4,534 件 ・ 関連度順
概要と使いどころ
Apply the local C++ coding conventions of the EMULATORS framework. Use when Codex adds, edits, reviews, or scaffolds C++ code in this repository, especially new classes, headers, cpp files, CORE/COMMODORE module code, emulator components, registers, chips, memory, sound, IO, commands, or InfoClass-derived objects.
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。
Validate Commodore 64 VIC-II emulation in EMULATORS, including $D000-$D3FF register behavior, PAL/NTSC timing, raster counters, badlines, BA/AEC bus stealing, video matrix and bitmap fetches, sprites, collisions, borders, IRQs, color RAM usage, and display modes. Use when Codex reviews or edits VICII, Screen, Memory/PLA, raster, sprite, video, or cycle-level behavior for C64 classes.
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。
Validate and implement Sinclair ZX Spectrum 16K/48K ULA and board-level behavior in the EMULATORS repository, including PAL/NTSC raster timing, bitmap and attribute fetches, FLASH/BRIGHT/INK/PAPER rendering, CPU clock generation, lower-RAM and I/O contention, floating bus, snow effect, DRAM addressing and refresh, port FE keyboard/tape/border/sound behavior, interrupts, and ULA revision boundaries. Use when Codex reviews or edits namespace ZXSPECTRUM ULA, ULARegisters, Memory, PortManager, Screen, Sound, Datasette, Z80 bus timing, raster, contention, or ZX Spectrum hardware tests.
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。
Validate Commodore 64 memory map, PLA/bank switching, 6510 port $0000/$0001 behavior, VIC bank selection, color RAM, ROM/RAM overlays, cartridge mapping, and mirrored I/O in the EMULATORS C64 namespace. Use when Codex reviews or edits C64 memory, PLA, CPU-visible address decoding, VIC-visible memory, color memory, char ROM, cartridge, expansion I/O, or mapped chip register behavior.
日本語の概要は準備中です。原文の説明を表示しています。
Recreate the nuxt-crouton dev environment from scratch and survive its install/build traps — the pnpm toolchain, the cold-start sequence (why packages must build before apps prepare), the version catalog and workaround pins, the per-app typecheck rule, required env vars, and the known environment traps. Use when setting up a fresh clone/worktree, when "pnpm install" or "nuxt prepare" fails, when an app won't boot after install, when typecheck output looks insane, or when a tool "isn't available". Trigger phrases: "set up the repo from scratch", "why does typecheck show thousands of errors", "playwright install fails", "what pnpm/node version". (Exact error strings — "Could not load '@fyit/crouton'", "Cannot find module '@vue/compiler-sfc'" — route via crouton-diagnostics-index first; it points back here for depth.)
日本語の概要は準備中です。原文の説明を表示しています。
Symptom → root-cause lookup table for nuxt-crouton's recurring failure modes — exact error strings mapped to their known cause, fix, and evidence issue. Use when you hit an error you don't recognize in this repo, before debugging from first principles. Trigger phrases and symptoms: "Cannot resolve entry module .nuxt/hub/db/schema.entry.ts", "Could not load '@fyit/crouton'", "No migrations present", "No schema files found", "$setup.t is not a function", "does not provide an export named 'Map'", "no such table: translations_ui", "collection pages 500 in production", "the build was green but the app is broken", "is this a known issue?".
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。
The case-law chronicle of this repo's major failures — symptom, root cause, evidence, status, and the rule each battle minted — so nobody re-fights a settled battle or re-proposes a rejected fix. Use when a bug/incident looks familiar ("didn't this happen before?"), when you're about to propose an approach that may have been tried and rejected (e.g. shipping a migration from a package), when someone asks "why does rule X exist" / "why is done-by-lgtm a thing" / "what was incident 988", or when a bug-archaeology run hits the shallow-clone wall and needs the pre-June-2026 history. Trigger phrases: "has this broken before", "why can't packages ship migrations", "why did graduation fail", "why is the green-build lesson a rule", "what did we learn from incident NN". (For a live "build is green but the app is broken" symptom, start at crouton-diagnostics-index. NB keep this description free of any space-then-hash sequence — an unquoted YAML scalar treats space-hash as a comment start and silently truncates.)
