「exa」の検索結果

Use when the user wants to know what will break if they change something, or needs safety analysis before editing code. Examples: "Is it safe to change X?", "What depends on this?", "What will break?"

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Use when querying or extending GitNexus's PDG control/data-dependence surface (the `pdg_query` MCP tool, CDG/REACHING_DEF edges), or reasoning about "what controls X" / "where does Y flow" / guard clauses. Examples: "what guards this statement?", "trace this variable within the function", "why is the pdg_query result empty?", "add a CDG query".

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Use when the user is debugging a bug, tracing an error, or asking why something fails. Examples: "Why is X failing?", "Where does this error come from?", "Trace this bug"

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Use when the user wants the GitNexus engineering pipeline run end-to-end on a task: gitnexus-plan (plan depth chosen up front), a blocking gate to execute with gitnexus-work or stop, finishing with a gitnexus-review of the result. Examples: "/gitnexus-lfg Add retry support to the ingestion pipeline", "run the gitnexus pipeline on this", "plan, build and review this feature".

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Use when the user asks how code works, wants to understand architecture, trace execution flows, or explore unfamiliar parts of the codebase. Examples: "How does X work?", "What calls this function?", "Show me the auth flow"

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Use when you need a deep, implementation-ready engineering plan for a code change — built from GitNexus graph intelligence, statement-level PDG analysis, and targeted source verification, compact enough that an implementation agent can start without re-investigating. Also strengthens existing plans via Deepen mode. Examples: "/gitnexus-plan Add retry support to the ingestion pipeline", "/gitnexus-plan deepen docs/plans/<plan>.md", "plan this change using the knowledge graph".

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Use when executing an engineering plan produced by gitnexus-plan (or a small bounded task directly) — implements step by step with GitNexus impact checks before every symbol edit, tests from the plan's scenarios, and detect_changes gating every commit. Examples: "/gitnexus-work docs/plans/2026-07-11-gitnexus-plan-ingestion-retry.md", "/gitnexus-work" (latest plan), "execute the plan".

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Use when working on, reviewing, or extending GitNexus's CFG/taint/PDG subsystem (the `--pdg` layers), or when reasoning about source→sink data-flow findings. Examples: "How does taint analysis work here?", "Why didn't explain find this flow?", "Add a new sink/source", "Review the interprocedural taint code".

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Use when the user asks about GitNexus itself — available tools, how to query the knowledge graph, MCP resources, graph schema, or workflow reference. Examples: "What GitNexus tools are available?", "How do I use GitNexus?"

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Use when the user needs to run GitNexus CLI commands like analyze/index a repo, check status, clean the index, generate a wiki, or list indexed repos. Examples: "Index this repo", "Reanalyze the codebase", "Generate a wiki"

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Use when the user wants to rename, extract, split, move, or restructure code safely. Examples: "Rename this function", "Extract this into a module", "Refactor this class", "Move this to a separate file"

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Capture surprises, workarounds, and rough edges hit while *consuming* the public surface of Prisma 8, Prisma Compute, or Prisma Postgres — anything a real user of these products would experience. Fires whenever an operator (or agent) writes a workaround, hits a surprising failure mode, or finds undocumented behaviour while using one of these three products from the outside (extension authoring, example apps, integration tests, customer reproductions, internal demos, manual repros). Does NOT fire on bugs in code the operator's own team maintains — those are normal product-backlog bugs. In product-team repos (e.g. `prisma-8-ws`), surfaces the gotcha and offers the operator three paths (capture-as-gotcha, file a normal bug, or note-and-move-on). Outside product-team repos (pet projects, hackathon entries, customer codebases), silent-captures into the project's gotchas log AND a Triage-state Linear ticket in the matching gotchas project — no operator escalation. Do not skip the recording step.

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Master proven backend architecture patterns including Clean Architecture, Hexagonal Architecture, and Domain-Driven Design to build maintainable, testable, and scalable systems.

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Generate comprehensive, developer-friendly API documentation from code, including endpoints, parameters, examples, and best practices

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Upgrade the pinned Flask-AppBuilder (FAB) dependency in the Apache Airflow FAB provider (`providers/fab/`). Bumps the exact `flask-appbuilder==` pin and its mirror constant, regenerates `uv.lock`, drives the `test_fab_alignment.py` drift tripwire, reviews the vendored security-manager `override.py` against the new upstream FAB, and conditionally re-vendors static assets / DB migrations. Use when asked to "upgrade FAB", "bump flask-appbuilder", or move the FAB provider to a newer Flask-AppBuilder release.

