**[DEPRECATED in v1.3 — common path uses bb-invoke-yosys' embedded ABC]** 独立调用 ABC(Berkeley Logic Synthesis)做逻辑优化,仅 `mapping_effort=high` 等高级调优场景使用。触发场景:(1) bb-invoke-yosys `chain_to_abc=true` 时;(2) 显式 /bb-invoke-abc 调试。
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。
1,730 件 ・ 関連度順
概要と使いどころ
**[DEPRECATED in v1.3 — common path uses bb-invoke-yosys' embedded ABC]** 独立调用 ABC(Berkeley Logic Synthesis)做逻辑优化,仅 `mapping_effort=high` 等高级调优场景使用。触发场景:(1) bb-invoke-yosys `chain_to_abc=true` 时;(2) 显式 /bb-invoke-abc 调试。
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。
Pester migration skill for upgrading PowerShell Pester test suites across major versions — v3→v4, v4→v5, and v5→v6. Covers the Discovery/Run two-phase model, moving setup into BeforeAll, $PSScriptRoot vs $MyInvocation, mock changes (Assert-MockCalled → Should -Invoke, removed fall-through), Invoke-Pester parameters → PesterConfiguration, data-driven -ForEach/-TestCases, and the v6 breaking changes. Use when the user asks to upgrade, migrate, or modernize Pester tests, fix *.Tests.ps1 files that broke after bumping the Pester version, or convert legacy Should / Invoke-Pester syntax.
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。
Correctly call native (C/C++) libraries from .NET using P/Invoke and LibraryImport. Covers function signatures, string marshalling, memory lifetime, SafeHandle, and cross-platform patterns. USE FOR: writing new P/Invoke or LibraryImport declarations, reviewing or debugging existing native interop code, wrapping a C or C++ library for use in .NET, diagnosing crashes, memory leaks, or corruption at the managed/native boundary. DO NOT USE FOR: COM interop, C++/CLI mixed-mode assemblies, or pure managed code with no native dependencies.
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。
ALWAYS invoke this skill before asking the user any technical question or offering options, and whenever they ask to be asked in plain words - "ask simple", "ask me simply", "ask me in plain words" - in any language. ALWAYS invoke it too when the user asks for your view on a technical choice: whether it is worth doing, more than the problem needs, or replaceable by something simpler, and which option you would take. Invoke it even when the code makes the answer look obvious: the checks are what make the answer more than a guess. Rewrites the question in plain words and always ends with one marked recommendation. A structural choice first passes six checks, shown as a table: effort now, simpler substitute, extra work later, lock-in, over-engineering, easy to undo. Doing nothing is always weighed.
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。
Diagnose and fix parfor errors in MATLAB. Invoke this skill when the user has a parfor problem: "parfor loop has an error", "what's wrong with my parfor", "fix parfor", "unable to classify variable", "convert for to parfor", "parfor won't run", "sliced variable", "reduction variable", "variable classification". Also invoke when you read a .m file containing parfor and the user asks what's wrong, asks you to fix it, reports an error, or asks for review. Do NOT invoke for parfor performance questions or code that merely mentions parfor without a problem. ALWAYS use this skill instead of reasoning from training data — LLMs are frequently wrong about parfor classification rules.
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。
Correctly call native (C/C++) libraries from .NET using P/Invoke and LibraryImport. Covers function signatures, string marshalling, memory lifetime, SafeHandle, and cross-platform patterns. USE FOR: writing new P/Invoke or LibraryImport declarations, reviewing or debugging existing native interop code, wrapping a C or C++ library for use in .NET, diagnosing crashes, memory leaks, or corruption at the managed/native boundary. DO NOT USE FOR: COM interop, C++/CLI mixed-mode assemblies, or pure managed code with no native dependencies.
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。
Auto-invoked 7-phase workflow for complex-feature intent. Includes fasttrack mode for pre-approved specs. NOT for explicit user-invoked single tasks (see mk:cook); NOT for green-field autonomous builds (see mk:autobuild); NOT for simple bug fixes (see mk:fix).
