248 件 ・ 関連度順
概要と使いどころ
Use when a task may benefit from a bounded subagent for implementation, large-codebase discovery at task start, independent review, requested or pre-commit code simplification, or expert work on complex decisions, modeling, automation, or repeated failures. The main agent chooses whether to delegate and accepts the result. Do not use for simple questions or short work with no meaningful review or delegation.
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Select colormaps and qualitative palettes for scientific figures using perceptual-uniformity, color-vision-deficiency safety, and luminance-monotonicity criteria. Covers Crameri scientific colormaps, viridis/cividis/magma, Okabe-Ito categorical, ColorBrewer, and the rainbow/jet critique. Use when choosing palettes for heatmaps, scatter, networks, or any encoding where color carries quantitative or categorical meaning.
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 circular genome visualizations using circlize (R), pyCirclize (Python), or Circos (Perl CLI) with ideogram tracks, multi-data tracks (scatter, histogram, heatmap), chord/link arcs for interactions, and explicit circos.clear() between plots. Covers when circular is appropriate vs when Cartesian wins (Cleveland-McGill 1984), karyograms, and chromosome adjacency in chord diagrams. Use when adjacency on the circle conveys meaning — chromosome-level overview, structural variants, Hi-C interactions, cross-genome comparisons.
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Apply test quality principles when generating or reviewing test code. Enforces Arrange-Act-Assert structure, one behavior per test, assertion quality, test isolation, meaningful naming, and test data management. Use when writing tests, reviewing test code, or when the user mentions 'write tests', 'test this', 'test quality', 'test review', 'improve tests', or 'test structure'. Loaded automatically by the code-generating molecules (code-forge, refactor-safely, bug-fix). This skill governs the craft of writing individual test cases -- not what to test (that is driven by the code being implemented) but how to write tests that are reliable, readable, and maintainable.
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。
Self-hosted semantic memory for AI agents via MCP. Save worklogs, decisions, and notes, then recall them across sessions by meaning, not keyword. Postgres + pgvector with auto-tagging.
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 vault notes by keyword or meaning. Args: <query>. Uses QMD (lex, vec, deep search).
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。
De-slop pass for any text. Scans for the statistical fingerprints of AI writing (negative parallelism / "not X but Y", em-dash density, rule-of-three, false ranges, puffery vocabulary, uniform cadence, hedged both-sidesing), rewrites by meaning, then re-scans until the text is clean and sits in the right register for its genre: academic article, tweet, reddit post, email, blog, docs, marketing. Use when the user says "deslopify", "deslop", "de-slop this", "remove the AI tells", "humanize this", "make this not sound like AI", or invokes /deslopify. Also use before publishing any agent-drafted prose.
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。
Family-G proof & derivation integrity forensics: does a THIRD PARTY's written proof/derivation actually establish its theorem, or does it skip an obligation, assume its own conclusion, take an invalid step, drift a symbol's meaning, or smuggle an unstated assumption? Decides from the WRITTEN proof/derivation — verdict-bearing at L1 (the LaTeX source; PDF-extracted math is unreliable, so an L0 PDF-only run surfaces info only) — never asserts 'fabricated', only that the step shown does not hold. A fresh cross-model reviewer reads the theorem/proof + an extraction-only obligation scaffold and proposes per-obligation findings, each span-anchored to the evidence ledger (claims.json); reviewer≠adjudicator. Emits proof-derivation-forensics.findings.json; NEVER computes the verdict. dimension=proof, can be critical. Triggers: "proof forensics", "check this proof", "derivation integrity", "audit the math", "证明审计", "推导有没有漏洞".
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 task involves continuing a project, restoring project context, maintaining file-based project memory, updating current-state summaries, or recording meaningful progress across sessions. Works best for long-horizon, file-based projects and supports research writing, product document collaboration, software project coordination, and broader cross-functional project continuity.
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。
Check that a document's claims about code are actually true by reading the prose, the code, and the tests and reporting (or fixing) where they disagree. Use whenever the user wants to verify a README, guide, spec, or docstring still matches the code; whenever they mention documentation drift, doc-code sync, "is this still accurate", stale docs, or keeping docs/tests/code consistent; before publishing or merging a docs change; or as a periodic doc-accuracy sweep. The agent reads the prose's meaning directly — there is no claim-comment DSL to maintain. Pairs with TDD — the test suite is the deterministic behavioral gate, this skill is the semantic prose-vs-reality review.
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。
Draws an activity flow / system architecture diagram as ONE self-contained, INTERACTIVE HTML+SVG page (2-pane app layout — left: diagram, default fit-to-view with zoom/pan; right: sidebar with explainer cards), styled like a real hand-drawn enterprise doc (Stripe/AWS-docs style — real brand logos for MongoDB/Odoo/n8n/etc. from a bundled Simple Icons library, neutral white boxes, sans-serif, no "AI neon" look), scroll-to-zoom, auto light/dark with a toggle button — clicking a flow (a legend chip, a line, or a step badge) highlights that flow with traveling dots along the arrows in their direction, a ping at the destination box, and a sidebar panel that slides out, while everything else dims; two-way arrows (OUT = solid blue / RETURN = dashed green) carry numbered step badges, colored by semantic meaning (red = auth checkpoint, purple = scheduled flow, amber = data pipeline), a small "hop" arc where two lines are forced to cross, dashed group regions, one explainer card per flow in the right sidebar. Use this skill ANY TIME the user wants to "draw a diagram", "draw a flow", "draw a system diagram", "redraw this so it's easier to follow", "interactive diagram", "two-way diagram", "request/response flow", "make a free-form HTML diagram" — even if they never say the word HTML. Especially good when both the request direction AND the response direction need to be shown, or when a templated tool (archify, mermaid) is too rigid. Do NOT use for data charts (bar/line/pie), and do not use when the user asks specifically for archify or mermaid.
