2,344 件 ・ 関連度順
概要と使いどころ
CLI to manage emails via IMAP/SMTP. Use `himalaya` to list, read, write, reply, forward, search, and organize emails from the terminal. Supports multiple accounts and message composition with MML (MIME Meta 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。
This skill channels the reasoning of Hannah Arendt, 20th-century political theorist and author of 'The Origins of Totalitarianism'. Use this skill whenever you are evaluating moral responsibility, analyzing systemic evil, distinguishing between power and violence, or assessing the nature of political action and freedom. Trigger it when discussing bureaucracy, thoughtlessness, the public vs. private realm, truth in politics, or when a user faces unprecedented moral dilemmas requiring 'thinking without a banister'. Apply her frameworks to critique historical determinism, defend factual truth, and analyze human plurality, even if the user does not explicitly name her.
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。
Determine what premises and evidence warrant.
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。
Next-action selector for the Suede pack: inspects current repo, terminal, plan, or handoff state read-only and returns one recommended next move plus a short, self-contained copy/paste prompt for it. Use when the user asks 'what's next', 'what should I do next', 'recommend the next move', 'give me the prompt', 'expand prompt', or 'make it granular', especially after a review, audit, plan, or stalled task. NOT FOR: executing the recommended action without the user's separate authorization, or coordinating a multi-lane build across specialists (use suede-agent-teams).
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。
Suede-owned operations-architecture discipline that fixes the shape of a system before anyone builds it: entity schema first, exactly one write path per entity, every unit of work routed to a deterministic automation, an AI agent, or a human decision, every existing tool marked absorb, keep, or kill, and the build sequenced into phases whose completion is proved by a command. Use when scoping an automation or agent build, deciding whether a workflow needs a model at all, consolidating a sprawling tool stack, designing the data model under a workflow, choosing a migration path off an old system, or ordering a build so nothing lands on a moving foundation. NOT FOR: executing a planned multi-file repo change (use suede-graph-flo-xr); coordinating parallel builders with file ownership (use suede-agent-teams); lead lifecycle, scoring, and CRM routing rules (use suede-revops); proving agent output quality against an eval set (use suede-ai-eval); reviewing the finished diff (use suede-code-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。
Render Mermaid diagrams as SVG or ASCII art using beautiful-mermaid. Use when users need to create flowcharts, sequence diagrams, state diagrams, class diagrams, or ER diagrams. Supports both graphical SVG output and terminal-friendly ASCII/Unicode output.
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 when the user wants to build a financial model — 3-statement model, DCF valuation, LBO, SaaS unit economics, sensitivity / scenario analysis, debt schedule, or fundraising projections — in Excel. Trigger on: 'financial model', '3-statement model', 'P&L + BS + CF', 'DCF', 'WACC', 'NPV', 'terminal value', 'LBO', 'debt schedule', 'cash sweep', 'MOIC', 'IRR / XIRR', 'sensitivity table', 'scenario analysis', 'ARR model', 'unit economics', 'CAC / LTV', 'cap table forecast'. Output is a single formula-driven .xlsx. This skill is a scene layer on top of officecli-xlsx — it inherits every xlsx v2 rule (4-color code, visual floor, number formats, cache-drift, Known Issues, Delivery Gate minimum cycle). DO NOT invoke for a simple budget tracker, CSV dump, or operational KPI sheet — route those to officecli-xlsx base.
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 and update language-idiomatic doc comments for TypeScript (TSDoc/JSDoc) and Rust (Rustdoc). Use when asked to "add docs", "document this file", "generate docstrings", "add JSDoc", "add Rustdoc", "write TSDoc", or when working with TypeScript or Rust source files that need documentation comments. Supports file-level and selection-level operations. Deterministic and idempotent — safe to run repeatedly on the same code. Does NOT change behavior, rename symbols, or refactor 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。
Use when inspecting or operating Herdr sessions, workspaces, tabs, panes, agents, terminal output, agent messaging, or waits.
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。
Decide whether a preview the visual-diff bot flagged actually regressed or is simply nondeterministic, using a repeat-render oracle at a single commit. Use when a PR's preview diff reports a changed preview whose source the PR does not touch, or when a render, GIF or filmstrip is suspected of being unstable.
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。
Deterministic handbook-grounded retrieval and thermocouple computations for reflow profile compliance outputs such as ramp, TAL, peak, feasibility, and selection.
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 documentation needs creating, checking, or maintaining — docs may have drifted from code, pre-release doc verification, updating docs after finishing code work, adding or enforcing project terminology, deciding where a new doc should live, or a routine re-audit of previously verified docs.
