「context」の検索結果

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.

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。

Quick read-only health check — session context, workspace mounts, tool availability, and task snapshot. Use when the user asks for system status or runs /status.

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。

Quick read-only health check — session context, workspace mounts, tool availability, and task snapshot. Use when the user asks for system status or runs /status.

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。

One-time setup that gathers design context for your project and saves it to your AI config file. Run once to establish persistent design guidelines.

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。

Guide for when to use and when not to use return validators in Convex functions. Use this skill whenever the user is writing Convex queries, mutations, or actions and needs guidance on return value validation. Also trigger when the user asks about Convex type safety, runtime validation, AI-generated Convex code, Convex AI rules, Convex security best practices, or when they're debugging return type issues in Convex functions. Trigger this skill when users mention "validators", "returns", "return type", or "exact types" in the context of Convex development. Also trigger when writing or reviewing Convex AI rules or prompts that instruct LLMs how to write Convex code.

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。

Patterns for scaling read-heavy Convex apps to millions of users. Use when optimizing bandwidth, reducing query costs, fixing slow queries, creating digest tables, replacing reactive subscriptions with one-shot fetches, adding compound indexes, debouncing writes, rate-controlling backfills, or running npx convex insights. Trigger when users mention "scale", "bandwidth", "performance", "optimize", "slow queries", "expensive queries", "digest table", "denormalize", or "thundering herd" in the context of Convex.

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. Generates creative, polished code that avoids generic AI aesthetics. Use when the user asks to build web components, pages, artifacts, posters, or applications, or when any design skill requires 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。

Adapt designs to work across different screen sizes, devices, contexts, or platforms. Implements breakpoints, fluid layouts, and touch targets. Use when the user mentions responsive design, mobile layouts, breakpoints, viewport adaptation, or cross-device compatibility.

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。

Agent Ready project design context for navigation, docs links, and interface tone. Use when building or reviewing UI in this repo so patterns match the documented product feel.

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。

One-time setup that gathers design context for your project and saves it to your AI config file. Run once to establish persistent design guidelines.

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。

Patterns for scaling read-heavy Convex apps to millions of users. Use when optimizing bandwidth, reducing query costs, fixing slow queries, creating digest tables, replacing reactive subscriptions with one-shot fetches, adding compound indexes, debouncing writes, rate-controlling backfills, or running npx convex insights. Trigger when users mention "scale", "bandwidth", "performance", "optimize", "slow queries", "expensive queries", "digest table", "denormalize", or "thundering herd" in the context of Convex.

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. Generates creative, polished code that avoids generic AI aesthetics. Use when the user asks to build web components, pages, artifacts, posters, or applications, or when any design skill requires 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。

Guide for when to use and when not to use return validators in Convex functions. Use this skill whenever the user is writing Convex queries, mutations, or actions and needs guidance on return value validation. Also trigger when the user asks about Convex type safety, runtime validation, AI-generated Convex code, Convex AI rules, Convex security best practices, or when they're debugging return type issues in Convex functions. Trigger this skill when users mention "validators", "returns", "return type", or "exact types" in the context of Convex development. Also trigger when writing or reviewing Convex AI rules or prompts that instruct LLMs how to write Convex code.

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。

Agent Ready project design context for navigation, docs links, and interface tone. Use when building or reviewing UI in this repo so patterns match the documented product feel.

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。

Adapt designs to work across different screen sizes, devices, contexts, or platforms. Implements breakpoints, fluid layouts, and touch targets. Use when the user mentions responsive design, mobile layouts, breakpoints, viewport adaptation, or cross-device compatibility.

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 structured GitHub issues from text, screenshots, or lists, with acceptance criteria and preserved reporter context. Use for filing bugs/features, batch creation, or template cleanup. Don't use for resolving, triaging, or deep issue analysis.

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。

This repo is indexed by graft/. For ANY task here, whether understanding how something works, finding where code lives, tracing what calls a symbol or what a change breaks, or scoping an edit, get your context from the graph before grepping or reading source files. Every command runs through `bin/harness graft`.

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。

6 production-ready AI engineering workflows: prompt evaluation (8-dimension scoring), context budget planning, RAG pipeline design, agent security audit (65-point checklist), eval harness building, and product sense coaching.

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。

Deploy AI and NLP-powered detection systems to identify business email compromise attacks by analyzing writing style, behavioral patterns, and contextual anomalies that evade traditional rule-based filters.

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。

Collects and synthesizes open-source intelligence (OSINT) about threat actors, malicious infrastructure, and attack campaigns using publicly available data sources, passive reconnaissance tools, and dark web monitoring. Use when investigating external threat actor infrastructure, performing pre-engagement reconnaissance for authorized red team assessments, or enriching CTI reports with publicly available adversary context. Activates for requests involving Maltego, Shodan, OSINT framework, SpiderFoot, or infrastructure reconnaissance.

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。

Scan Model Context Protocol servers and tool metadata for poisoning, SSRF, and unauthenticated exposure.

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。

Automates the enrichment of raw indicators of compromise with multi-source threat intelligence context using SOAR platforms, Python pipelines, or TIP playbooks to reduce analyst triage time and standardize enrichment outputs. Use when building automated enrichment workflows integrated with SIEM alerts, email submission pipelines, or bulk IOC processing from threat feeds. Activates for requests involving SOAR enrichment, Cortex XSOAR, Splunk SOAR, TheHive, Python enrichment pipelines, or automated IOC processing.

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。

Analyzes structured and unstructured threat intelligence feeds to extract actionable indicators, adversary tactics, and campaign context. Use when ingesting commercial or open-source CTI feeds, evaluating feed quality, normalizing data into STIX 2.1 format, or enriching existing IOCs with campaign attribution. Activates for requests involving ThreatConnect, Recorded Future, Mandiant Advantage, MISP, AlienVault OTX, or automated feed aggregation pipelines.

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 a context-rich briefing prompt for an external agent (Claude Code, Cursor, etc.)

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。