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概要と使いどころ
Scaffold and amend the L1 Investment Constitution — [ALL_CAPS] placeholder bootstrap, SemVer bump rules, Sync Impact Report, MINOR/MAJOR re-examination dispatch after the gate-5 budget confirm. Thesis creation stays refused until ratification (Q83).
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 a new Lattice skill — atom, molecule, or refiner — following all framework conventions. Writing skill files manually almost always produces convention violations: wrong section order, missing confirmation gates, defaults.md without the right structure. This skill knows all of that and guides you through it. Use whenever adding any new atom, molecule, or refiner to Lattice, or when the user says 'create a new skill', 'add an atom', 'add a molecule', 'add a refiner', 'build X for Lattice', 'new lattice skill', or 'skill forge'. Does not validate, align docs, or deploy — those are separate skills you run after.
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。
Grounded in first principles, rigorously examine and refine a user's plan, task, decision, goal, strategy, proposal, or idea through structured, progressively deeper questioning, in order to bridge the gap between the User and the Agent. Use when the user explicitly requests grilling, challenge, pressure-testing, cross-examination, red-team review, pre-mortem analysis, or a decision audit. The goal is to uncover unclear objectives, hidden assumptions, contradictions, weak evidence, missing information, overlooked constraints, dependencies, risks, trade-offs, failure modes, and misalignment between intended outcomes and likely real-world results. Begin by establishing a shared understanding of the user's actual intent, goals, constraints, and success criteria. Ask focused, high-leverage questions rather than broad or repetitive ones. Adapt each question based on previous answers, probing deeper where uncertainty, unsupported assumptions, or strategic weaknesses remain. Regularly summarize the current understanding of the user's intent and position to confirm alignment, expose misunderstandings, and refine the problem or goal definition. Distinguish facts, assumptions, hypotheses, and unknowns. Challenge reasoning rigorously while remaining constructive, respectful, and solution-oriented. Continue until the reasoning is internally coherent, evidence-aware, constraint-conscious, risk-assessed, and translated into a clearer, more actionable goal, decision, or plan. Ultimately, achieving the super-alignment.
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。
Research potential partners by analyzing company profiles, product fit, market positioning, team background, and mutual connections. Combines firmographic data, content analysis, and social signals for partnership qualification and relationship mapping.
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。
Research startups and emerging companies with funding data, team composition, product positioning, market traction, and news coverage. Combines Apollo firmographics, LinkedIn team data, and web intelligence for comprehensive startup due diligence.
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。
Prepare for sales conversations with comprehensive account intelligence — company news, hiring signals, product launches, social activity, and decision-maker profiles. Combines firmographic data, news monitoring, and social signals for sales-ready briefings.
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 companies, enrich profiles with firmographic data, find job postings, and track company news through Apollo. Covers company search, detailed enrichment (industry, size, funding, tech stack), hiring activity, and news monitoring for B2B sales intelligence.
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。
Enrich any company with comprehensive firmographic data including industry, size, revenue, funding, tech stack, beneficial ownership, and regulatory status. Combines multiple data sources for complete B2B company intelligence and due diligence.
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。
Computes and interprets treatment effect measures (OR, RR, RD, HR, NNT) with calibrated confidence intervals (Wilson, Newcombe, Miettinen-Nurminen, MOVER, profile likelihood, Bender NNT) and reports marginal vs conditional estimands per FDA 2023 covariate adjustment guidance. Use when reporting treatment effects in confirmatory trials, comparing effect sizes across studies, or constructing forest plots.
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。
Tests associations between categorical variables in clinical data using chi-square, Fisher's exact, Boschloo, Cochran-Mantel-Haenszel, and modern McNemar variants with calibrated confidence intervals (Wilson, Newcombe, Miettinen-Nurminen). Use when analyzing categorical outcomes, paired binary endpoints, or testing treatment-outcome independence in confirmatory or exploratory clinical trials.
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。
Trim PCR primers from aligned reads in amplicon-panel BAMs using samtools ampliconclip. Use when processing SARS-CoV-2 ARTIC, hereditary cancer panels, ctDNA hot-spot panels, or any amplicon assay where primer-derived bases would falsely confirm reference at primer footprints.
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 a devopsdays event has confirmed a speaker and their talk, workshop, ignite, or keynote needs to appear on the event site - covers the speaker bio page, the talk page, the headshot, and multi-speaker talks.
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 a devopsdays event has sold or confirmed a sponsorship and the sponsor needs to appear on the event's site - covers both sponsors already in the shared directory and brand-new ones needing a logo and data file.
