「orw」の検索結果

Produces a rigorous, forward-looking technical audit with severity ratings and improvement directions.

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。

Authoritative reference for working with the released Wandelbots NOVA API v2 in the wandelbots-nova Python SDK. Use whenever a task touches the NOVA API, the generated `wandelbots_api_client` models (`nova.api.models.*`), motion planning requests (`plan_trajectory`, `MotionGroupSetup`, `LimitSet`, `LimitsOverride`), robot limits, or torque/velocity/acceleration/jerk limits. Reach for this skill before guessing field names or assuming a field exists — the installed client reflects the RELEASED API, while nightly specs may contain unreleased fields. Especially relevant for controller-reported limits (e.g. KUKA torque) and any "does field X exist / how is it forwarded to the planner?" question.

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 uncommitted changes need to be split into atomic, conventional commits ordered for review. Triggers on "commit this", "make commits", "clean up commits", "commit the changes". In Hedgehog, each Loop step is already meant to be its own commit — this skill matters most when a Correction Protocol fast-forward touches several steps at once and those fixes need splitting back into per-step commits.

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 verifying that a model in the imp inference engine produces coherent output without repetition loops, token-stuck states, or state corruption across turns or streams. Triggers on "degenerates", "check degeneration", "repetition loop", "own own own", "stuck token", "empty content", "multi-turn regression", "does it still work", "NIAH", and after enabling CUDA graphs / changing forward pass / MoE routing / KV cache or KV dtype / GDN state or scan / sparse attention / PDL / speculation (MTP, n-gram) / ragged prefill / batched-decode kernels (smallm, producer quantize) / FA2 softmax.

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 currency hedging models with rolling forward programs, option-based strategies, and cross-hedge analysis for international portfolios. Use when designing hedge programs, analyzing hedge ratios, or evaluating FX protection costs.

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。

Evaluates commodity price exposure with forward curve analysis, hedging strategies, and break-even price sensitivity. Use when analyzing commodity risk, designing hedging programs, or stress testing price assumptions.

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。

After an issue's PR has squash-merged on GitHub and its issue has closed: fast-forward the default branch, remove the issue-numbered nested worktree (.worktrees/<issue#>), and delete the local feature branch. Use when the user says to finish, tear down, or clean up a lane or worktree for a merged 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。

Validated Google Play release — runs the pre-flight checks and clears the Play policy gates, builds a signed app bundle with a git-stamped versionCode, uploads to a track, and walks staged rollout (with halt/roll-forward). Use when releasing an Android app to Play.

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。

Produces structured markdown session continuation documents for multi-session workflows. Captures active work streams, decisions with rationale, knowledge-file deltas learned during the session, the exact files to load next conversation, ingested content, artifacts, and open items into an ingestion-optimized handoff. Carries pending KF updates and unresolved items forward across handoff chains so context never drops. Generates a closeout checklist and echoes the starter prompt to chat. Use when approaching context limits, wrapping up a session, or managing work across conversations. Trigger on: "create a handoff," "session closeout," "wrap up this session," "build session handoff," "BSH," "continue next session," "we're running out of context," "context is getting long." Do NOT use for Memory optimization, context budget analysis, project audits, deciding whether work is ready for autonomous/Claude Code execution (use rootnode-handoff-trigger-check), or summaries with no continuation intent.

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 ornamental patterns using modern and speculative aesthetics with colorblind-accessible color scales. Breaks free from historical period constraints to explore cyberpunk, solarpunk, biopunk, brutalist, vaporwave, and other contemporary genres. Includes CVD (Color Vision Deficiency) awareness and perceptually uniform scales (viridis, cividis, inferno). Use when creating ornamental designs in modern or genre-specific aesthetics, designing patterns that must be colorblind-accessible, or exploring hybrid motifs combining historical ornament with contemporary visual language.

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。

Fit hidden Markov models using the Baum-Welch (EM) algorithm with model selection, Viterbi decoding for state sequences, and forward-backward probabilities. Use when observations are generated by unobservable latent states, you need to segment a time series into latent regimes (market regimes, speech phonemes, biological sequences), compute sequence probabilities, decode the most likely hidden state path, or compare models with different numbers of hidden states.

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。

Perform controlled dismantling of rigid system structures while preserving essential capabilities (imaginal discs). Covers rigidity mapping, dissolution sequencing, knowledge extraction, interface archaeology, and safe decomposition of technical debt and organizational calcification. Use when assess-form classified the system as PREPARE or CRITICAL, when a system is so calcified that incremental change is impossible, when technical debt blocks all forward progress, or before adapt-architecture when the current form must be softened before it can be reshaped.

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 reducing header bloat and compilation cascades with Include What You Use, interpreting IWYU reports, mapping files, forward declarations, or CMake integration.

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 explaining pipeline stages, data or control hazards, forwarding, stalls, or superscalar basics behind a counter reading. Not for mispredict cost: use branch-prediction-and-speculation.

