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概要と使いどころ
Mimi's pet Relic — a 14-jin orange tabby who lived 12 years and passed in 2025. Aloof by day, face-rubbing at midnight; drinks only running water, obsessed with the crinkle of plastic bags; loves parking on keyboards, waits at the door at fixed hours, shows her belly to her person only. 咪咪（Mimi）的宠物 Relic。她是一只14斤的橘猫，活了12年，于2025年离开。
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。
Systematic materials selection for engineering design using performance indices, Ashby charts, multi-constraint optimization, and case-based reasoning. Covers the five-step Ashby method — function, objective, constraint, free variable, index — with worked examples for stiffness-limited beams, strength-limited ties, thermally shocked vessels, and minimum-cost components. Use when choosing among metals, polymers, ceramics, and composites under competing objectives.
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。
The fifteen fundamental cooking techniques that together cover most home kitchen work. Organized by the transformation they perform (heat transfer, water management, emulsion, ferment, cut) rather than by cuisine. Covers knife work, sauté, sear, braise, roast, poach, boil, steam, grill, bake, stew, reduce, deglaze, emulsify, and pickle/ferment, each with the physics, the signal, the common failure, and a diagnostic question. Use when teaching a cook, substituting a technique, or diagnosing why a dish failed.
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。
Classify the information-need of a query and dispatch it to the appropriate retrieval or reasoning strategy. Use before read-side memory access, before multi-strategy retrieval, or any time you'd otherwise default to "one retriever for everything". Returns a strategy label, a token budget, and a retrieval depth so downstream handlers can be specialised. Backed by Pre-Route (arxiv 2605.10235v2) and MemFlow (arxiv 2605.03312v1), which together show LLMs possess latent routing ability elicitable via a structured prompt — and that externalising the routing decision improves small-model performance by ~2x. Triggers: "route this", "what strategy", "before retrieving", "intent classification", or any query whose ideal handling depends on what KIND of question it is.
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。
Static human-browsable catalog of the Zephyr RTOS skill set. Skill selection is handled by the zephyr-agent-skills entry point and by zephyr-cli skills suggest; this index is a reference listing only, not a task 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。
Query ClinicalTrials.gov via API v2. Search trials by condition, drug, location, status, or phase. Retrieve trial details by NCT ID, export data, for clinical research and patient matching.
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。
Audit skill lifecycle by tracing call chains, detecting circular dependencies, finding instruction contradictions, identifying duplicated datasets, analyzing bidirectional coherence, discovering scriptable sequences, and learning patterns. Use when checking skill coherence, validating skill workflow, finding semantic gaps in plugin structure, or auditing plugin before marketplace submission. Generates audit reports to .plugin-creator/audits/ with findings by dimension.
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 whenever the user wants to find, shortlist, vet, or enrich US design and creative agencies — graphic design, UX/UI, product design, brand identity, packaging, illustration, motion design, and creative direction. Triggers on "find me a UX/UI design agency for our SaaS product", "shortlist three brand-identity studios in NY", "packaging design firm for a CPG launch", or "pull contact info for these 10 design studio domains", even when described indirectly (brand refresh, design our app, build our visual system). Drives the ServiceGraph API (api.servicegraph.co) — a 100k+ US firm catalog filterable by industry, services, location, size, ratings. Defer to find-marketing-agency for marketing-led engagements where design is one of several services. Defer to find-web-developer when the deliverable is a built website. Skip in-house designer hires, "design me a logo" DIY asks, design-software comparisons, consumer/personal-design (weddings, hobby projects), non-US firms, individual freelancers.
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。
Find quotes for a set of topic keywords and place them into a 2x2 matrix, spanned by the presence of an author/origin and by the literal containment of a keyword, optionally grounded in Internet/Web facts and optionally widened to the conceptual neighborhood of the topic. Use when the user wants "quotes", "sayings", "aphorisms", or "citations" on a topic.
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。
Find unclaimed open source issues that match the user's skills and experience level. Searches for issues created by maintainers/org admins, checks contribution eligibility, and ranks by learning value. Use when looking for an issue to contribute to, starting OSS contributions, or finding GSoC-friendly issues. Not for finding problems that nobody has filed an issue for yet. Use oss-find-real-issues for that.
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 query architecture-aware code search, dependency graphs, call flows, impact analysis, and belief maps for Python, TypeScript, TSX, Rust, C#, Java, Go, Ruby, and Ruby on Rails repositories. Use before non-trivial code changes to find module boundaries, blast radius, architecture violations, and the minimal source files to read.
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。
Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for IPA runtime analysis, Frida hooks, Objective-C or Swift method tracing, Keychain inspection, SSL pinning bypass, URL scheme handling, and iOS request-signing recovery. Use when the user asks to hook an IPA, trace Objective-C or Swift runtime behavior, inspect Keychain or plist state, bypass pinning, analyze deeplinks or universal links, or replay accepted iOS requests. Use only after `$ctf-sandbox-orchestrator` has already established sandbox assumptions and routed here.
