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概要と使いどころ
Coordinated botnet takedown methodologies — sinkholing, infrastructure mapping, legal frameworks, BGP intervention, and post-disruption analysis. Studies Operation Endgame, Badbox 2.0, and emerging blockchain C2 countermeasures. Defensive disruption for authorized law enforcement, CERT, and academic research contexts.
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Bridge active inference theory with robot control using K-Scale's JAX/MuJoCo stack. Use when connecting predictive coding to locomotion policies, mapping KL divergence minimization to RL training, applying mean field approximation to robotics state estimation, or implementing sim2real as inference about future observations.
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。
Unified ASI skill combining ACSets, Gay-MCP colors, bisimulation games, world-hopping, glass-bead synthesis, and triad interleaving for autonomous skill dispersal.
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Build an interactive account org chart, leadership map, buying committee, or manager/report neighborhood around a person. Use for decision makers, reporting-line candidates, stakeholder mapping, and warm intro paths. Skip standalone email lookup and unrelated cross-company prospecting.
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Create original pixel-art "Clawd" crab emotes as pure SVG + CSS keyframe animations (no frame-by-frame GIFs, no raster sprites), and optionally export them to looping GIFs. Each emote is a tiny pixel crab doing an activity — holding a prop, wearing a hat, reacting — built from <rect>/<polygon>/<circle> and animated with @keyframes. Use this skill whenever the user wants to make, add, fix, or extend Clawd / pixel-crab / desk-pet emotes, mascot animations, "表情/图鉴" cards of an animated character, festival or daily-life crab stickers, or asks to turn such SVG animations into GIFs — even if they don't say the word "SVG". Also use it when fixing visual bugs in these emotes ("帽子悬空/hat floating", "脚断开/feet detached", a prop that looks disconnected from the hand), since the fixes follow specific structural rules documented here.
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。
Convert a Clay table configuration into local Deepline scripts. Handles extraction (MCP or script), documentation, action mapping, script generation, and parity validation against Clay ground truth.
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 navigate DSP (Data Structure Protocol) — graph-based long-term structural memory of codebases for LLM agents. Stores entities (modules, functions), their dependencies (imports), public API (shared/exports), and reasons for every connection. Use when: (1) project has a .dsp/ directory, (2) user asks to set up DSP or bootstrap project structure, (3) creating/modifying/deleting code files in a DSP-tracked project, (4) navigating project structure, understanding dependencies, or finding modules, (5) user mentions DSP, dsp-cli, .dsp, or structure 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。
End-of-session closure for a research or code repository. Records what changed into the project's own handoff and log files, separating verified work from work merely attempted, and reports what is left uncommitted. Use when wrapping up a session so the next one can resume without re-deriving state. Its start-of-session twin is sitrep.
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。
Runs several language models as independent coders on the same labeling or discovery task and reads their disagreement as data — panel assembly for model diversity, keeping votes independent, consensus rules, agreement statistics (Cohen's and Fleiss kappa, Krippendorff's alpha), the correlated-errors caveat that stops agreement being mistaken for validity, human validation beyond the panel, and reporting. Use when the user asks about a council, panel, ensemble, or jury of models, asks how to combine several models' labels, or asks what kappa or alpha to report for model coders. Single-model codebook and validation work goes to text-classification, per-item confidence to llm-calibration-logprobs.
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。
Ensemble SOLID review — fans the ruleset across overlapping focused workers over the same code, then reduces by corroboration.
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 primary outcome is refining an existing AI-facing artifact without dropping behavior, including SKILL.md, AGENTS.md, CLAUDE.md, rules, prompts, and agent definitions that need sharper invocation, structure, or completion criteria.
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 and teaches Python 3.11+ modernization patterns with PEP citations. Use when reviewing or writing Python code to apply built-in generics (PEP 585), pipe unions (PEP 604), walrus operator (PEP 572), match-case (PEP 634), Self type (PEP 673), exception notes (PEP 678), StrEnum, tomllib, pytest-mock fixtures, Typer Annotated syntax, or Rich terminal output — or when refactoring legacy typing imports or elif chains to modern equivalents.
