「across」の検索結果

Expert in Buddhist philosophy covering Four Noble Truths, dependent origination, emptiness, and meditation practices across traditions

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Expert in world religions covering beliefs, practices, texts, and comparative analysis across traditions

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Expert in pan-Asian cuisines and modern fusion techniques across Chinese, Japanese, Thai, Vietnamese, and Korean cooking

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Complete guide to Japanese Language Proficiency Test preparation with strategies for vocabulary, kanji, grammar, reading, and listening across all levels

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 in language and culture relationships, sociolinguistics, and language variation across communities

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Diagnose failures in SKMTC sessions — no output, wrong output, error messages, failed bundle builds, parseIssues, "Registered definition mismatch", ref cycles, "Module not found" in generated code, or any other broken behavior. Applies across both CLI usage and generator authoring contexts. Use this skill when the user asks "why isn't my generator working", "no output for X", "wrong output", "what does this error mean", "manifest says X", "bundle failed", "INVALID_SCHEMA", "INVALID_DEPENDENCY_REF", "Registered definition mismatch", "Module not found" (in generated code), "ConfigValidationError", or reports any other SKMTC failure. This skill encodes a **verify-first epistemic stance** — read the manifest, check parseIssues, reproduce the failure before proposing fixes. Distinct from `skmtc-cli` and `skmtc-generator` which guide *doing*; this skill guides *diagnosing*.

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。

Full customer lookup across [Gorgias](https://composio.dev/toolkits/gorgias) tickets and [HubSpot](https://composio.dev/toolkits/hubspot) CRM.

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Check SLA compliance across open tickets and flag breaches or at-risk tickets

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Persistent memory patterns for moflo agents — session memory, long-term knowledge, pattern learning, and cross-session context via moflo's node:sqlite + HNSW vector store. Use when building stateful agents or assistants that need to remember across runs.

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Structured multi-hop web research with explicit confidence gating — plan the inquiry, search (WebSearch/WebFetch), score your own confidence, and keep digging until the answer is well-supported or a hop cap is hit, then emit a cited synthesis. Learns across sessions by storing each research case to memory and reusing prior strategies. Use when a question needs more than one search — comparisons, current-best-practice questions, anything where a single lookup leaves you unsure.

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。

Adaptive learning for moflo agents via ReasoningBank: trajectory storage, verdict judgment, memory distillation, consolidation, and MMR retrieval. Use when building agents that should improve from experience across runs.

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Manage personal AI agents that travel with you across projects

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Coordinating work across multiple Squad instances

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Shared hard rules enforced across all squad agents

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.NET timezone handling guidance for C# applications. Use when working with TimeZoneInfo, DateTimeOffset, NodaTime, UTC conversion, daylight saving time, scheduling across timezones, cross-platform Windows/IANA timezone IDs, or when a .NET user needs the timezone for a city, address, region, or country and copy-paste-ready C# code.

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Query .NET APIs across NuGet packages, platform libraries, and local files. Search for types, list API surfaces, compare and diff versions, find extension methods and implementors. Use whenever you need to answer questions about .NET library contents.

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MUST USE for any real runtime debugging across ANY language or binary — crashes, silent failures, wrong responses, stuck processes, memory leaks, async misbehavior, unexplained timing, reverse engineering. Runs a hypothesis-driven loop: form ≥3 hypotheses, investigate in parallel, after 2 failed rounds spawn Oracles from orthogonal angles, confirm root cause, lock with a failing test, fix minimally, QA by actually USING the system, scrub artifacts. The actual HOW lives in `references/` — READ THEM. Triggers: 'debug this', 'why is X not working', 'hanging', 'attach a debugger', 'reverse engineer', 'pwndbg', 'gdb', 'lldb', 'node inspect', 'tsx debug', 'pdb', 'dlv', 'delve', 'rust-gdb', 'set a breakpoint', 'context window exploded', 'why is the response empty', 'attach the debugger', 'debug it', 'why is this happening', 'trace this bug', 'reproduce and fix', 'silent failure', 'HTTP 200 but empty', 'why did it stop', 'inspect the binary', 'reverse engineering', 'playwright'.