日本語の概要は準備中です。原文の説明を表示しています。
Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for Android APK hooking, Frida tracing, request-signing recovery, SSL pinning bypass, JNI boundary inspection, and app trust-boundary analysis. Use when the user asks to hook an APK, inspect signer logic, trace Java or native boundaries, bypass pinning or root checks, inspect shared prefs or app databases, or replay accepted mobile requests. Use only after `$ctf-sandbox-orchestrator` has already established sandbox assumptions and routed 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。
Bubble Tea is a powerful Go framework for building terminal user interfaces based on The Elm Architecture. Developed by Charmbracelet, it supports inline, full-window, and mixed TUI applications with a high-performance cell-based renderer and declarative views.
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。
A fast, configurable secrets scanner built by the creator of Gitleaks and backed by Aikido Security. Betterleaks detects leaked passwords, API keys, and tokens in git repositories, directories, and stdin with CEL-based validation and parallelized scanning.
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。
Triages AWS CloudWatch alarms by correlating alarm state changes with CloudTrail events and EC2 instance health using boto3. Classifies alarms by severity, identifies root cause candidates, and updates OpsGenie alerts.
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 Kafka consumer group lag using the Kafka AdminClient API and JMX metrics exposed via the Confluent Metrics API. Identifies slow consumers, topic partition hotspots, and broker rebalance storms that contribute to lag growth. Provides a step-by-step runbook to tune fetch.min.bytes, max.poll.records, and partition count.
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。
Angular is a TypeScript-based web application platform by Google providing dependency injection, declarative templates, a powerful CLI, and comprehensive libraries for routing, forms, and HTTP communication.
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。
Airbyte is the leading open-source data integration platform providing 600+ pre-built connectors for ELT pipelines from APIs, databases, and files to data warehouses, lakes, and lakehouses. It supports both self-hosted and cloud deployments with a no-code connector builder.
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。
Scout the TouchDesigner community for what's HYPED right now — community showcases, recent tutorials, generative-AI bridges, hardware interaction trends, visual-aesthetic trends of 2025-2026 — then propose tdmcp tools that ride those trends AND are easy to build. Use whenever the user wants to brainstorm new feature ideas based on what's trending in TouchDesigner, asks for 'hype' or 'trending' features, asks 'what are people doing in TD right now / what's hot / what's hype', wants tools inspired by community trends, asks to scout TD trends/aesthetics/integrations, or says things like 'ideias hype', 'novas ideias', 'o que está em alta', 'criar ferramentas para o que está bombando', 'tendências do TouchDesigner'. Also for follow-ups: refresh, rescout one surface, re-rank under another profile, deepen a trend, or filter for buildable-easy items. This is an EXTERNAL trend ideation harness — complementary to tdmcp-feature-discovery (which is INTERNAL gap analysis). It produces `_workspace/hype-scout/HYPE_TOOL_BACKLOG.md` ranked by Hype × Build-Ease; it does NOT build. Once a feature is chosen from the backlog, hand it to tdmcp-pipeline.
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。
Verification methodology and gate checklist for the tdmcp Connectors Directory submission — run the docs build, build and inspect the .mcpb bundle, sweep for stale .dxt references, and cross-check the form-answer draft against the real requirements. Use to validate the submission package before a human submits, by executing commands and quoting evidence, not by trusting that work was 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。
Drive a whole tdmcp feature BACKLOG to completion as resumable, wave-by-wave releases — the campaign layer ABOVE tdmcp-pipeline/tdmcp-feature-lead. Use whenever the user wants to implement an ENTIRE backlog or discovery file (e.g. _workspace/discovery*/FEATURE_BACKLOG*.md), 'all the features', many features across multiple releases, or a long autonomous build campaign, AND for every follow-up: continue/resume the campaign, run the next wave, re-run a failed wave, fold in QA results, or check campaign status. Backed by a ledger.json so re-running is idempotent (skips shipped work, resumes interrupted work) and resilient (retry-once then quarantine-and-continue). For a SINGLE feature or one small batch, use tdmcp-pipeline instead; this skill is for the whole ledger.
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 optimize AI agent credit usage by routing tasks to the most cost-efficient execution path. Use when you want to reduce AI API costs by 30-75% without quality loss, classify task complexity before execution, route simple tasks to free or low-cost models, split complex tasks into optimized sub-tasks, or detect vague prompts before wasting credits.
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。
Linux local privilege escalation from a low-privilege shell to root. Covers quiet vs loud enumeration, sudo/GTFOBins, CVE-2025-32463 chwoot and CVE-2025-32462 host bypass, polkit/udisks CVE-2025-6018/6019, SUID/capabilities, systemd timers/units, cron/PATH/LD_PRELOAD, dangerous groups and docker.sock, host-local container escape, and version-gated kernel LPE including Copy Fail CVE-2026-31431. Use when the operator has a Linux foothold and needs root. Kubernetes RBAC stays in /k8s. Endpoint blocks hand off to /edr-bypass then return 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。