'fast' 검색 결과

Predict structures of protein, nucleic acid, and small-molecule complexes with ESMFold2, using single sequences or aligned related sequences. The skill also covers ESMC models for numerical sequence representations, mutation scoring, and predictions of contacts between residues.

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• Predicting complex structures from single sequences
• Assessing designed binders with ESMFold2-Fast
• Predicting structures using aligned related sequences

dontbesilent 慢就是快。帮创业者找到看起来更慢但长期更快的方法，用摩擦建造资产。 触发方式：/dbs-slowisfast、/慢就是快、「有没有更慢的方法」「我是不是太快了」 Slow-is-fast diagnosis. Help entrepreneurs find seemingly slower methods that build assets through friction. Trigger: /dbs-slowisfast, "is there a slower way", "am I going too fast"

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Fix "Requested backend named 'X' does not exist" or TLS alert errors in Fastly Compute@Edge. Use when: (1) Backend works locally but fails in production with "backend does not exist", (2) TLS alert received (alert_id=0) errors when calling external APIs from Fastly, (3) Backends defined in fastly.toml aren't available after deployment. The fastly.toml [[backends]] section only applies during initial service creation - existing services require backends to be added via CLI or API with proper SSL/SNI configuration.

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Fix "backend exists on a draft version but isn't reachable from the new Compute deploy" bugs after `fastly compute publish`. Use when: (1) You ran `fastly service backend create --autoclone` (or any dashboard/CLI change that creates a draft version) but did not activate that draft, (2) You then ran `fastly compute publish` which appeared successful but your backend / ACL / header / dictionary change is missing from the active version, (3) Compute code returns backend-not-found errors or misroutes requests, (4) You're surprised to see your draft version number "skipped over" in the version chain. Root cause: `fastly compute publish` clones from the currently-active version, not from the latest draft, so dashboard changes made in an un-activated draft get stranded.

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FastAPI web framework conventions: APIRouter with prefix/tags/dependencies, Pydantic v2 schemas (BaseModel, model_config, field_validator, model_validator), dependency injection with Depends, async SQLAlchemy session yielding, OAuth2PasswordBearer + JWT auth, lifespan context manager, pydantic-settings configuration, OpenAPI customization, and HTTPException error handling. Activated automatically by fastapi-plugin/stack.md. Use this skill to: - Structure FastAPI apps with per-feature APIRouter modules and a central app factory. - Write Pydantic v2 request and response schemas with proper validators. - Build a reusable Depends-based dependency chain for DB session, auth, and pagination. - Implement JWT-based authentication with get_current_user dependency. - Configure the app from environment variables via pydantic-settings. Do NOT use this skill for: - SQLAlchemy ORM model configuration and Alembic migrations — see fastapi-plugin:sqlalchemy-patterns. - Python language idioms — see python-foundation:python-conventions. - Testing patterns — see python-foundation:pytest-testing.

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Automates Flutter iOS and Android deployment using Fastlane. Use when setting up `fastlane match` for iOS certificate and provisioning profile management, automating TestFlight uploads via `upload_to_testflight`, pushing Android releases to Google Play via `upload_to_play_store`, auto-incrementing build numbers, writing Fastfile lanes for Flutter release workflows, integrating Fastlane with GitHub Actions or Codemagic, or configuring App Store Connect API Key and Google Play Service Account JSON credentials.

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非同期パターン、依存性注入、包括的なエラー処理を備えた本番環境対応のFastAPIプロジェクトを作成。新しいFastAPIアプリケーションの構築またはバックエンドAPIプロジェクトのセットアップ時に使用。

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Implement Python services for Azure Cosmos DB NoSQL with guidance for authentication, data models, database operations, and tests. Separate business logic from storage access, validate data access permissions, and use reusable templates for consistent implementation.

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• Adding Cosmos DB storage to a FastAPI application
• Separating database access from business logic
• Configuring Azure and local emulator authentication

Reduce LLM weight usage through pruning, which removes selected model parameters. Explore Wanda and SparseGPT for compression without retraining, choose hardware-friendly patterns for faster inference, and compare the compressed model's accuracy with the original.

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• Compressing an LLM without retraining
• Comparing pruning methods
• Exploring faster inference on supported hardware

Build transcription workflows for uploaded or stored audio and video using Zoom AI Services Scribe. Consult guidance on authentication, single-file requests, batch jobs, completion notifications, and saving transcript results for further processing.

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• Adding transcription for uploaded recordings
• Transcribing stored call archives in batches
• Saving transcripts after job completion notifications

Get guidance on fine-tuning language models with Unsloth, including LoRA and QLoRA methods for training with fewer resources. The skill points to documentation for understanding APIs, implementing training code, debugging problems, and exploring speed and memory optimizations.

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• Exploring faster training with lower memory use
• Learning about LoRA and QLoRA fine-tuning
• Checking Unsloth features and APIs

Find the right workflow for next-generation sequencing data by inspecting files and clarifying only missing setup details. Receive a recommended analysis skill, checks of available tools, and plans for software installation and reference data.

