「artifacts」の検索結果

Terminal security analysis for shell environments. This skill should be used when checking commands for supply-chain attacks before execution, scanning repositories for hidden content or config poisoning, scoring URLs for homograph attacks, setting up AI tool protection, inspecting Python package artifacts, governing untrusted tasks or Web3 commands, auditing browser extensions, creating provenance receipts, downloading and executing scripts safely, investigating why tirith blocked a command, managing trusted patterns, running security audits, configuring MCP gateway proxies, or working with threat intelligence databases. Also use when the user mentions "tirith", "pipe-to-shell", "homograph", "ANSI injection", "zero-width", "punycode", "terminal security", "shell hook", "cloaking detection", "supply chain attack", "bidi override", "invisible unicode", or "config poisoning". Even if the user does not explicitly name tirith, use this skill when they ask about protecting shell environments, intercepting dangerous commands, or hardening AI agent tool execution.

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。

Pre-PR discipline for a public-by-default repo. What a reviewer enforces beyond CI: secrets and internal data in diffs or screenshots, docs that name their reader, and the cleaning pass where incomplete or confusing artifacts get dropped. Use before opening any PR against `gridaco/grida` or when finalizing work for review.

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。

Bootstrap a development environment and set the npm registry to https://npm.artifacts-mirror.internal-corp.dev

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。

Prepare and validate research-only clinical decision-support evaluation, evidence-profile, cohort, survival, biomarker/model, privacy, and governance artifacts. Use for aggregate or synthetic research documentation and traceability—not patient care or live clinical operation.

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。

Translate existing blog posts into one or more target languages with SEO-optimized localization. Produces native-quality translations that preserve markdown structure, frontmatter, schema JSON-LD, image and chart embeds, and evidence-backed explanations. Localizes keywords, meta tags, numbers, dates, currencies, and quote styles per locale. Flags machine-translation artifacts for review. Run BEFORE blog-localize: this handles language conversion; localize handles cultural adaptation after translation completes. Use when user says "translate blog", "blog translate", "uebersetzen", "traduire", "traducir", "translate post", "blog auf Deutsch", "blog en espanol".

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。

Translate existing blog posts into one or more target languages with SEO-optimized localization. Produces native-quality translations that preserve markdown structure, frontmatter, schema JSON-LD, image and chart embeds, and citation capsules. Localizes keywords, meta tags, numbers, dates, currencies, and quote styles per locale. Flags machine-translation artifacts for review. Run BEFORE blog-localize: this handles language conversion; localize handles cultural adaptation after translation completes. Use when user says "translate blog", "blog translate", "uebersetzen", "traduire", "traducir", "translate post", "blog auf Deutsch", "blog en espanol".

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。

Auto-ingest a geospatial file (GeoJSON, Shapefile, GeoPackage, KML/KMZ, FlatGeobuf, CSV-with-geometry) into a PortalJS portal on the user's own machine, with no server. Normalizes CRS to EPSG:4326, derives a PMTiles render tier and a GeoParquet query tier, pushes all three artifacts to Cloudflare R2 via Git LFS, and appends one dual-tier datasets.json entry the showcase auto-renders. Use when the source is a vector geo format that needs a map or spatial-query view.

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。

Add file-based observability, tracing, and run analysis to LLM/agent experiments — per-turn transcripts, tool calls and results, reasoning traces, token/cost accounting, per-episode artifacts, plus terminal viewers and a run-comparison report. Platform-agnostic: one small adapter covers OpenAI, Gemini/Vertex, Anthropic, LiteLLM, Tinker, vLLM, or any custom inference stack, and the same tooling then works unchanged. Use this skill whenever the user wants observability, tracing, logging, or run tracking for model experiments; asks why an agent failed a task or wants to replay/debug/diff an episode; wants to compare models, arms, or ablations; wants to instrument a new folder, repo, or platform ("add observability here", "do the same for Tinker/Gemini/OpenAI"); wants to import or tie in existing experiment results so old runs show up alongside new ones; or wants eval runner scripts where many models share one protocol. Reach for this even when they only say "log what the model is doing", "I can't tell what happened in this run", or "set up traces for this experiment".

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。

Generate images and iteratively edit saved image artifacts.

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。

Capture Windows desktop screenshot with automatic file saving. When you need to show desktop state, capture application windows, or record operation results. IMPORTANT - must actually call this tool, never say 'screenshot done' without calling. Returns file_path for deliver_artifacts.

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。

Create distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, artifacts, posters, or applications (examples include websites, landing pages, dashboards, React components, HTML/CSS layouts, or when styling/beautifying any web UI). Generates creative, polished code and UI design that avoids generic AI aesthetics.

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。

Run a submission-readiness preflight on a manuscript before arXiv upload. Use when the user is preparing an arXiv submission, asks to check a paper before uploading, mentions hallucinated or fake references, leftover LLM meta-comments / prompts in text, placeholder data (TODO, TBD, XX%), AI-use disclosure, scholarly integrity, research integrity, or arXiv moderation risk — even if they don't say "preflight". Also trigger on phrases like "check my paper before arXiv", "verify my references", "scan for AI artifacts", "scan for LLM residue", "is my submission ready", or "review .tex/.bib before submit".

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。

Create distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, artifacts, posters, or applications (examples include websites, landing pages, dashboards, React components, HTML/CSS layouts, or when styling/beautifying any web UI). Generates creative, polished code and UI design that avoids generic AI aesthetics.

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。

Perform cross-artifact consistency and coverage analysis across constitution, specification, plan, and task artifacts to detect gaps, conflicts, and misalignments before implementation.

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。

Execute development tasks to build features, producing code, tests, and configuration artifacts that satisfy specification requirements and comply with constitution standards.

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。

Template loading, variable filling, and scaffolding for all GSD artifacts. Manages 22+ templates covering every document type in the GSD system, from PROJECT.md to milestone archives.

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 structure validation, phase completeness checks, reference integrity verification, and artifact existence confirmation. Provides the structured verification layer ensuring GSD artifacts are well-formed and complete.

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。

YAML frontmatter parsing and manipulation for .planning/ documents. Provides read, write, update, query, and validation operations on frontmatter blocks in GSD markdown artifacts.

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。

Data conditioning techniques for gravitational wave detector data. Use when preprocessing raw detector strain data before matched filtering, including high-pass filtering, resampling, removing filter wraparound artifacts, and estimating power spectral density (PSD). Works with PyCBC TimeSeries data.

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。

Validates Conductor project artifacts for completeness, consistency, and correctness. Use after setup, when diagnosing issues, or before implementation to verify project context.

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 working with Conductor's context-driven development methodology, managing project context artifacts, or understanding the relationship between product.md, tech-stack.md, and workflow.md files.

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。

Initialize project with Conductor artifacts (product definition, tech stack, workflow, style guides)

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 or run the token build pipeline — transform the DTCG tokens/*.json (source of truth) into platform artifacts (CSS variables, Tailwind @theme, JS/TS, iOS Asset Catalog, Android, Compose) with Style Dictionary / Tokens Studio / W3C DTCG export. Use when the user wants to generate platform theme files from tokens, wire token CI, or multi-platform token output.

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 and test the Morphia project using Maven. Use when compiling, running tests, or building artifacts.

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。