「context-aware」の検索結果

Suede Slop Stop: Suede Labs context-aware anti-slop pass for finished prose. Find or remove generic filler, manufactured emphasis, false agency, formulaic structure, chat and draft residue, and formatting applied by rule, without flattening the author's voice. Use before copy, a README, an email, a social post, or a doc ships; after a long assisted-writing session; or for a findings-only slop audit. NOT FOR: writing new copy (use suede-copy); deciding whether a person or model wrote text; changing or certifying facts, which require primary evidence.

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Expert skill for building CLI applications with Cobra and Viper, authored by spf13 — the original creator of both libraries. Covers command-first architecture, decoupled business logic, configuration management, environment variable binding, context-aware commands, and in-memory CLI testing. Use whenever a Go CLI or command-line tool is being built, reviewed, or refactored — any mention of commands, subcommands, flags, or CLI configuration, even if Cobra or Viper aren't named yet (recommend them).

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Guided, section-by-section UX spec authoring for a screen, flow, or HUD. Reads game concept, player journey, and relevant GDDs to provide context-aware design guidance. Produces ux-spec.md (per screen/flow) or hud-design.md using the studio templates.

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Implement semantic vector search with AgentDB for intelligent document retrieval, similarity matching, and context-aware querying. Use when building RAG systems, semantic search engines, or intelligent knowledge bases.

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。

Implement semantic vector search with AgentDB for intelligent document retrieval, similarity matching, and context-aware querying. Use when building RAG systems, semantic search engines, or intelligent knowledge bases.

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。

Implement semantic vector search with AgentDB for intelligent document retrieval, similarity matching, and context-aware querying. Use when building RAG systems, semantic search engines, or intelligent knowledge bases.

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。

Validate and improve GitHub Well-Architected Framework (WAF) documentation under the content/ folder for architectural correctness, decision quality, explicit trade-offs, and actionable guidance. Use this when reviewing pull requests, markdown files, or draft content in content/ to ensure recommendations are technically sound, context-aware, and guide readers toward correct architecture and design decisions.

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Generate context-aware quality checklists for code review and QA using IEEE 1028 base standards plus LLM contextual additions

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Step 2 of the PaperOrchestra pipeline (arXiv:2604.05018). Execute the visualization plan from outline.json — render plots and conceptual diagrams from experimental_log.md and idea.md, optionally refine via VLM critique loop, and produce context-aware captions. Runs in parallel with the literature-review-agent. TRIGGER when the orchestrator delegates Step 2 or when the user asks to "generate the figures for my paper" or "render the plots from this experiment log".

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, section-by-section UX spec authoring for a screen, flow, or HUD. Reads game concept, player journey, and relevant GDDs to provide context-aware design guidance. Produces ux-spec.md (per screen/flow) or hud-design.md using the studio templates.

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。

Creates context-aware git commits with smart pre-commit checks, submodule support, and conventional commit message generation. Use when user requests to commit changes, stage and commit, check in code, save work, save changes, push my code, finalize changes, add to git, create commits, run /commit command, or mentions "git commit", "commit message", "conventional commits", "stage files", "git add", or needs help with commits.

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Semantic vector search with moflo — RAG over your own documents, similarity matching, context-aware retrieval via HNSW (node:sqlite-backed). Use when building retrieval layers for chat, search, or context-assembly.

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。

Implement semantic vector search with AgentDB for intelligent document retrieval, similarity matching, and context-aware querying. Use when building RAG systems, semantic search engines, or intelligent knowledge bases.

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。

Generates comprehensive, context-aware code review checklists tailored to the specific codebase, programming language, and team standards. Analyzes PR diffs and suggests what reviewers should focus on.

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Audit, rename, and polish a GitHub repository across its local checkout and remote settings. Use when Codex needs to synchronize a local and GitHub repository name, set the description, homepage URL, or topics, create repository branding and a GitHub social preview, restructure a README, or prepare and publish a cohesive repository identity. Uses GitHub CLI for supported remote operations and delegates visual identity work to $create-context-aware-logos.

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Design original, scalable logos and production-ready asset sets for a specific usage context. Use when Codex needs to create or refine a logo, symbol, wordmark, app icon, repository identity, CLI mark, website brand, social preview, or Codex skill/plugin icon; adapt concepts, formats, dimensions, variants, and delivery checks to the target platform instead of producing a context-free image.

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。

Configuring Google Cloud Identity-Aware Proxy (IAP) to enforce per-request identity verification for Compute Engine, App Engine, Cloud Run, and GKE services using access levels, context-aware policies, and programmatic access with service accounts.

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Register a custom Dynamic Visibility condition for JetEngine — extend \Jet_Engine\Modules\Dynamic_Visibility\Conditions\ Base, hook jet-engine/modules/dynamic-visibility/conditions/register, call $manager->register_condition( new MyCondition() ). The 3 abstract methods are get_id() / get_name() / check( $args = [] ); override get_group() to assign a UI group, is_for_fields() / need_value_detect() / need_type_detect() to control where the condition appears, get_custom_controls() to add per-condition UI controls. The check() $args includes type ('show' or 'hide'), field / field_raw, value, data_type ('chars' / 'numeric' / 'datetime' / 'date' / 'list'), and context ('default' or 'current_listing'). Important — $args['type'] is the user's show/hide intent; condition must invert its boolean accordingly. Use get_current_value() helper for context-aware meta resolution (handles WP_Post, WP_User, WP_Term, WP_Comment, listing macros). Use when scaffolding a JetEngine companion plugin's visib...

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。

Context-aware remapping of stale parent shard references to new sub-shard targets after shard split operations

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。

Expert Cody (Sourcegraph Cody, code search, AI autocomplete, context awareness)

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。

Implement semantic vector search with AgentDB for intelligent document retrieval, similarity matching, and context-aware querying. Use when building RAG systems, semantic search engines, or intelligent knowledge bases.

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。

Configuring Google Cloud Identity-Aware Proxy (IAP) to enforce per-request identity verification for Compute Engine, App Engine, Cloud Run, and GKE services using access levels, context-aware policies, and programmatic access with service accounts.

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。

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.

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。

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.

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。