「zero」の検索結果

Plans Convex schema and data migrations with widen-migrate-narrow and @convex-dev/migrations. Use for breaking schema changes, backfills, table reshaping, or zero-downtime rollouts.

日本語の概要は準備中です。原文の説明を表示しています。

Build content-focused websites with Astro — zero JS by default, islands architecture, multi-framework components, and Markdown/MDX support.

日本語の概要は準備中です。原文の説明を表示しています。

Memory is the cornerstone of intelligent agents. Without it, every interaction starts from zero. This skill covers the architecture of agent memory: short-term (context window), long-term (vector stores), and the cognitive architectures that organize them.

日本語の概要は準備中です。原文の説明を表示しています。

Fighter-jet / helicopter head-up display: phosphor green on near-black, all-caps data overlays, angular geometry. Zero ambiguity at speed and altitude. For flight-sim UIs, telemetry, and command-and-control displays.

日本語の概要は準備中です。原文の説明を表示しています。

Magazine-grade, collage-driven editorial system: warm paper canvas, surreal plaster-and-architecture imagery, oversized display type, hairline rules, and Roman-numeral section markers.

日本語の概要は準備中です。原文の説明を表示しています。

Plan and execute database migrations, data transformations, and system migrations safely with rollback strategies and data integrity validation. Use when migrating databases, transforming data schemas, moving between database systems, implementing versioned migrations, handling data transformations, ensuring data integrity, or planning zero-downtime migrations.

日本語の概要は準備中です。原文の説明を表示しています。

When the user wants to optimize content for AI search engines, get cited by LLMs, or appear in AI-generated answers. Also use when the user mentions 'AI SEO,' 'AEO,' 'GEO,' 'LLMO,' 'answer engine optimization,' 'generative engine optimization,' 'LLM optimization,' 'AI Overviews,' 'optimize for ChatGPT,' 'optimize for Perplexity,' 'AI citations,' 'AI visibility,' 'zero-click search,' 'how do I show up in AI answers,' 'LLM mentions,' or 'optimize for Claude/Gemini.' Use this whenever someone wants their content to be cited or surfaced by AI assistants and AI search engines. For traditional technical and on-page SEO audits, see seo-audit. For structured data implementation, see schema-markup.

日本語の概要は準備中です。原文の説明を表示しています。

Design finalization: generates production-quality Pretext-native HTML/CSS. Works with approved mockups from /design-shotgun, CEO plans from /plan-ceo-review, design review context from /plan-design-review, or from scratch with a user description. Text actually reflows, heights are computed, layouts are dynamic. 30KB overhead, zero deps. Smart API routing: picks the right Pretext patterns for each design type. Use when: "finalize this design", "turn this into HTML", "build me a page", "implement this design", or after any planning skill. Proactively suggest when user has approved a design or has a plan ready. (gstack) Voice triggers (speech-to-text aliases): "build the design", "code the mockup", "make it real".

日本語の概要は準備中です。原文の説明を表示しています。

Chief Security Officer mode. Infrastructure-first security audit: secrets archaeology, dependency supply chain, CI/CD pipeline security, LLM/AI security, skill supply chain scanning, plus OWASP Top 10, STRIDE threat modeling, and active verification. Two modes: daily (zero-noise, 8/10 confidence gate) and comprehensive (monthly deep scan, 2/10 bar). Trend tracking across audit runs. Use when: "security audit", "threat model", "pentest review", "OWASP", "CSO review". (gstack) Voice triggers (speech-to-text aliases): "see-so", "see so", "security review", "security check", "vulnerability scan", "run security".

日本語の概要は準備中です。原文の説明を表示しています。

Set up gbrain for this coding agent: install the CLI, initialize a local PGLite or Supabase brain, register MCP, capture per-remote trust policy. One command from zero to "gbrain is running, and this agent can call it." Use when: "setup gbrain", "connect gbrain", "start gbrain", "install gbrain", "configure gbrain for this machine". (gstack)

日本語の概要は準備中です。原文の説明を表示しています。

Guides generic vs trait object decisions in Rust. Use when choosing between static and dynamic dispatch, designing traits, handling E0277/E0038, or deciding between enum and dyn Trait.

日本語の概要は準備中です。原文の説明を表示しています。

Guided first-run that produces a real verified win in under five minutes using the skill library on a seeded offline fixture. Load when a new user asks how to start, run the demo, try agent-loom, or get a quick win. Also triggers on "quickstart", "first run", "demo agent-loom", "try the skills", or onboarding to the library. Zero external credentials required. Idempotent — safe to run multiple times.

日本語の概要は準備中です。原文の説明を表示しています。

Deprecate APIs, features, or systems safely — announce, migrate consumers, sunset on a timeline, and document alternatives. Load when removing an old API, migrating users between implementations, sunsetting a feature, or the user asks about deprecation policy, migration guides, or breaking changes. Not for deleting dead code with zero consumers (use code-simplification). Distinct from meta `deprecate-skill` (skill library retirement).

