2.4천건 · 관련도순
Use when starting feature work that needs isolation from current workspace or before executing implementation plans - creates isolated git worktrees with smart directory selection and safety verification
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Author pull requests with intent-separated commits, blast-radius disclosure, and verification evidence. Load when opening a PR, writing a PR description, separating refactor from feature commits, or summarizing a change set for review. Also triggers on "write the PR", "PR body", "intent-separated commits", "split refactor from feature", "pr summary", or after safe-change cycles complete. Extends git-workflow-and-versioning — does not replace it.
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Fix broken or failing functionality through structured reproduction, root-cause analysis, minimal fix, and verification. Load when the user asks to fix a bug, debug an error, resolve an issue, or work on a Linear ticket. Also triggers on "this is broken", "fix this bug", "why is this failing", "debug this", "resolve this error", "what went wrong", or any request to diagnose and fix a problem.
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Build the smallest, highest-signal context package for an AI coding task — goal, constraints, repo facts, boundaries, and a verification plan. Load when prompts are underspecified, the agent is missing key files or decisions, the user says "use the right context", "here's the repo", or when work is drifting due to missing constraints. Also triggers on "context engineering", "gather context", "what do you need from me", "before you start". Not for cross-session continuity (use memory-startup/memory-recall).
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Test and debug browser UIs using Chrome DevTools MCP — DOM inspection, console errors, network requests, performance traces, and visual verification. Load when building or debugging anything that renders in a browser, verifying a UI fix, profiling Core Web Vitals in a real page, or the user asks for browser testing with DevTools. Requires chrome-devtools MCP configured. Not for backend-only or CLI work. Pairs with frontend-design and performance-optimization.
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Required reference for Prisma ORM 7 SQL driver adapter work. Use when implementing or modifying adapters, adding database drivers, or touching SqlDriverAdapter, Transaction, savepoint, result mapping, or DriverAdapterError behavior. Covers current transaction lifecycle, optional savepoint hooks, original database-error preservation, and verification.
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Run large codebase migrations and multi-file refactors. Uses the Composio CLI to coordinate issue tracking, batched PRs, and CI verification while the agent executes the transforms locally across hundreds of files.
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Azure Key Vault Keys SDK for .NET. Client library for managing cryptographic keys in Azure Key Vault and Managed HSM. Use for key creation, rotation, encryption, decryption, signing, and verification.
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Use when a coding task should be driven end-to-end from issue intake through implementation, review, deployment, and acceptance verification with minimal human re-intervention.
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Download genome assemblies, gene records, and ortholog data from NCBI using the modern Datasets v2 CLI (replaces assembly_summary.txt scraping and many EFetch workflows). Use when bulk-pulling genome assemblies, gene metadata across species, ortholog sets, or BLAST databases; when E-utilities are too slow for genome-scale work; or when automatic checksum verification, parallel download, and clean accession-driven retrieval are required. Encodes the JSON-lines output format, dataformat conversion, --dehydrated for cloud workflows, and when Datasets is/isn't the right tool.
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Download large datasets from NCBI efficiently using EPost, history server, batching, rate limiting, and retry logic. Use when bulk-fetching tens of thousands of sequences, pulling all results of a large ESearch, designing reproducible pipelines, comparing E-utilities to NCBI Datasets v2 CLI, or implementing checksum-validated downloads. Encodes WebEnv TTL (~8h), EPost 200-ID limit, retmax caps, parallelization design, and integrity verification.
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Quality control for pooled CRISPR screens covering library representation, Gini index, log-skew, replicate Pearson and Spearman concordance, essentialome precision-recall AUC against CEGv2 (Hart 2017), Cas9 cut-toxicity diagnostics, copy-number amplicon detection (Aguirre 2016 / Munoz 2016), bottleneck propagation through plasmid pool, infection, selection, and endpoint stages, MOI verification, and DepMap-style screen-quality scoring. Use when assessing screen quality before hit calling, deciding whether to repeat or rescue a screen, diagnosing low-confidence hits, choosing between MAGeCK / BAGEL2 / Chronos based on quality grade, picking a normalization strategy from QC signatures, or evaluating whether an in-vivo screen retained adequate library complexity.
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Assesses RNA-seq data quality specifically for alternative splicing analysis. QC layers include experimental design audit (library prep, read length, depth, replicates), STAR 2-pass cohort-style alignment, junction saturation curves and discovery plateau detection, novel-vs-known junction ratio diagnostics, junction-overhang distribution, splice-site strength scoring (MaxEntScan intrinsic + SpliceAI context-aware), strandedness verification, GENCODE basic vs comprehensive choice, and rRNA contamination screening. Splicing analysis is more demanding than DGE on read length, depth, library prep, alignment strategy, and annotation choice — failures silently bias PSI estimates and inflate novel-junction false positives. Use when evaluating data suitability for splicing analysis, troubleshooting low event detection, or designing sequencing experiments where AS is a primary endpoint.