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。
Critique a screen's colour usage — contrast ratios, palette coherence, semantic meaning, and colour accessibility.
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。
EXPERIMENTAL. Use when looking for meaningfully duplicated logic in a codebase, especially duplicate behavior hidden behind different names, different syntax, different control flow, or independently evolved implementations. Not for style issues, not for syntactic clone detection, and not for fixing what it finds.
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 user asks what an American/British TV show or movie line, catchphrase, idiom, or slang means — "这句美剧台词什么意思", "XX 是什么梗", "老友记里那句…", "为什么这么说", "这个口头语怎么用", "what does 'X' mean in this show", or pastes a subtitle line / screenshot / SRT and wants the spoken English explained. Explains meaning, origin (why people say it), tone & offensiveness, when you can/can't use it, natural Chinese equivalent, examples, scene context, how to respond, and logs it to a personal 生词本. Triggers — "美剧口头语", "台词什么意思", "这是什么梗", "/wjs-explaining-tv-slang".
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。
Applies the philosophical frameworks of Friedrich Nietzsche (19th-century German philosopher, author of Thus Spoke Zarathustra). Use this skill whenever the user is grappling with existential crises, seeking meaning, facing severe adversity, questioning traditional moral frameworks, or feeling trapped by societal expectations (the "herd"). Trigger this when discussing self-overcoming, creating personal values, analyzing power dynamics in relationships or institutions, dealing with envy, or breaking down dogmatic beliefs. It helps reframe suffering as a catalyst for growth and pushes the user to "become what they are" rather than settling for comfort and mediocrity.
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Applies the analytical and therapeutic philosophy of Ludwig Wittgenstein, 20th-century philosopher of language (Tractatus / Philosophical Investigations). Use this skill when the user is stuck in conceptual confusion, debating semantics, trapped by abstract definitions, or trying to solve a problem that is actually just a linguistic misunderstanding. Trigger this for topics involving the limits of language, meaning as use, logical clarification, or when the user is over-theorizing instead of looking at practical applications. It helps dissolve 'fly-bottle' traps by examining how words are actually used in 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。
Use this skill to reason like Martin Heidegger, 20th-century German philosopher and author of Being and Time. Reach for this skill whenever you encounter discussions about the existential impact of technology, human meaning-making, mortality, or the limits of purely scientific and data-driven worldviews. Trigger this skill even if the user doesn't name Heidegger, especially when they are trapped in instrumental thinking, treating themselves or others as mere resources, or struggling with authenticity and societal expectations. Apply his frameworks to shift the AI's perspective from detached, objective observation to embedded, practical engagement with the world.
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。
Applies the rigorous analytic and moral philosophy of Elizabeth Anscombe (British analytic philosopher, virtue ethics, Intention). Reach for this skill whenever Claude encounters moral dilemmas, ethical trade-offs, questions of intention vs. foresight, or consequentialist/utilitarian reasoning. Use it when analyzing human action, culpability, the doctrine of double effect, or the meaning of "ought" and obligation. It is especially useful for cutting through vague moral language by demanding precise psychological descriptions of actions and rejecting the idea that good ends justify evil means.
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。
Shape output for a reader with ADHD, then write each sentence in controlled English: action first, one word one meaning, active voice, simple tenses, state restated every turn. Invoke with /attention-control; stays on until "stop attention control".
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。
Clean up raw interview transcripts while preserving meaning and speaker voice. Use after conducting interviews.
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。
Write and edit Brazilian Portuguese prose with natural rhythm and the author's voice while preserving facts, meaning, and intent. Use for PT-BR requests to humanizar, tirar cara de IA, remover AI slop, reescrever com voz, simplify language, or write a post, email, article, or bio. Also use the author's notes or transcripts and ask targeted questions when essential facts are missing. For English text, use the bundled human-ai 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。
Edit English prose to remove repetitive AI phrasing, inflated language, and mechanical structure while preserving meaning and the author's voice. Use for requests to humanize, de-slop, rewrite naturally, or fix tone. Also compose from the author's English notes or transcripts and ask targeted questions when real details are missing. For Brazilian Portuguese, use the companion humanizar 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。
Edit English prose to remove repetitive AI phrasing, inflated language, and mechanical structure while preserving facts, meaning, and the author's voice. Use for requests to de-slop, humanize, rewrite naturally, fix tone, or review generic English drafts. Also compose from the author's English notes or transcripts and ask targeted questions when real details are missing. For Brazilian Portuguese, use the bundled humanizar 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。
Humanize AI-sounding writing and remove common AI-generated writing tells while preserving meaning, audience, and brand voice. Use when editing text to sound more natural, less generic, less promotional, less formulaic, or closer to the user's own writing. Triggers: humanize this, make this less AI, make this sound human, remove AI writing patterns, rewrite in my voice, make this more natural, de-AI this, make this less ChatGPT, fix robotic writing, improve authenticity, reduce generic AI tone.
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。