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Evaluates water rights valuation with seniority analysis, regulatory framework assessment, and allocation risk for resource investments. Use when analyzing water rights, evaluating water allocation, or assessing water risk.

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。

Measures implementation shortfall with paper portfolio comparison, delay cost attribution, and execution quality assessment. Use when measuring implementation shortfall, analyzing execution quality, or attributing trading 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。

Render a dashboard of the current Claude Code session — message counts, token usage, cache read/write, dollar cost, context %, lines changed, cost-per-turn sparkline, and a tool-call histogram — parsed from the session transcript JSONL by a bundled bash script. One bash call, zero analysis, zero confirmation. Optionally pass a session id to inspect a different session. Use when the user asks for session stats, usage, token or cost breakdown, or a session dashboard.

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。

Post-implementation QA planning — independent of /review (the developer chooses whether to run them sequentially or in parallel), only when the change has a running surface worth driving. Interviews the developer to turn the specs and the diff into an executable QA specification (specs/qa/QA-<N>-<slug>.md) that /execute-qa runs. The agent drives browser and shell; the human steps in only at named handoff points. Use only when the user asks to plan manual QA — never trigger automatically.

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 Docker build times using layer caching, multi-stage builds, BuildKit features, and dependency-first copy patterns. Applicable to R, Node.js, and Python projects. Use when Docker builds are slow due to repeated package installations, when rebuilds reinstall all dependencies on every code change, when image sizes are unnecessarily large, or when CI/CD pipeline builds are a bottleneck.

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 a generative recipe DSL so agents emit small validated JSON documents and ONE audited interpreter renders them all — data, not code. Covers the N-artifacts threshold for choosing a DSL over bespoke code, designing roles as style slots so a single recipe renders unchanged in every output style, the validator gate (compile + bounds + real render in all styles, plus a --fast mode for corpus-wide sweeps), hand-authored seed recipes, and the emergent conventions that keep a corpus of hundreds consistent without per-item steering. Use when many similar artifacts (icons, status badges, diagram nodes, test fixtures) must be generated by agents, when per-item bespoke code is multiplying unreviewable code paths, or when a whole corpus must be re-rendered cheaply into new styles.

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。

Alluvial gold recovery using panning, sluicing, and classification. Covers site reading (geological indicators, stream dynamics, pay streak location), panning technique, sluice box operation, and responsible extraction practices. Use when prospecting in an area with known or suspected alluvial gold deposits, sampling a stream to test for gold presence, maximizing recovery during recreational panning, or assessing a site's gold potential before investing more effort.

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。

Add an external probabilistic classifier to a decision path without letting it take the path over. Covers finding the externally-graded rows you are already logging, measuring the confidence separation between the overrides it got right and the ones it got wrong, choosing an operating point your data licenses, failing open at the call site, and proving the whole arrangement offline with no API key. Applies to any service returning a score you can order — TypeSafe AI's System One models (Jev) are the worked example. Most of the method transfers to a local model or a second heuristic, with the parts that do not called out where they arise. Use when a rule-based path is wrong often enough to hurt, when someone proposes replacing a heuristic with a model, when a confidence threshold needs a defensible value, or when an oracle already in production has never been graded.

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。

Concurrent investigation of independent failures. Use when multiple unrelated issues need parallel resolution.

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。

Parallel map-reduce bulk ingest for large source sets. Map phase dispatches read-only knowledge-extractor agents (≤N-wide, default Haiku) emitting per-source JSON extracts; Python routes extracts by target library file (fuzzy-merging new topics, pre-allocating new files, flagging oversized topics); reduce phase dispatches one agent-knowledge-updater per file (parallel, one writer per file); single shelf-index rebuild + one log.md entry. Resumable. Supersedes kb-ingest-batch.

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。

Send, read, and respond to Telegram messages as Claudicle via the @claudicle_bot Bot API. Use this skill when sending Telegram messages (text, Markdown, inline keyboards), building approval gates with tappable buttons, checking the shared inbox for unhandled Telegram messages, answering callback queries, managing Telegram memory context, or checking bot and listener status. Five purpose-built scripts (send, check, status, callback, memory) wrap the python-telegram-bot v22 polling adapter at ~/.claudicle/adapters/telegram/ with REST-based senders (no asyncio). Pairs with /telegram-respond for the cognitive pipeline and with mazkir-callback-watcher.py for the Mazkir approval gate.

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 UI component patterns across the component.gallery corpus — 60 canonical component types, ~95 production design systems, 2,600+ examples — plus an AI-era overlay (prompt inputs, tool-call cards, streaming status, citations) and composite patterns (command palette, app shell, agent console). Compare implementations, find alternative component names, ground frontend decisions in real-world precedent. Pairs with minoan-frontend-design for research-then-build workflows. Triggers on component patterns, how do others implement X, design system research, component comparison, AI chat components, agent UI patterns.