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 RFDB data disappearing after compaction, where rfdb-server reports a tiny node count (e.g. "15 nodes") on startup despite manifest_index.json showing hundreds of thousands of nodes and segment files existing on disk. Use when: (1) rfdb-server logs "Default database: N nodes" with N orders of magnitude smaller than recent analysis output, (2) /api/stats returns only the most recent commit's nodes, (3) the issue appears AFTER a compaction event (manifest with l1_node_segments populated and node_segments: []), (4) subsequent commits dropped L1 references. Root cause: ManifestStore::create_manifest() initializes l1_node_segments/l1_edge_segments to Vec::new() instead of cloning from current manifest, so any commit AFTER compaction silently orphans all L1 data even though segment .seg files still exist on disk. Compaction injects L1 fields explicitly after create_manifest, but regular commits do not.

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。

Recover from stale RFDB nodes that survive `commit_batch` cleanup despite having their `file` field listed in `changed_files`. Use when: (1) re-running an enricher/orchestrator step but old data with the same file field stays in the graph, (2) `commit_batch(changed_files=[X], ...)` reports success but a query later still returns nodes with `file = X`, (3) you re-pointed structural nodes (e.g., DIRECTORY/FILE) from a synthetic file path to real file paths and the old synthetic-path nodes won't go away, (4) graph-stream / find_by_type returns a mix of "stale" and "new" nodes for the same logical entity. Root cause: `handle_commit_batch` calls `engine.find_by_attr({file: X})` to enumerate nodes-to-delete, but that query path returns only a PARTIAL set after compaction (L1 segments and the file→nodes index can desync). Workaround: enumerate stale nodes via the TS rfdb client `queryNodes({file: X})` (different code path that finds all of them) and call `deleteNode(id)` per node, then re-commit the intended state. Related: rfdb-manifest-l1-carryforward (same L1 family).

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。

Guide for implementing smooth, native-feeling animations using React's View Transition API (`<ViewTransition>` component, `addTransitionType`, and CSS view transition pseudo-elements). Use this skill whenever the user wants to add page transitions, animate route changes, create shared element animations, animate enter/exit of components, animate list reorder, implement directional (forward/back) navigation animations, or integrate view transitions in Next.js. Also use when the user mentions view transitions, `startViewTransition`, `ViewTransition`, transition types, or asks about animating between UI states in React without third-party animation libraries.

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。

在基础模型适配完成后，按算法适配并安装 Adapter 接口，依据目标模型真实 forward 生成并验证 final-logits patch，执行单算法 msModelSlim 离群值抑制变换、官方计算图提取和浮点 logits 门禁。

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。

Structured marketing brainstorming when direction is unclear. Use when the agent doesn't know which skill to run, the user is vague about what they need, there are multiple valid marketing paths, or someone says 'I don't know where to start', 'what should we market', 'explore approaches', 'help me think through this', 'marketing ideas', 'what campaign should I run', 'where do I start with marketing', 'what's our marketing plan', or 'I have no idea how to promote this'. Explores 2-3 approaches and recommends the best path forward with a specific next-skill handoff. Even vague frustration like 'nobody knows about my product' or 'how do I get users' should trigger this when no specific channel or tactic is mentioned.

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。

kbo-cli 새 버전을 릴리즈한다. develop 에서 package.json 버전을 올리고 커밋·태그를 만든 뒤, main 을 develop 으로 fast-forward 동기화해 origin 으로 push 하면, GitHub Actions 가 npm 배포와 GitHub Release 생성을 처리한다. 인자 형식 — `/release` (patch), `/release minor`, `/release major`, `/release 1.2.3` (명시 버전).

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 phrasing a forward-looking statement, the user asks "how likely is X?" / "what's the likelihood?", or the tradecraft pipeline applies a probability yardstick to a finished product. Standardised likelihood language across all products.

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。

Iterative literature-review workflow for a research topic. Use this skill to draft up to 10 search keywords, build a seed set from OpenAlex title-and-abstract matches, expand by backward and forward citations, screen candidates by title and abstract, repeat until no new relevant papers remain, rank the final set, inspect up to 30 full texts, build a concept-reference knowledge graph, and write a literature review grounded only in the final included references.

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。

"Summarize and analyze earnings calls (法說會) including financial highlights, management commentary, guidance, and analyst Q&A key takeaways. Use this skill when the user needs to digest an earnings call transcript, extract key financial data and forward guidance, compare actual results vs consensus estimates, or prepare for an investor meeting — even if they say 'summarize this earnings call', 'what did management say about next quarter', 'did they beat estimates', or 'key takeaways from the 法說會'.".

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。

Analyze budget-versus-actual or forecast-versus-actual performance and turn finance data into a management-ready narrative using variance logic, drivers, cash impact, and forward actions. Use when finance, FP&A, or business leaders need commentary, management accounts, or performance explanation. Do not use for bookkeeping entries, tax filing preparation, or legal accounting sign-off.

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。