783 件 ・ 関連度順
概要と使いどころ
Create product backlog items in Why-What-Acceptance format — independent, valuable, testable items with strategic context. Use when writing structured backlog items, breaking features into work items, or using the WWA format.
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Create job stories using the 'When [situation], I want to [motivation], so I can [outcome]' format with detailed acceptance criteria. Use when writing job stories, creating JTBD-style backlog items, or expressing user situations and motivations.
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 comprehensive test scenarios from user stories with test objectives, starting conditions, user roles, step-by-step actions, and expected outcomes. Use when writing QA test cases, creating test plans, defining acceptance tests, or preparing for feature validation.
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Is a story implementation-ready? Checks clear acceptance criteria, open questions, ADR refs. READY/NEEDS WORK/BLOCKED/NOT ASSESSED.
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。
End-of-story completion review — verifies each acceptance criterion, checks GDD/ADR deviations, prompts code review, updates status.
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。
Break one epic into implementable stories embedding TR-ID, ADR guidance, acceptance criteria. Reads the control manifest. After /create-epics.
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。
Plan or divide a named NemoClaw issue into independently useful changes with acceptance evidence. Use for planning requests before implementation.
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Design and acceptance gates for centrally enforcing sandbox outbound network policy.
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。
Hardens LifeOS tests via property/mutation testing. USE WHEN harden, hardening, property test, property based testing, PBT, fast-check, mutation test, mutation testing, Stryker, CRAP score, CRAP analysis, DRY scan, jscpd, acceptance test mutation, strengthen tests, sharpen ISCs, find bugs example tests miss, universal quantified claim, shrink counterexample, what bugs am I missing, test the tests, test of the test. NOT FOR writing new feature tests (use bun test directly), grading agent output quality (use Evals), UI verification with real Chrome (use Interceptor), finding security vulnerabilities, or building new functionality.
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。
Reference-only OpenClaw adaptation of SkillOpt-Sleep. Use it to study or port the contributed DeepSeek wrapper, not as a ready-to-run installation.
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。
Linux networking expert for iptables, nftables, routing, DNS, and network troubleshooting
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。
This skill should be used when the harness, scaffold, workflow, or optimizer itself is the optimization target: recursive self-improvement (RSI) loops, meta-harnesses, self-improving harnesses that mine their own failures and propose bounded edits, evolutionary or population-based search over agent scaffolds, acceptance gates for self-modifying systems, and agentic context evolution where the mechanism that produces context is versioned and evolved. Route governance of a single autonomous loop (locked surfaces, durable logs, rollback, novelty gates, approval boundaries) to harness-engineering, measurement and quality-gate design to evaluation, judge design to advanced-evaluation, and remote sandbox infrastructure to hosted-agents.
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。
Manage a stateful, run-directory-based proof project with Codex: continuation across runs, run-local source bookkeeping, manual GPT Pro handoff packages when a local attempt stalls, and an optional DeepSeek second opinion as additional evidence only. Use when the user asks for proof-run orchestration, a GPT Pro handoff, or cross-run proof continuation — use /proof-writer for ordinary proof drafting and /proof-checker for rigorous verification or submission acceptance.
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。
Manage a stateful, run-directory-based proof project: continuation across runs, run-local source bookkeeping, manual GPT Pro handoff packages when a local attempt stalls, and an optional DeepSeek second opinion as additional evidence only. Use when the user asks for proof-run orchestration, a GPT Pro handoff, or cross-run proof continuation — use /proof-writer for ordinary proof drafting and /proof-checker for rigorous verification or submission acceptance.
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。
Workflow 1 adaptation for robotics and embodied AI. Orchestrates robotics-aware literature survey, idea generation, novelty check, and critical review to go from a broad robotics direction to benchmark-grounded, simulation-first ideas. Use when user says \"robotics idea discovery\", \"机器人找idea\", \"embodied AI idea\", \"机器人方向探索\", \"sim2real 选题\", or wants ideas for manipulation, locomotion, navigation, drones, humanoids, or general robot learning.