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。

Spaced repetition and retrieval practice engine for the vault. Use when the user wants a review session, recall practice, to test what they remember, or to resurface notes. Triggers on "review session", "what should I review", "recall practice", "resurface notes", "spaced repetition", "quiz me", "what do I know about", "inbox triage", "surprise connection".

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。

Flask web framework conventions: app factory pattern with create_app(), Blueprint registration with url_prefix, MethodView for class-based API views, Marshmallow schema validation, WTForms for HTML forms, Flask-Login for session auth, flask-jwt-extended for stateless API auth, Jinja2 template conventions, error handlers, and extension initialization. Activated automatically by flask-plugin/stack.md. Use this skill to: - Structure Flask applications with the app factory and per-feature Blueprints. - Validate JSON request data with Marshmallow and HTML forms with WTForms. - Implement session-based auth with Flask-Login or token auth with flask-jwt-extended. - Render Jinja2 templates safely or return JSON responses for API mode. - Register global error handlers for consistent error responses. Do NOT use this skill for: - SQLAlchemy ORM model patterns and Flask-Migrate — see flask-plugin:sqlalchemy-patterns. - Python language idioms — see python-foundation:python-conventions. - Testing patterns — see python-foundation:pytest-testing.

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.js App Router routing primitives: file-based routes, dynamic and catch-all segments, route groups, parallel routes, intercepting routes, middleware, programmatic navigation, link patterns. Use this skill to: - Pick the correct dynamic segment syntax for the route shape. - Use route groups to organize without affecting URLs. - Implement parallel/intercepting routes for modal-style navigation. - Build effective middleware for auth, redirects, A/B tests. - Use Link and useRouter correctly. Do NOT use this skill for: - Data fetching per route (see nextjs-data-fetching). - General file conventions (see nextjs-conventions). - RSC vs Client (see server-component-patterns).

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 a deterministic 15-second vertical promo video from real Simulator screenshots with a three-beat viewer challenge and no Remotion initialization. Use in a twelve-minute parallel launch lane, as a reliable fallback to a richer Claude Design animation, or whenever ffmpeg and ImageMagick are available.

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 tracking heap allocations on Linux with heaptrack: allocation hotspots, peak heap, temporary allocations, leaks, or a diff of two runs via heaptrack_print. Not for heap errors: use valgrind.

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 all packages, reinstall VS Code extension, commit and push. Use when: user says "ship", or wants to build+install+commit+push in one go.

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。

Use when running the full team/breezing flow end-to-end — all tasks with parallel workers. Do NOT load for: single-task implementation, planning, review, release, or setup.

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 generating, vectorizing, or converting images to SVG — logos, icons, illustrations, or 'allow1'/'quiver' 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。

Use for ANY bug bounty, penetration test, or web/API/mobile security assessment: recon, testing endpoints, analyzing Burp traffic or any bug-bounty platform's MCP (HackerOne, Intigriti, Bugcrowd, YesWeHack, Immunefi), reviewing APKs, bypassing a WAF, enforcing scope, hunting a specific vuln class, validating findings, writing reports, or when you are stuck on a target and about to give up. Activates automatically for all bug-bounty and pentest sessions. Runs an autonomous, never-surrender predator methodology: refuses to conclude "secure", exhausts each vuln class to depth, proves a real attacker-path with impact and no false positives, tracks coverage so nothing is re-tested or skipped, diagnoses failed tooling from full logs, and hunts at maximum effort with intelligent token use until the goal is found. Activates and follows instructions in ANY language the operator writes in (the skill itself is English). Bundles a per-class web-exploitation KB, a writeup library, and PayloadsAllTheThings.

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。

Install and verify every developer tool NowStack Mobile needs on this machine (Node, eas, vercel, convex, asc, gpc, fastlane, bun, gcloud, + Xcode/Android Studio). Cross-platform — Homebrew/npm on macOS, apt/curl on Linux, winget/scoop on Windows. Use for "install the CLIs", "set up my machine", "ns doctor", missing-tool errors, or right before /ns accounts. Proposes to install everything missing in one pass.

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。

First-run conversational setup wizard for marketing-cli. Use when /cmo detects no populated brand files and no cmo-preferences.md, when the user just installed marketing-cli for the first time, or when they say things like "set up marketing", "start marketing", "marketing wizard", "I just installed marketing-cli", "onboard me", "first time", "initial setup". Asks 3 sharp questions (identity, posture, distribution preferences), records the answers to brand/cmo-preferences.md, then hands off to /cmo's foundation flow which spawns 3 research agents in parallel. The user never has to type /mktg-setup directly — /cmo auto-routes here on first run.

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。