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 building or debugging Typer/Rich CLI applications. Activates on Rich table rendering, console output in non-TTY environments, CliRunner testing with Rich output, snapshot testing, Typer command wiring, exception chain prevention with AppExit/AppExitRich patterns, table width at 80-column wrapping, Progress/Live in non-interactive contexts, stderr/stdout separation, or force_terminal vs width configuration. Grounds AI-generated CLI code in verified correctness patterns and prevents known Typer/Rich integration mistakes.
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 asyncio Python code — async/await coroutines, concurrent I/O with asyncio.gather, task creation and cancellation, semaphore rate limiting, producer-consumer queues, async context managers, async generators, WebSocket servers, aiohttp web scraping, async database operations, run_in_executor for blocking calls, or testing async code with pytest-asyncio. Covers FastAPI and aiohttp patterns, synchronization primitives, timeout handling, and common pitfalls like event loop blocking and missing await.
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。
Activates on any Python task involving *.py files, uv, ruff, ty, pytest, or pyproject.toml — loads the shared Python 3.11+ standards and routes the task to the specialist skill that applies them: TDD, CLI, web, data, async, typing, packaging, publishing, documentation sites, test design, test-failure analysis, or stdlib-only constrained environments.
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。
Synthesize multiple independent structured review verdicts into one lossless deduplicated punch list. Use when findings from several review perspectives must be merged without inventing, dropping, or changing source verdicts.
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 starting, stopping, or checking the dot-dash live session dashboard — a real-time browser UI that monitors all active Claude Code sessions, streams transcripts, and supports prompt injection
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Same reverse-thinking method as dh:rt-ica (see dh:rt-ica or dh-glossary for the definition), but localizes any MISSING input to the affected task only, as a non-blocking information-completeness pre-pass before task decomposition and plan generation. Use when grooming backlog items, generating plans, decomposing tasks under uncertainty, or working in brownfield and refactor scenarios. Produces completeness summary (APPROVED-FOR-PLANNING, APPROVED-WITH-GAPS, or BLOCKED-FOR-PLANNING), missing input report with dependency mapping, required unblock actions, and planning annotations for downstream tasks. Use dh:rt-ica instead at the S2 implementation gate where missing inputs must halt execution.
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。
Reviews Python boundaries, typing, error handling, tests, dependencies, and supported-version idioms against the target project's contracts and active tools. Loaded by dh:code-reviewer for Python source; uses Python-engineering standards when available and retains standalone checks otherwise.
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Dasel v3 selectors for Spring bean factory XML — use when querying any Spring ApplicationContext XML for bean discovery, dependency wiring, JMS destination mapping, property injection extraction, or cross-bean reference tracing. Load this skill before writing dasel selectors against Spring bean XML files (applicationContext.xml, *_beans.xml, spring-*.xml).
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 PLAN artifact from SAM Stage 2 needs contextualization against actual codebase state — grounds the design plan in reality by performing scope analysis (NEW/MODIFY/COMPLETE classification), conflict detection between plan assumptions and codebase patterns, and resource mapping to concrete file paths and integration points. Produces an updated ARTIFACT:PLAN registered via MCP with a Contextualization section appended.
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Creates a GitHub milestone on the current repository and returns its number for downstream use. Use when starting a new sprint, release, or theme grouping of backlog items. No args triggers guided intake (title, due date, description); 'quick {title}' skips to description only. Checks for duplicates before creating. Returns milestone number for /group-items-to-milestone.
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。
Integrates patterns from external sources (URLs or local files) into local skills, agents, and plugins. Use when comparing external agent definitions against local equivalents, extracting best practices from frameworks like GSD or BMAD-METHOD, enhancing local skills with external workflow patterns, or adding interoperability with external tool ecosystems. Runs a 3-phase workflow — parallel candidate mapping, contextual enhancement, and validation — with source attribution and backlog tracking for deferred enhancements.
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。
Runs a multi-model orchestration workflow led by the session's Fable or Claude Opus model. Sends menial tool-calling work to Haiku subagents, judgment work to Opus subagents at an effort matched to each task, and high-stakes or fresh-perspective questions to a GPT-6 Astra Codex peer. Detects the lead from session context; `--lead fable` or `--lead opus` overrides. Use to orchestrate, delegate, fan out, get a decorrelated Codex opinion, run a blind Opus-Codex cross-check, or act as tech lead.
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。