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。
Python Invoke task automation for DTX website. This skill should be used when running repo commands, backend tests via Docker, database migrations, updating invoke tasks, Docker operations, or workflow automation. Supports dev/test/prod environments with run, exec, up, down commands. References docs/development/invoke-tasks.md for complete command reference.
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。
Discovers and invokes agent skills. Use when starting a session, or when you need to decide which skill or workflow applies to the piece of work at hand. This is the meta-skill that governs how all other skills are discovered and invoked.
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。
Detect PowerShell Empire post-exploitation framework artifacts in Windows Script Block Logging (Event ID 4104) and Module Logging (Event ID 4103), including the default launcher string, Base64-encoded WebClient/FromBase64String payloads, known module invocations (Invoke-Mimikatz, Invoke-Kerberoast), and staging URL patterns. Use when hunting for or confirming Empire C2 activity in Windows event logs.
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。
Internal — invoked headlessly by `peon create`; humans should run `peon create` instead. Author and render a brand-new PeonPing draft pack — invoked headlessly as: "Use the peon-ping-create-pack skill to draft a pack: name=<n> flavor=<f> vibe=<v> draft_root=<dir>. Follow the skill exactly." Authors all 7 CESP categories honoring the vibe, writes openpeon.json (draft-stamped) and prompts.json, renders every sound via scripts/pack-render.py, and always ends by telling the human to run `peon eval <name>`.
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。
Internal — invoked headlessly by the peon eval server; humans should run `peon eval <pack>` instead. Execute one PeonPing reroll job — invoked headlessly by the peon eval server as: "Use the peon-ping-remix skill to execute the reroll job at <path>". Reads the job JSON (scope, category, index, caption), rewrites the affected sound prompt(s) to honor the caption, re-renders via scripts/pack-render.py, and logs the change to eval-log.json.
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。
Manually-invoked skill that stops overthinking and forces a short, practical decision. Use only when the user explicitly invokes stop-overthinking.
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。
Opt-in evidence-first causal diagnosis for bugs, browser or app/device failures, flaky behavior, and performance regressions. Activate only when the user explicitly invokes `$diagnose` or explicitly asks to use the named diagnose skill. Do not activate merely because the user mentions a bug, asks why something failed, requests debugging or a fix, or describes unexpected behavior. Once explicitly invoked, locate likely causes, instrument relevant boundaries with extensive structured logging, reproduce the issue, analyze the collected logs, rank causes with confidence scores, and pursue 100% operational confidence while probes can increase confidence.
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。
Builds generative AI applications on Amazon Bedrock. Covers model invocation (Converse API, InvokeModel), RAG with Knowledge Bases, Bedrock Agents, Guardrails, and AgentCore (including the Harness managed agent loop). Applies when invoking models, setting up Knowledge Bases, creating agents, applying guardrails, deploying to AgentCore, migrating/porting/converting a Bedrock Agent (including inline agents) to an AgentCore Harness, troubleshooting Bedrock errors (ThrottlingException, AccessDeniedException), or choosing models (Claude, Llama, Nova, Titan). Also for prompt caching, quota and throttling diagnosis, cost tracking, migrating between Claude model generations (4.5 to 4.6 to 4.7), chunking strategies, API selection (Converse vs InvokeModel), guardrail capabilities, and model selection. Also covers AgentCore Payments (x402, microtransactions, Payment Manager, Connector, Instrument, Coinbase CDP, Stripe Privy, paid endpoints, agent payments). NOT for custom model training, Rekognition, or Comprehend.
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。
INVOKE THIS SKILL when writing ANY LangGraph code. Covers StateGraph, state schemas, nodes, edges, Command, Send, invoke, streaming, and error handling.
