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

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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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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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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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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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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。

Create a tldr page from documentation URLs and command examples, requiring both URL and command name.

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Run a read-only documentation drift audit for a feature, PR, branch, release, API, configuration change, workflow, CLI, package, or repository area. Use when the user asks whether docs are stale, missing, inconsistent with code, or need updates after code changes. Checks README files, setup guides, API docs, env docs, changelogs, examples, comments, generated docs, and user-facing instructions. This is not a general code review; it compares what the docs claim against what the code does.

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Prompt and workflow for generating conventional commit messages using a structured XML format. Guides users to create standardized, descriptive commit messages in line with the Conventional Commits specification, including instructions, examples, and validation.

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Use for the PROVIDER half of getting a locally running CopilotKit Channels agent to answer in Slack, when no Slack app exists yet — setting up a Channels bot in Slack for the first time, creating the Slack app and its tokens, attaching it to a managed Intelligence Channel, or when a Channel reports setup_required, sits at "Waiting for runtime", the Channel is Online but a Slack mention gets no reply, or a Slack app was built with Socket Mode instead of an Intelligence Request URL. Scoped to an OpenTag checkout, or the OpenTag example inside a channels-sdk clone — the phases assume those conventions (app/channel.tsx, app/env.ts, INTELLIGENCE_CHANNEL_NAME, a local agent on port 8123) and do not describe a project scaffolded by copilotkit init, which already ships its own channel host. If the Slack app and Channel already exist and the question is about declaring or customising the Channel in code, use the copilotkit-channels skill instead.

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This skill should be used when the user asks to "create an agent", "add an agent", "write a subagent", "agent frontmatter", "when to use description", "agent examples", "agent tools", "agent colors", "autonomous agent", or needs guidance on agent structure, system prompts, triggering conditions, or agent development best practices for Claude Code plugins.

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Solve competition math problems (IMO, Putnam, USAMO, AIME) with adversarial verification that catches the errors self-verification misses. Activates when asked to 'solve this IMO problem', 'prove this olympiad inequality', 'verify this competition proof', 'find a counterexample', 'is this proof correct', or for any problem with 'IMO', 'Putnam', 'USAMO', 'olympiad', or 'competition math' in it. Uses pure reasoning (no tools) — then a fresh-context adversarial verifier attacks the proof using specific failure patterns, not generic 'check logic'. Outputs calibrated confidence — will say 'no confident solution' rather than bluff. If LaTeX is available, produces a clean PDF after verification passes.

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This skill should be used when the user asks to "demonstrate skills", "show skill format", "create a skill template", or discusses skill development patterns. Provides a reference template for creating Claude Code plugin skills.

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Choose GPT-Image2 / gpt-image-2 visual styles and industrial prompt templates from the awesome-gpt-image-2 style library. Use when an agent needs to create, rewrite, classify, or improve image-generation prompts with repository-backed templates, categories, style tags, scene tags, pitfalls, and example cases.

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。