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Add MAUI DevFlow to a .NET MAUI project with agent package references, MauiProgram.cs registration, Blazor WebView support, GTK variants, Central Package Management guidance, and verification commands. USE FOR: first-time DevFlow setup, reviewing what files to edit, choosing DevFlow packages, or continuing after `maui devflow init` installs skills. DO NOT USE FOR: troubleshooting an already-integrated app that cannot connect, iterative app debugging, UI inspection, or generic MAUI build failures (use maui-devflow-debug). INVOKES: maui devflow CLI and dotnet CLI.
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Use this skill when buying a used tractor or trailer. Covers verifying compliance status, hidden issues, and what to inspect before signing.
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Use this skill to understand how IFTA quarterly mileage is calculated. Covers measurement methods, manual vs ELD-derived, and verification.
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Use this skill when the user asks about onboarding a new CDL driver — pre-hire process, day-zero requirements, application + DQF setup, road test, drug & alcohol pre-employment, Clearinghouse Full query, MVR initial pull, PSP report, ELDT verification, sequence of activities + timing, and what NOT to do (handing keys before testing complete). Cite 49 CFR 391, 382.
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Refute-before-prove research discipline: automated counterexample sweeps before any formalization, meter-integrity audits for information-bound experiments, mutation-tested model checkers, pre-registered commit-or-cut gates for speculative directions, wrong-turn reporting, and numeric-claim provenance. Use when validating any new theorem, bound, equilibrium, or security claim; when building or trusting a checker, simulator, or experiment; or when deciding whether a speculative research direction lives or dies. NOT for exploratory brainstorming, product prioritization, writing style, or literature review.
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Build face recognition systems with InsightFace, ArcFace, enrollment pipelines, HDBSCAN clustering, and privacy-compliant architecture. Activate on: face recognition, face enrollment, face clustering, identity verification, facial search. NOT for: general object detection (computer-vision-pipeline), emotion analysis (ai-engineer).
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Cloudflare Pages and Workers deployment checklist for wrangler deploys, secret audits, D1 migrations, Worker-compatible SDK checks, and browser-auth verification. Use when shipping Cloudflare changes to production. NOT for general CI/CD architecture, non-Cloudflare deployments, or post-launch UX QA.
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Practical incident-response runbook for a suspected or confirmed ComfyUI / GPU-daemon compromise. Triage, scope, contain, forensic collection, weight-integrity verification, rebuild from clean snapshot, postmortem. NOT for hygiene scans on a healthy box (use supply-chain-defense-for-ml-extensions), and NOT for runtime hardening of a fresh deployment (use gpu-hosted-asset-hardening).
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Produces a narrow-interval quality signal for a WinDAGs skill that a third party can verify without inspecting model weights or method internals. The mechanism is attribution-kNN over a tamper-evident outcome log (task→skills→accept/reject store), combined with a conformal-prediction calibration certificate that provides a formal coverage guarantee. Thompson/Beta sampling is explicitly rejected as a category error: it produces a selection signal for stationary i.i.d. rewards, not an attestation signal for context-dependent LLM output quality. The resulting bundle — outcome-log Merkle root + conformal threshold + optional TEE guardrail signature — constitutes a "narrow-interval trust" credential: verifiable, bounded, and internals-opaque.
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Audit a compliance-ladder design (C0-C6) and transcript-fidelity ladder (T0-T5) plus their adapter conformance fixtures — Codex, Claude Code, Cloudflare, Ollama/LM Studio, custom stdio/HTTP agents — for the two failure modes that make a C-badge or T-fidelity label a lie: the ladder disagreeing with itself across doc/schema/ui/probe surfaces, and a level being reachable by self-report because no daemon-witnessed negative probe actually tries to forge it. Use when designing or freezing a compliance ladder, wiring an adapter conformance probe suite, deciding whether a numeric C-badge or T-label is safe to ship, or investigating a self-attestation or observed-to-controlled bypass risk. NOT for auditing a cryptographic protocol or whitepaper for adversarial soundness (`redteam-review`), writing TLA+/formal invariants for a daemon monitor (`runtime-verification-for-agents`), or agent identity, successor linkage, and reputation across restarts (`agent-identity-continuity-reputation`).
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Design a normalized, machine-readable "work receipt" that answers what changed, why, by whom, and with what validation, for any AI-coding-agent task regardless of backend (Claude Code, Codex, Cursor, Aider, CI, or homegrown). Use when defining a receipt schema, normalizing heterogeneous agent logs into one evidence shape, gating PR merges on artifact-backed proof, or designing an OSS maintainer's fast-reject/fast-merge workflow. NOT for validating a DAG node's output against its own schema (use output-contract-enforcer), continuous runtime monitoring of a live coordination daemon (use runtime-verification-for-agents), or general Port Daddy claims/notes/salvage mechanics (use port-daddy-agent-skill).
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