, provenance, or migrations; and when planning production QA for Stability-generated images.

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Full enhancement pipeline for an existing Lattice skill — rewrites a molecule or atom to modern-capable-model grade: restores degraded grammar, deduplicates, hardens gates and branching to one-unambiguous-action precision, verifies zero behavioral loss against a pre-capture diff, then runs the combined QA gate (skill-review, skill-tighten, skill-validate) and an independent fresh-context verifier, fixing everything found. Consumer-first: optimized for first-time open-source users on fresh repos with minimal .lattice/ setup, running capable models. Use when the user says 'enhance this skill', 'upgrade this molecule', 'modernize this skill', 'optimize this skill', 'make this skill production grade', 'full enhancement', 'polish this molecule like design-blueprint', or names a molecule/atom to overhaul. For gap-finding only use skill-review; for conventions only use skill-validate — this skill runs the whole loop end to end.

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Deep behavioral audit of a Lattice skill — proposes 3 review personas relevant to the skill, runs independent scenario analysis from each persona's perspective, then merges only the high-confidence, practical findings into a severity-ordered gap report with proposed fixes. Structural validation (conventions, cross-references) is skill-validate's job — this skill finds gaps that would realistically surface when someone actually uses the skill: missing scenario handling, ambiguous instructions, silent failure cases, and behavioral inconsistencies. Filters out theoretical edge cases, low-likelihood speculation, and findings owned by other skills. Use after writing or significantly changing any skill, or when the user says 'review this skill', 'deep review', 'does this skill work', 'find gaps in this skill', 'stress test this skill', 'review from different angles', or 'skill review'. Standalone — does not call other skills.

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Convert between sequence file formats (FASTA, FASTQ, GenBank, EMBL) using Biopython Bio.SeqIO. Use when changing file formats or preparing data for different tools.

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Detect transcription factor binding footprints in ATAC-seq using TOBIAS, HINT-ATAC, Wellington, or scprinter. Use when identifying bound TF sites within accessible regions, correcting Tn5 insertion bias before footprinting, choosing between cleavage-based and aggregate-based footprinters, or comparing differential TF activity between conditions.

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Perform differential expression analysis using edgeR in R/Bioconductor. Use for analyzing RNA-seq count data with the quasi-likelihood F-test framework, creating DGEList objects, normalization, dispersion estimation, and statistical testing. Use when performing DE analysis with edgeR.

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Workflow from differential expression results to functional enrichment analysis. Covers GO, KEGG, Reactome enrichment with clusterProfiler and visualization. Use when taking DE results to pathway enrichment.

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Quality control and exploration of RNA-seq count matrices before differential expression. Check for outliers, batch effects, and sample relationships. Use when assessing count matrix quality before DE analysis.

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Analyzes CUT&RUN (Skene Henikoff 2017) and CUT&Tag (Kaya-Okur 2019) chromatin profiling data. Handles SEACR vs MACS2 peak calling (with the btaf375 2025 benchmark guidance), pA-MNase vs pA-Tn5 vs pAG-Tn5 chimera differences, E. coli spike-in carryover normalization, IgG-only control logic (no input), characteristic fragment-size signatures (25-75 bp for CUT&Tag), and lower depth requirements (5M reads typical vs 25M for ChIP). Use when calling peaks from CUT&RUN/CUT&Tag, scaling by E. coli spike-in carryover, choosing SEACR norm mode, or comparing CUT&RUN/Tag results to traditional ChIP.

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