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CCXT cryptocurrency exchange library for TypeScript and JavaScript developers (Node.js and browser). Covers both REST API (standard) and WebSocket API (real-time). Helps install CCXT, connect to exchanges, fetch market data, place orders, stream live tickers/orderbooks, handle authentication, and manage errors. Use when working with crypto exchanges in TypeScript/JavaScript projects, trading bots, arbitrage systems, or portfolio management tools. Includes both REST and WebSocket examples.

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Runs the job-search pipeline. Adds jobs from a link or pasted posting, keeps stages and dates accurate, sets follow-ups, runs a weekly review (stale applications, next actions, funnel stats), records the exact resume version sent, and drafts networking, LinkedIn, referral, recruiter-reply, follow-up, thank-you, status-check, expedite and withdrawal messages without sending them. Use when the user says "add this job to my tracker", "I applied", "log my interview", "I got rejected", "I was ghosted", "log my offer", "track my applications", "do my weekly review", "what should I follow up on", "write a thank-you note", "message this recruiter", "ask for a referral", "withdraw my application", or wants a job-search spreadsheet. Works with a Markdown/CSV tracker or Reactive Resume MCP tools. Not for resume work (resume-tailor, resume-bullet-writer, resume-content-guide), interview prep or practice (interview-prep, mock-interview), or judging, negotiating, accepting or declining an offer (offer-negotiation).

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The complete slide DSL manual — the canvas and its background, the ten element types field by field with units, defaults and legal values, where each type keeps its words, which field the renderer actually paints when two disagree, exactly what happens to the HTML you put in `content`, and the structure schema that is now the ONLY thing a write is checked against. Nothing filters your markup and nothing normalises your values, so this manual is the whole of what makes a page render correctly. Load it before patching a field you have not patched before, when a patch comes back rejected, when a patch lands but nothing moves on screen, or when you need to know where a colour, a font, a table cell or a code line really lives. This is a field reference and not a procedure — `page-clone` and `pro-editing` decide which pages to touch, `slide-craft` decides what a good page looks like, and this one says what the JSON means.

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Turn code from the current session into a blog post written in the voice of its author. Covers one function, script, class, or tool as a focused walkthrough with a generalized sample and a usage example, learns tone and structure from existing posts or writing samples by the same author, takes the destination from what the user names or the blog repository in use instead of assumed folders, and saves no file until the draft is approved. Use when asked to write, draft, or turn code into a blog post, article, tutorial, or gist, or when invoked as /make-blog-post at the end of a turn.

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Look up Microsoft API references, find working code samples, and verify SDK code is correct. Use when working with Azure SDKs, .NET libraries, or Microsoft APIs—to find the right method, check parameters, get working examples, or troubleshoot errors. Catches hallucinated methods, wrong signatures, and deprecated patterns by querying official docs.

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Query official Microsoft documentation to find concepts, tutorials, and code examples across Azure, .NET, Agent Framework, Aspire, VS Code, GitHub, and more. Uses Microsoft Learn MCP as the default, with Context7 and Aspire MCP for content that lives outside learn.microsoft.com.

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Audit MCP (Model Context Protocol) server configurations for security issues. Use this skill when: - Reviewing .mcp.json files for security risks - Checking MCP server args for hardcoded secrets or shell injection patterns - Validating that MCP package-runner dependencies use exact reviewed versions, not bare names, @latest, or ranges - Detecting mutable npm/npx, bunx, pnpm dlx, yarn dlx, and npm exec references in MCP configurations - Auditing which MCP servers a project registers and whether they're on an approved list - Checking for environment variable usage vs. hardcoded credentials in MCP configs - Any request like "is my MCP config secure?", "audit my MCP servers", or "check .mcp.json" keywords: [mcp, security, audit, secrets, shell-injection, supply-chain, governance]

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Import existing Azure resources into Terraform using Azure CLI discovery and Azure Verified Modules (AVM). Use when asked to reverse-engineer live Azure infrastructure, generate Infrastructure as Code from existing subscriptions/resource groups/resource IDs, map dependencies, derive exact import addresses from downloaded module source, prevent configuration drift, and produce AVM-based Terraform files ready for validation and planning across any Azure resource type.

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Use this skill to get context about Fabric Lakehouse and its features for software systems and AI-powered functions. It offers descriptions of Lakehouse data components, organization with schemas and shortcuts, access control, and code examples. This skill supports users in designing, building, and optimizing Lakehouse solutions using best practices.

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。