日本語の概要は準備中です。原文の説明を表示しています。

Build content-focused websites with Astro — zero JS by default, islands architecture, multi-framework components, and Markdown/MDX support.

日本語の概要は準備中です。原文の説明を表示しています。

Reads, queries, and writes bigWig indexed binary signal tracks (coverage, fold-change, conservation, methylation-rate) with pyBigWig (Python) and the UCSC Kent tools (bedGraphToBigWig, bigWigToBedGraph, bigWigInfo, bigWigSummary, bigWigAverageOverBed) and deepTools (multiBigwigSummary, computeMatrix, bigwigCompare). Covers the central trap that a wide query returns a precomputed zoom-level summary (by default the mean, which annihilates narrow peaks) not per-base data, when exact=True/values() is mandatory, the NaN-not-zero gap-handling fork, choosing mean vs max vs sum vs coverage by biological question, and the sorted-bedGraph plus chrom.sizes build requirement. Use when extracting signal at regions, computing mean signal per gene/peak, building a browser track from bedGraph, comparing tracks, or building TSS/gene-body metaprofiles.

日本語の概要は準備中です。原文の説明を表示しています。

Parses, queries, converts, and extracts from GTF and GFF3 gene-model annotation files - walking the gene/transcript/exon/CDS hierarchy with gffutils (queryable SQLite DB), converting formats and extracting transcript/CDS/protein FASTA with gffread, slurping to dataframes with gtfparse/pyranges, and sanitizing malformed files with AGAT. Covers the 1-based-inclusive vs 0-based BED coordinate conversion (start-1 only), deriving implicit features (introns/UTRs/TSS), phase-not-frame, the stop-codon-in-or-out-of-CDS convention, and the chr1-vs-1 seqid and gene-ID-version mismatches that silently produce all-zero count matrices and dropped joins. Use when extracting features or sequences from an annotation, converting GTF<->GFF3 or GTF->BED, traversing the gene tree, or diagnosing a coordinate/provenance mismatch upstream of counting or DE.

日本語の概要は準備中です。原文の説明を表示しています。

Extracts, filters, annotates, and exports differential expression results from DESeq2 or edgeR with proper handling of padj=NA (independent filtering, Cook's outliers, all-zero), multiple-testing correction choice (BH vs Storey q-value vs IHW vs lfsr), TREAT vs post-hoc fold-change filtering, p-value histogram diagnostics, gene annotation via org.db/biomaRt/mygene, GSEA preranked input, ORA background construction, replication reality (Schurch 2016 small-n result), and SABV/sex-stratified reporting. Use when extracting and interpreting DE results, troubleshooting padj=NA, choosing FDR method, preparing ranked lists for pathway analysis, annotating gene IDs, or comparing DESeq2 vs edgeR outputs.

日本語の概要は準備中です。原文の説明を表示しています。

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.

日本語の概要は準備中です。原文の説明を表示しています。

Retired pointer for Next.js SSR doctrine. Use when something references nextjs-ssr-architecture; read the ssr-zero-layout-shift skill instead.

日本語の概要は準備中です。原文の説明を表示しています。

The doctrine for turning a vision into a finished, verified, deployed system with near-zero owner involvement. Use when launching, coordinating, resuming, or working any large build, module, campaign, or multi-agent project, or when writing its launch prompt.

日本語の概要は準備中です。原文の説明を表示しています。

Locate CEconItemView::CEconItemView in CS2 server.dll / libserver.so via IDA Pro MCP and emit a fresh, minimal-unique signature or offset for the WeaponPaints gamedata entry "CEconItemView::CEconItemView" (symbol CEconItemView_CEconItemView). This is the CONSTRUCTOR of CEconItemView. Shortlist via allocation sites: callers of operator-new whose result is immediately stored with the CEconItemView vtable (RTTI), followed by zeroing and initialization of definition-index/quantity/attribute-list fields. Distinguish from subobject constructors of derived classes by the vtable identity. Trigger: CEconItemView_CEconItemView, CEconItemView::CEconItemView

日本語の概要は準備中です。原文の説明を表示しています。

Find and identify the CBaseEntity::TakeDamageOld function in the CS2 server binary using IDA Pro MCP. Use this skill when reverse engineering CS2 server.dll or libserver.so to locate the legacy damage-application entry point by finding the code that references its self-identifying assert/warning message "CBaseEntity::TakeDamageOld: damagetype %d with info.GetDamageForce() == Vector::vZero". Trigger: CBaseEntity_TakeDamageOld

日本語の概要は準備中です。原文の説明を表示しています。

Clone a GitHub repository and automatically build a Docker environment for local verification. Creates a verification workspace in WS/, sets up Docker files, launches the environment, and performs health checks.

日本語の概要は準備中です。原文の説明を表示しています。

差分解析してタスク分割。 トリガー例: 「/diff」