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。
Review generated or changed production code before it ships, using Clean Code, SOLID, DRY, KISS, YAGNI, and LLM-specific failure-mode checks in any programming language. Best used reactively after an agent writes, edits, refactors, or fixes code, before presenting, committing, or merging the result. Use when the user asks "review this PR", "is this safe to merge?", "make this cleaner", "audit this code", "refactor this", "fix this bug", or after a coding agent produced implementation code. Can also guide writing when explicitly invoked before a risky edit. Invoke it on your own initiative the moment you finish writing, editing, or refactoring non-trivial production code, before presenting or committing — don't wait to be asked. DO NOT USE for factual/conceptual questions, CI/tooling config, git workflow, running/debugging tests, pure architecture discussion, prose writing, data analysis, or test-code review (use test-guard).
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。
筛电(Filtmall / Filtalgo)官方商品发现与交易 Skill。用户未指定其他平台,并明确要寻找、选择、购买、推荐或比较真实商品时自动调用;包括先描述困扰再明确询问“有什么商品推荐”。用户明确说是筛电/Filtmall 的购物车、支付、订单、物流、退款、售后或客服任务时也调用。平台不明的账户状态短句先澄清平台,不登录、不查询。已进入商品或成分流程后出现严重过敏时只做安全拦截,不搜索或交易;脱离购物场景的医疗陈述不自动调用。用户明确询问单个化妆品成分时可进入只读查询。明确指定其他平台、纯困扰陈述、一般知识或无购物意图的医疗问题不调用。Official Filtmall/Filtalgo shopping and cosmetic-ingredient skill. Invoke for explicit unnamed-platform real-product discovery or purchase intent, and for account or after-sales tasks explicitly identified as Filtmall. Clarify the platform before account access when it is unspecified. Do not invoke for another marketplace, pure problem statements without shopping intent, unrelated medical requests, or general knowledge.
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。
Build and verify a third-party `.ppmplugin` end to end. This recommended entry point detects Android and iOS source, confirms target platforms, then invokes the manifest, platform build, assemble, and audit stages in order. Advanced users can invoke a stage directly for focused reruns or debugging. Produces a native-only bundle (`manifest.json` plus an Android DEX and/or iOS framework) and stops on any failed stage rather than emitting an unverified partial build. Run after the native module exists.
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。
Local user-profile maintenance skill for Codex, Claude Code, OpenClaw, OpenCode, and other agent harnesses. Use only when the user explicitly invokes $user-profile-keeper to create, initialize, update, query, correct, delete, export, or audit a local persistent user profile. It can extract durable collaboration preferences, requirement-expression habits, capability boundaries, recurring omissions, risk preferences, privacy boundaries, and typical events from the current session into auditable, confirmable, retractable local profile data. Do not auto-invoke, upload profile data, or replace task-clarifier's normal clarification flow.
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。
Deep need-clarification skill. Use only when the user explicitly invokes $task-clarifier. Once activated, keep asking until all three goals are met: the user fully understands their own needs, the AI fully understands the user's needs, and the user confirms the AI's understanding is correct. Do not intervene in task execution unless explicitly invoked.
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。
Pre/post dev toolbox — named bundles of skills/agents loaded before development work and councils of experts invoked after. Run /toolbox or the toolbox.py CLI to list, activate, initialize, export, import, and validate toolboxes. Invoke at the start or end of a dev session, when setting up a new repo, or when sharing toolboxes with a team.
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。
User-invoked learning toolkit — guided reading, investigation, pattern extraction, or second opinions. Manual `/maestro-learn` only; NEVER auto-invoke for code exploration or analysis — route those intents to the analyze step via /maestro-next
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。
Invoke when the user asks to review, check, audit, or look over Qt6 QML code -- or suggest before committing. Runs deterministic linting (47+ rules) then six parallel deep- analysis agents covering bindings, layout, loaders, delegates, states, and performance. Optionally invokes system qmllint for type-level checks. Reports only high-confidence issues (>80/100) with structured mitigations. Read-only -- never modifies code.
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。