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Mechanical consistency check for game design — answers "is the design consistent with itself?" — plus changed-scope impact analysis across all three GDD axes: systems, flows, and content types. Offline and deterministic: greps the facts registry against the documents (numbers, terms, IDs, duplicate & dangling references, roster↔disk, map freshness, Depends 3-way, status/version, AC presence, placeholder leaks, flow & content schema), and from a git diff computes which dependent systems, flows, and content a change affects. Scope is inferred: a named document checks that document; an unverified diff triggers a changed-scope pass; otherwise everything. Use when the user wants a consistency or impact check, e.g. "verify the design", "what did this change affect", "find broken references in the design". Conflicts triage into four tracks; the entailed fixes hand off to /unikit-gd-apply in one pass. This is the mechanical pass — for a subjective "is this design good" quality critique use /unikit-gd-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。

Qualitative quality review of game design documents — answers "is this design good, and does it follow best practices?" — across all three GDD axes: systems, flows, and content types. Fans out adversarial lenses (completeness, clarity, pillar alignment, systems-math, fantasy-delivery, feasibility, scope) plus domain lenses that check it against the game-design rules, each prompted to find problems rather than validate; produces a severity-graded verdict and a two-bucket report (apply-ready fixes vs research), handed to /unikit-gd-apply or /unikit-gd-explore in one move. Scope is inferred: a named system, flow, or content type reviews that document; "all" runs a cross-document review. Use when the user wants a critique, quality judgment, or rules check of the design, e.g. "review the combat GDD", "review the onboarding flow". This is the subjective quality pass — for a mechanical consistency check (numbers, terms, IDs, references matching the registry) use /unikit-gd-verify.

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Execute the tasks from an already-created feature plan in .unikit/code/plans/ — read the plan manifest (the PLAN.md file in the plan folder), work through the uncompleted tasks in order, write the code, mark progress, and resume across sessions. Supports selective runs by phase or by task numbers, and continuing from where the last session stopped. Use whenever a plan exists and the user wants to build it, e.g. "implement", "implement the plan", "start coding", "execute the plan", "run the plan", "do the next task", "implement phase 3", "implement tasks 2.1 and 2.3", "continue implementation", "continue where we left off", "keep going on the feature". To create the plan first, use the planning skill — this one carries an existing plan out.

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。

Comprehensive test suite review across five phases. Surveys unit coverage, integration coverage, E2E (browser) coverage for webapps, fuzz coverage, and test quality — in that order. Advisory only — produces findings and proposes tickets; does not implement test changes.

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Prospective failure imagination for a plan, decision, or running system. Operates in two modes — **plan mode** (a plan has not yet been committed to; imagine its catastrophic failure broadly) and **scenario mode** (a specific catastrophic scenario is posed against an existing system; investigate causes against the actual code and architecture). Spawns parallel pre-mortemers in isolation across three categories of lens: standard failure classes (technical, operational, estimation, scope, adoption, dependency, team, incentive, detection, reversibility, adversarial), 0-3 ad-hoc target-specific lenses the orchestrator names when warranted, and a first-principles lens that always runs to catch what the prescribed taxonomy misses. Synthesizes into a prioritized risk register with early-warning signals. Produces feedback only — no code, no tickets, no artifacts.

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Good-faith adversarial scrutiny of an idea or plan. Spawns critical skeptics across relevant lenses, pairs them with an advocate defending the idea, and synthesizes the exchange into a report. Produces feedback only — no code, no tickets, no artifacts.

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Run the same scrape or task across many accounts at once - each in its own browser profile with its own fingerprint, cookies and exit IP - and read data from sites that need a session or that answer a plain HTTP scraper with a captcha while answering a real browser. One command per site returns JSON, so there are no selectors to write or repair: Amazon and Walmart search, Google and DuckDuckGo results, Reddit posts and comments, X timeline, Medium, Yelp, Indeed job listings, Hacker News, GitHub, PyPI, npm, plus exit-IP and fingerprint checks. Use for multi-account operations you are authorized to run, price and listing monitoring per region, SERP collection, logged-in data, and scrapers that keep breaking. Also for 'scrape amazon', 'google search results', 'reddit data', 'scrape logged in site', 'run task on many accounts', 'site blocks my scraper', 'scraping without selectors'. Node or Python.

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。