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。
Resolve, validate, and audit manuscript integrity and applicable requirements for academic manuscripts and paper artifacts. Use when Codex needs to determine active paper rules from manuscript state, paper type, venue, submission stage, or workflow mode; lint a LaTeX paper project; assess submission readiness; create or update a paper policy profile; explain why a rule is active; or validate the paper-policy registries. Do not use as the primary skill for prose drafting, peer review, rebuttal writing, citation discovery, or figure/table creation.
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。
Audit a codebase or subsystem for architecture simplification - shallow or pass-through modules, scattered concepts, naming drift, sibling workflows that disagree, weak test seams. Use when the user asks what to simplify or restructure. Not for a narrow fix or for implementing an already chosen design.
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。
Judge performance or resource claims on real hardware: benchmark design or review, latency, throughput, memory or headroom numbers, and accept-or-reject decisions on optimizations. Not for refactors with no resource claim.
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。
Use when the deliverable is authored or edited prose whose wording matters (docs, READMEs, release notes, public copy) or when the user asks to tighten, de-AI, or review writing. Not for chat answers, code review, or explanations of current work.
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。
Get structured data from catalogued providers instead of scraping pages. Firecrawl Alexandria is a library of official APIs, licensed publishers, and Firecrawl indexes (financial series, company data, government contracts and law, podcasts, listings, research). Use this skill when the user needs records, listings, prices, filings, transcripts, or a dataset, says "is there an API for", "find a data source for", "pull the records", "get the dataset", or when assembling the answer by scraping would take many pages that one provider call returns directly. Discover with search, inspect with find_tools, execute with scrape.
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。
Search an index built for coding agents — GitHub issues, merged pull requests, repository READMEs, and curated documentation sites — and get back the matched passages, not just links. Use this skill whenever the question is about code: how a library, framework, or API behaves, what an error message or stack trace means, whether a bug was reported or fixed, what a function returns, what a default is, or which repos do a given thing. Triggers on "why does <library> do X", "what does this error mean", "is this a known bug", "how do I use <library>", "what's the API for", pasted stack traces, and pasted error strings. Prefer this over a general web search for programming questions — it answers from the primary source instead of a blog post about it.
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。
自セッションで評価せず外部LLMに委譲したいとき、Sycophancyを避けたいときに使う。
Discover, compare, and compose existing open-source GitHub repositories for a user's goal, using GitHub MCP for live discovery and verification plus Context7 semantic retrieval over repository code and official documentation. Use when a user asks for GitHub repo recommendations, open-source alternatives, a multi-repository solution stack, project comparison, or help choosing an implementation to adopt.
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 and use the Exasol Text AI Extension (TXAIE) with notebook-connector. Covers `deploy_license`, `initialize_text_ai_extension`, the `PYTHON3_TXAIE` language container, the Extraction API classes `StandardExtractor`, `NamedEntityExtractor`, `TopicClassifierExtractor`, `PipelineExtractor`, and `BranchExtractor`, named-entity, zero-shot classification, and feature extraction runs, default-model installation, and result-table querying such as `TXAIE_AUDIT_LOG`.
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。
Use this skill to process one to 99 local exact 2:1 equirectangular panorama images with Realsee Argus, producing depth maps, a merged GLB point cloud, camera poses, optional intrinsics, and a validated local output index. Trigger for Argus panorama reconstruction, Argus ZIP input, or explicit Argus start/status/collect lifecycle requests. Do not trigger for panorama editing or stitching, arbitrary-photo 3D generation, existing GLB inspection, or research-only questions.
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。
Convex backend specialist. Use this agent for any code inside a `convex/` directory — function definitions, schemas, indexes, queries, mutations, actions, HTTP endpoints, cron jobs, file storage, auth wiring, and component installation. Knows the object-form function syntax, validator patterns, resource limits, and component ecosystem that generic Claude routinely gets wrong.
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。
Design and generate Convex database schemas with proper validation, indexes, and relationships. Use when creating schema.ts or modifying table definitions.
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。
Design and build reactive, type-safe, production-grade backends on Convex. Covers schema, queries/mutations/actions, indexes, auth, file storage, scheduling, real-time multiplayer, mobile backends, and LLM/agent workflows on Convex's one-platform stack.
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。
Design and generate Convex database schemas with proper validation, indexes, and relationships. Use when creating schema.ts or modifying table definitions.
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。
Design and build reactive, type-safe, production-grade backends on Convex. Covers schema, queries/mutations/actions, indexes, auth, file storage, scheduling, real-time multiplayer, mobile backends, and LLM/agent workflows on Convex's one-platform stack.
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。