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。
Workflow 1 adaptation for robotics and embodied AI. Orchestrates robotics-aware literature survey, idea generation, novelty check, and critical review to go from a broad robotics direction to benchmark-grounded, simulation-first ideas. Use when user says "robotics idea discovery", "机器人找idea", "embodied AI idea", "机器人方向探索", "sim2real 选题", or wants ideas for manipulation, locomotion, navigation, drones, humanoids, or general robot learning.
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。
Communications-domain literature review with Claude-style knowledge-base-first retrieval. Use when the task is about communications, wireless, networking, satellite/NTN, Wi-Fi, cellular, transport protocols, congestion control, routing, scheduling, MAC/PHY, rate adaptation, channel estimation, beamforming, or communication-system research and the user wants papers, related work, a survey, or a landscape summary.
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。
Fine-tunes and evaluates OpenVLA-OFT and OpenVLA-OFT+ policies for robot action generation with continuous action heads, LoRA adaptation, and FiLM conditioning on LIBERO simulation and ALOHA real-world setups. Use when reproducing OpenVLA-OFT paper results, training custom VLA action heads (L1 or diffusion), deploying server-client inference for ALOHA, or debugging normalization, LoRA merge, and cross-GPU issues.
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。
Read before automating LinkedIn with browser_* tools. LinkedIn combines shadow DOM (#interop-outlet), strict Trusted Types CSP that silently drops innerHTML, Lexical composer, native beforeunload dialogs that hang the bridge, and aggressive spam filters — each has bitten us at least once. Verified flows for profile messaging, connection-request acceptance, feed composition, and search. Requires hive.browser-automation. Verified against logged-in production 2026-04-11.
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 intake — practice-area templates, cross-area issue spotting, conflict flags, and triage classification. Produces a formatted case summary the student analyzes and the professor reviews. Does NOT decide case acceptance. Use when starting a new client intake, running an intake interview, or writing up a new client's situation.
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。
Enrolls a project in OSS-Fuzz, Google's free continuous fuzzing service for open source, and drives it locally. Covers project.yaml, Dockerfile and build.sh setup, the helper scripts, reproducing OSS-Fuzz crash reports, and the acceptance criteria. Use when setting up continuous fuzzing for an open-source project, reproducing an OSS-Fuzz bug report, or testing an OSS-Fuzz build before submitting 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。
Prompt- and template-complete Google Docs creation and editing with explicit-instruction-authoritative structural preservation, including semantic roles, relationships, comparison dimensions, and instructed extensions; full-topology native-copy routing; source-grounded per-tab adaptation for past/example references; style-preserving hyperlink and table edits; canonical smart-chip-first authoring for dates and relevant supported people or Google resources; a file-backed advisory trusted read before existing-document writes; automatic protected-control awareness; direct connector APIs by default; DOCX-first import only when no supplied Google Doc template/reference constrains the output; and checked-in code mode only for exact native dropdown mutation. Use when Codex must create, edit, fill, adapt, redesign, or verify Google Docs without overriding explicit user/template instructions, adding unrequested document scope, or carrying stale reference facts into a new deliverable.
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。
Publish a validated Data Analytics report or dashboard artifact through Sites. Use automatically for durable artifacts in any positively identified Work Mode when the full Sites lifecycle is callable, or in ChatGPT Desktop outside Work Mode only after an explicit Sites request or acceptance of the optional post-handoff sharing offer.
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Port an existing mod to a newer game version or another mod loader while keeping its behaviour, values and quirks. Typical cases are an old Forge 1.7.10 or 1.12 Minecraft mod moving to modern Fabric or NeoForge, a Skyrim LE plugin moving to SE/AE, or a tModLoader 1.3 mod moving to 1.4. It covers pinning one source version, a private decompiled reference, an adaptation matrix, extracting the mod's data with scripts instead of retyping it, porting unit by unit with tests that catch drift, real-client checks, audits against the original, and keeping a long port resumable across sessions and agents. Use when the user wants to update, port, revive or re-implement a mod that already exists, or to continue such a port.
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。