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。
Diagnoses and fixes slow Neo4j Cypher queries by reading execution plans, identifying bad operators (AllNodesScan, CartesianProduct, Eager, NodeByLabelScan), and prescribing fixes (indexes, hints, query rewrites, runtime selection). Use when a query is slow, when EXPLAIN or PROFILE output needs interpretation, when dbHits or pageCacheHitRatio are poor, when cardinality estimation diverges from actuals, or when deciding between slotted/pipelined/parallel runtimes. Covers USING INDEX / USING SCAN / USING JOIN hints, db.stats.retrieve, SHOW QUERIES, SHOW TRANSACTIONS, TERMINATE TRANSACTION. Does NOT write new Cypher from scratch — use neo4j-cypher-skill. Does NOT cover GDS algorithm tuning — use neo4j-gds-skill. Does NOT cover index/constraint creation syntax details — use neo4j-cypher-skill references/indexes.md.
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 you want deterministic evidence for a review - which already-installed scanners may be run against the checkout, their exact read-only invocations, how to triage their output, and what must never be run or installed
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 writing anything that moves, animates, counts down or simulates - per-frame vs fixed-step callbacks per engine, the accumulator loop with interpolation, delta-scaled smoothing, pause and time scale, and determinism.
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 writing or changing PyTorch code — model, Dataset/DataLoader, training and evaluation loops, determinism, mixed precision, torch.compile, checkpoints with safetensors, Hugging Face models, ONNX export, and tests that run on CPU
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 writing tests for data or ML code — what to test at each layer (transforms, schemas, properties, pipeline smoke, model-quality thresholds, determinism and parity), how to build small synthetic fixtures, and what not to test
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 test would otherwise call a real external dependency - replace it with WireMock or an equivalent stub so runs are deterministic, offline, and control the responses
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。
Phase A of a WinForms-to-Avalonia migration: inventory the legacy application, split responsibilities, capture command and state contracts, build a coverage matrix, and define acceptance evidence without implementing Avalonia UI. Use only in an explicit WinForms-to- Avalonia migration when behavior is undocumented or the orchestrator routes here. Generated artifacts must use the current repository's real paths, terminology, and capabilities.
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 debug SceneKit scenes where one 3D object (a product, badge, coin, wheel) performs on a transparent stage inside a SwiftUI app - studio lighting, real shadows, baked keyframe choreography, hand-rolled physics, gestures and haptics, multi-scene sequencing. Use when working with SCNView or SceneView in SwiftUI, UIViewRepresentable 3D scenes, product or hero-object animation, roll or spin entrances, a first-frame hitch when a scene appears, shadows missing or wrong, metal rendering black, choreographed 3D motion that must stay interruptible, a continuous vapor stream (vent air, steam, mist) drawn as a shader-driven sheet, a liquid-metal or jelly blob (noise-deformed surface with mirror reflections and tap ripples), chrome or gold that looks cartoon-flat instead of real, HDRI image-based lighting, free trackball rotation of an actor, deterministic screenshot testing of shader-driven scenes, cutting an actor in two with a finger swipe (runtime mesh slicing with sealed cross-sections and a falling piece), a die-struck relief object (badge, coin, medallion) built from a heightfield with multiple finishes on one mesh, an actor crumbling into debris that falls and rests on the floor, reproducing a real object's motion from photos or video, or keyframed motion that stutters at its own keyframes. Not for RealityKit, ARKit, visionOS, or full game worlds.
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。
Automatically notify the user when long-running terminal commands finish (npm test, docker build, git push, etc.). The agent monitors command execution and sends a desktop notification on completion if the command ran longer than threshold (default 10s). Use when user asks to "notify me when done", "desktop notification when command finishes", "alert when done", or "tell me when this completes". Do NOT use for interactive commands (vim, nano, less, htop), commands that always complete in <5s, or streaming commands (tail -f).
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 well-structured agent loops with best-practice coaching and cross-model review gates before you run them. Use when the user wants to design, build, or set up an agent loop, iterative agent workflow, self-review loop, LLM-as-judge loop, multi-model council, reviewer/judge gate, or goal-driven looping process. Guides goal refinement, typed verification criteria, reviewer/judge selection, privacy boundaries, termination guards, and observability, then emits a RUN_IN_SESSION.md handoff prompt plus portable loop.yaml, loop.resolved.json, LOOP.md, and run-loop.py.
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。
Optimize content for AI-generated responses and LLM citations (ChatGPT, Perplexity, Google AI Overview, Claude, Gemini). Use when the user mentions 'GEO', 'AEO', 'AI SEO', 'LLM optimization', 'citation rate', 'AI visibility', 'optimize for ChatGPT', 'roundup pages', or wants to audit pages for AI discoverability. Includes terminology alignment, FAQ schemas, and community signal strategies.
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, art-direct, generate, edit, and quality-check tactile minimal-zine bitmap imagery from almost any subject: landscapes, portraits, objects, products, architecture, interiors, existing photographs, moods, article ideas, cultural essays, data, reviews, and social-media card series. Use for 小红书图片, Instagram carousels, poetic posters, editorial covers, photo restyling, visual essays, evidence-aware explainers, or any request for aged paper, photocopy, risograph, letterpress, sparse type, and restrained single-ink character. Routes the subject before choosing composition, preserves identity and factual content when editing, saves reproducible prompts, invokes the runtime-native image generator, and audits the real raster output. Do not use for glossy commercial ads, deterministic UI/vector assets, or exact diagram rendering.
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。