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。
Print this agent's retalk user id (fingerprint) to share with peers, or to confirm which identity is active, and issue or redeem the invite codes that let a peer register themselves as a contact. Use whenever you need your own retalk address/fingerprint, or when onboarding a peer with an invite 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。
Run the konsistent CLI, review all reported violations, and fix them in the codebase. Use when the user wants to "fix konsistent violations", "resolve konsistent errors", "clean up konsistent diagnostics", "make konsistent pass", "address structural convention violations", or asks to run konsistent and act on the results. The skill is interactive: it requires explicit user decisions when many violations stem from the same rule (rule vs. code question), explicit user confirmation before modifying any code, and a triage step for non-trivial violations. For editing `konsistent.json`, this skill defers to the `konsistent-config` skill.
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 for guided MBSE work in MATLAB — starting a new project, resuming work mid-workflow on an existing project, or answering orientation questions about how the MBSE skills fit together. Trigger when the user says they want to create, start, or set up a new MBSE project; work on a model-based systems engineering / RFLPV project; or asks which skill covers which phase. Walks through phases one at a time — propose → approve → generate → run → confirm. Use proactively whenever someone mentions starting or continuing an MBSE project.
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。
Establish the shared environment, source/runtime correspondence, target confirmation and validation evidence for MetaX vLLM upgrades. Use as the common prerequisite of the patch, attention, registry and model upgrade skills, or for an explicitly requested MetaX environment preflight; it does not perform domain-specific adaptations.
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。
Turn a vague bug report into a VERIFIED minimal reproduction and then a failing regression test, agent-driven end to end. Covers extracting the implicit repro from a thin report (env, build, steps, data), the reproduce-minimize-isolate-capture loop, git bisect to find the introducing commit, building a deterministic minimal repro (fixed seeds, frozen time, stubbed network), writing the failing regression test BEFORE the fix (red) and confirming the fix flips it green, and writing repro evidence back into the ticket. Distinguishes flaky-not-reproducible from environment-specific. Use when: "reproduce this bug," "minimal reproduction," "repro steps," "find the commit that broke it," "git bisect," "make the repro deterministic," "write a failing test for this bug," "regression test for a defect," "can't reproduce this bug." Not for: Classifying/deduplicating/severity-routing existing failures without reproducing them — that is ai-bug-triage. Generating tests from specs rather than from a defect — that is ai-test-generation. Related: ai-bug-triage, ai-test-generation, test-reliability, systematic-debugging, qa-project-context.
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。
Generate a Conventional Commits message from staged changes and wait for confirmation before committing. Use when the user asks to commit or generate a commit message.
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。
UX-тексты на русском языке: кнопки, формы, ошибки, пустые состояния, онбординг, подтверждения, уведомления, пуши и микрокопия. Use this skill whenever the user asks to write, rewrite, review, choose, or improve interface copy, product messages, UI strings, transactional emails, push notifications, toasts, snackbars, forms, empty states, onboarding, errors, confirmations, labels, tooltips, or button text. Триггеры: «текст для кнопки», «сообщение об ошибке», «текст в форму», «пустое состояние», «подпись к полю», «текст тоста», «снекбар», «онбординг», «пуш-уведомление», «микрокопия», «UX-текст», «что написать на экране…», «лейбл поля», «тултип», «подтверждение удаления», «письмо-уведомление». Для статей и постов см. skills statya и redaktura; для проектного словаря — redpolitika.
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 task completion loop with Definition of Done verification. Combines the Ralph Wiggum technique (prompt re-injection via Stop hook) with DoD-based independent verification. Claude proposes DoD criteria, user confirms, then Claude works autonomously. Stop hook re-injects the original prompt and blocks exit until all DoD items are independently verified. "/ralph", "ralph loop", "ralph 루프", "반복 작업", "DoD 루프", "완료 검증 루프", "task loop", "keep going until done"
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。
Apply when tempted to ask 'should I do X?' on reversible work. Proceed, present the result, let the human course-correct after the fact; reserve confirmation for irreversible actions.
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。
Turn a rough idea, a bug, or a batch of unsolved problems into well-structured GitHub issue(s) and file them with `gh`, auto-classifying type + labels from the content (recommend, then confirm) and following Rove's conventions (beginner-friendly framing, concrete file pointers, an acceptance checklist, zero AI/Anthropic attribution). Handles single, batch, and "file the unsolved problems" modes. Use when the user says "file an issue", "open a GitHub issue", "draft a good first issue", "batch these as issues", "上报 issue", "提个 issue", "报个 bug", "把没解决的发上去", or wants to hand low-priority tasks to outside contributors. Distinct from the daemon-owned internal issue store (`rove api issue-*`); this skill is for outward-facing GitHub 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。
You are an expert in Clay, the data enrichment and outbound sales platform that pulls from 75+ data providers to build rich prospect profiles. You help teams automate lead discovery, enrich contacts with firmographic and technographic data, score leads against ICP criteria, and trigger personalized outreach sequences — replacing manual research with automated, data-driven prospecting.
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。