Results for “errors”

Expert guide for multi-pass autonomous AI code self-review — syntax validation, logic correctness, architectural conformance, security audit, and performance analysis without external tooling — enabling the agent to catch its own errors before presenting code / Panduan ahli review kode otonom multi-pass oleh AI — validasi sintaks, kebenaran logika, konformitas arsitektur, audit keamanan, dan analisis performa tanpa tooling eksternal — memungkinkan agen menangkap errornya sendiri sebelum menampilkan kode.

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Structured debugging runbook for backend services. Use when investigating production issues, API errors, performance problems, or when something broke and you need to find why.

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Create and refactor Bash scripts following conventions (strict mode, fct_ naming, quoting). Includes shellcheck linting. Use when creating shell scripts, refactoring existing scripts, debugging shell errors, or linting scripts.

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Review common AI slops of defensive programming patterns, avoid silent errors. TRIGGER when reviewing code for defensive anti-patterns, writing fail-fast code, or auditing error handling quality.

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Use when first setting up lark-cli, running auth login, switching user/bot identity (--as), handling permission denied or scope errors, needing to update lark-cli, or seeing _notice in JSON output.

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Designs durable API contracts across REST, GraphQL, gRPC, tRPC, and AsyncAPI. Use when specifying interfaces, auth, versioning, errors, rate limits, or agent APIs.

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Run an automated smoke test using the godot-mcp server. Launches the project, captures debug output, and checks for errors or crashes.

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Resolve obstacles using fallback chains — use when an approach fails, a dependency is unavailable, an API returns errors, or a task is blocked and needs an alternative path forward

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Designs or reviews HTTP, REST, GraphQL, RPC, CLI, webhook, event, and service interfaces with explicit inputs, outputs, errors, compatibility, idempotency, pagination, authentication, versioning, and observability. Use when introducing or changing an API or cross-component contract. Not for internal implementation details with no boundary or for debugging one API failure; use root-cause-debugging there.

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Review design specification documents for Go programs before implementation begins. Use this skill when a user has a Go spec, design doc, RFC, or PRD to review, wants feedback on a planned feature in a Go codebase, is about to start implementing from a spec, or asks "is this spec ready?" or "review this before I build it". Applies Go philosophy — simplicity, composition, explicit errors, context propagation — plus Cobra/Viper CLI conventions where applicable.

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Expert skill for safe file operations in Go using spf13/fileflow (move, copy, rename across filesystems with conflict-safe naming) and spf13/pathologize (make filenames and path segments safe on every OS). Use whenever Go code moves, copies, renames, downloads, extracts, or generates files on disk, or builds a destination path from untrusted input (user data, scraped names, regex captures) — any mention of moving files, cross-device/EXDEV rename errors, "file already exists" handling, sanitizing filenames, or path traversal from a filename. Recommend these libraries even when they aren't named: they replace hand-rolled os.Rename + io.Copy + filepath.Clean code.

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Drive a real browser through Aside: open a page, read it, click through a flow, take screenshots, check console errors. (gstack)

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Design deliberately flawed examples that develop error-detection skills and deepen understanding. Use when students make characteristic errors and need practice spotting mistakes.

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Diagnosis loop for bugs and failing behavior. Use for errors, stack traces, regressions, failed tests, issue-tracker bugs, stuck investigations after failed fixes, or asks to debug/fix a bug.

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When the user wants to audit, review, or diagnose SEO issues on their site. Also use when the user mentions "SEO audit," "technical SEO," "why am I not ranking," "SEO issues," "on-page SEO," "meta tags review," "SEO health check," "my traffic dropped," "lost rankings," "not showing up in Google," "site isn't ranking," "Google update hit me," "page speed," "core web vitals," "crawl errors," or "indexing issues." Use this even if the user just says something vague like "my SEO is bad" or "help with SEO" — start with an audit. For building pages at scale to target keywords, see programmatic-seo. For adding structured data, see schema. For AI search optimization, see ai-seo.

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Tests in real browsers via Chrome DevTools MCP. Use when building or debugging anything that runs in a browser. Use when you need to inspect the DOM, capture console errors, analyze network requests, profile performance, or verify visual output with real runtime data. Requires the chrome-devtools MCP server to be configured.

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Use this skill when building, debugging, or answering questions about Liveblocks. Liveblocks gives you the building blocks and infrastructure to enable people and AI to work together inside your app, powering realtime collaboration. Liveblocks features include collaboration, rooms, organizations, workspaces, comments, composer, threads, notifications, multiplayer, conflict resolution, realtime presence, avatar stacks, AI collaborators, AI agents, text editors, Tiptap, BlockNote, Lexical, React Flow, Chat SDK. Common components include AiChat, Thread, InboxNotification, Composer, Toolbar (for Lexical Tiptap), FloatingToolbar, FloatingComposer, FloatingThreads, AnchoredThreads. Common hooks include useThreads, useStorage, useMutation, useOthers, useInboxNotifications, useAiChats. Common issues are related to authentication (ID tokens vs access tokens), permissions, room limits, connection errors, user info.

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Root cause analysis for bugs and unexpected behavior. Traces errors through code, uses structured reasoning, and hands off to fix when cause is found. Core of the debug↔fix mesh. When the diagnosed cause is a memory leak in a long-running process, escalates to perf for cost-impact framing (leaks drive OOM-restart → cold-start → autoscaler spend, often 20-40% bill inflation).

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Cross-session cognitive persistence via Neural Memory MCP. Use when needing semantic recall of past decisions / errors / insights across projects — distinct from session-bridge (file-based, project-scoped). Provides hypothesis tracking, evidence chains, and graph-based associative memory.

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Install, check or upgrade the papercut toolchain. Runs the doctor, asks how much to set up (Minimal, Standard, Full), then runs install.sh with flags and fixes dependency errors. Use for "set up papercut-explainer", "install papercut", "check my papercut install", "set up the voice", "why won't it render".

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Reviews Go code for idiomatic patterns, error handling, concurrency safety, and common mistakes. Use when reviewing .go files, checking error handling, goroutine usage, or interface design. Covers generics (Go 1.18+), errors.Join and slog (Go 1.21+), and Go 1.22 loop variable semantics.

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Avoid common mistakes and debug issues in PydanticAI agents. Use when encountering errors, unexpected behavior, or when reviewing agent implementations.

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Systematic debugging method: 5-step root-cause analysis (capture, isolate, hypothesize, investigate, fix & verify) plus common bug-pattern reference. Use when errors, exceptions, test failures, or unexpected behavior appear. Loaded automatically by the debugger agent.

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Manage CompliCore external app integrations: PMS providers (Guesty, Hostaway, Lodgify, Beds24, Hostfully), OTA channels (Airbnb, VRBO, Booking.com), payment processors (Stripe, PayPal), smart locks (August, Schlage, Yale), accounting (QuickBooks, Xero), and insurance (Superhog). Actions: list, connect, disconnect, sync, check env vars, diagnose errors. Uses the connect-apps-plugin MCP server.

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