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• Choosing an analysis workflow from sequencing files
• Clarifying requirements for RNA-seq or variant analysis
• Checking tools and preparing an installation plan

Design protein sequences while accounting for bound small molecules, nucleic acids, or metals. Use LigandMPNN to redesign binding pockets or metal-coordinating sites, and export sequence files alongside PDB structures with the designed sequences applied.

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• Redesign a binding pocket around a small molecule or cofactor
• Design residues around a metal-coordinating site
• Export designed sequences as FASTA and PDB files

Predict three-dimensional structures of complexes containing proteins, RNA, DNA, and small molecules with Chai-1. Compare candidate structures using confidence scores and clash indicators, or run repeated predictions from Python to evaluate designed binders.

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• Predicting antibody–antigen complex structures
• Evaluating protein–ligand binding structures
• Reassessing designed binders

Inspect scientific data files to understand their format, structure, and quality. Covering over 200 formats, this skill produces Markdown reports with statistical summaries, potential issues, and recommendations for preprocessing, visualization, and further analysis.

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• Inspecting an unfamiliar scientific data file
• Checking missing values and duplicates in experimental tables
• Reviewing sequence lengths and quality scores in FASTQ files

Generate OpenAPI 3.0.3 specifications, a standard format for describing APIs, from route definitions in supported web frameworks. Extract paths, HTTP methods, parameters, and available model information into JSON or YAML for Swagger UI or Redoc.

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• Generating an API specification from source code
• Listing existing API endpoints
• Preparing specifications for Swagger UI or Redoc

All-in-one read preprocessing with fastp including adapter trimming, quality filtering, deduplication, base correction, and HTML report generation. Use when preprocessing Illumina data and wanting a single fast tool instead of separate Cutadapt, Trimmomatic, and FastQC steps.

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Reapply and repair Windows Codex Desktop after Store upgrades, including custom provider models hidden by Statsig available_models filtering, the dependent blue-purple Power slider and its Ultra toggle, Fast Mode request/UI gates, locale i18n, plugin UI gates, Chrome/browser_use gates, Goal command gates, Windows Computer Use availability gates and plugin/runtime repair, phone remote-control pairing under third-party/API-key main app usage, Desktop dynamicTools/inputSchema thread-start schema drift, local conversation visibility recovery after model_provider switches, restored-conversation missing-cwd continuation repair, ASAR integrity repair, signing/installing patched MSIX packages, SDK cleanup, Fast Mode wire verification, local plugin marketplace registration, and optional custom model_instructions_file setup (the bundled system prompt, also called 听话水).

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Build MCP servers in Python with FastMCP. Define tools / resources / prompts, build the server, test locally, deploy to FastMCP Cloud or Docker. Use whenever the user mentions building an MCP server, exposing tools to LLMs, FastMCP, building a Claude integration, or troubleshooting FastMCP module-level server, storage, lifespan, middleware, OAuth, or deployment errors.

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Diagnoses why your product team ships slowly and produces a velocity plan with a baseline, a bottleneck map, the top 3 interventions and a stop-doing list. Use it when you say 'we're too slow', 'how do we ship faster', 'projects keep slipping', 'too many meetings', 'approvals take forever', 'our releases are scary', 'velocity', 'cycle time', 'we hired more people and nothing got faster' or 'AI made coding fast but we still ship slowly'. Draws on 226 Lenny's Podcast guests including Farhan Thawar, Nicole Forsgren and Melissa Perri.

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All-in-one FASTQ QC and adapter trimming. Auto-detects Illumina adapters, filters low-quality reads, corrects paired-end overlaps, emits HTML+JSON QC in one pass. 3-10x faster than Trim Galore/Trimmomatic. First step before STAR, BWA-MEM2, or Salmon.

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Fix wildcard subdomain routing for Fastly Compute@Edge services when subdomains resolve but return 500 "Domain Not Found" or empty responses. Use when: (1) TLS subscription "issued" but edge serves default certificate (CN=j.sni-644-default), (2) Fastly domain-v1 create succeeds but subdomain returns 500, (3) Static publisher/PublisherServer returns empty content for subdomain requests, (4) DNS wildcard CNAME resolves to wrong target. Covers TLS configuration SNI endpoint selection (x.sni vs j.sni vs w.sni), DNS trailing dot issues, Fastly domain-v1 activation, and reading from KV store directly when PublisherServer fails for subdomains.

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Debug Fastly Compute services where code changes don't affect behavior due to multi-service routing architecture. Use when: (1) deployed changes have no effect, (2) unexpected redirects persist after code updates, (3) DNS resolves to Fastly but responses don't match deployed code, (4) `fastly service list` shows multiple related services. The root cause is often a routing/gateway service intercepting requests before they reach your content service.

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Debug Fastly Compute deployments that appear successful but return stale/wrong responses. Use when: (1) fastly compute publish succeeds but version check shows old version, (2) new endpoints return 404 after deployment, (3) cache-busted requests work but regular requests fail, (4) fastly domain list doesn't show your custom domain. Covers edge propagation timing, cached error responses, and domain management API differences.

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