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Benchmark franchise locations by comparing top and bottom quartile performance across revenue, profitability, and operational scores.

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。

Analyze flow metrics to identify delivery bottlenecks and improve throughput. Use when the user says "flow metrics", "why is delivery slow", "cycle time analysis", "WIP analysis", "throughput review", "what's our lead time", "DORA metrics", "where is work getting stuck", "Kanban metrics", or wants to diagnose delivery performance using data - even if they don't explicitly say "flow metrics review". Based on "Making Work Visible" by Dominica DeGrandis (WIP limits, flow blockers, time thieves) and "Accelerate" by Forsgren, Humble & Kim (DORA metrics, delivery performance indicators).

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。

Surface and visualize hidden dependencies blocking delivery. Use when the user says "map our dependencies", "what's blocking what", "dependency audit", "why are teams blocked", "we have a bottleneck", "draw out the dependencies", or asks to identify cross-team blockers - even if they don't explicitly say "dependency mapping". Based on "Making Work Visible" by Dominica DeGrandis (time theft, invisible work, flow blockers).

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 investigating, adding, validating, or debugging external website profiles for the 99idea Playwright browser demo. It teaches how to probe selectors, classify failure modes, add config-driven profiles, and validate both heuristic and Gemini flows.

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 competitive SEO content briefs with per-section word counts, competitor scoring, keyword density guidance, and page-type templates. Supports both new page briefs and improve-existing-page briefs. Use when user says "content brief", "write a brief", "content outline", "blog brief", "service page brief", "brief for", "writing brief", "content plan", or "outline for".

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 and fix agent readiness: the Lighthouse Agentic Browsing fraction, accessibility tree for agents, robots.txt and Content-Signal for AI agents, WAF treatment of agent traffic, llms.txt, Markdown delivery, ai-catalog.json, /.well-known discovery files, and WebMCP tools. Exclude AI citability and brand signals (seo-geo) and commerce protocol depth (seo-ecommerce).

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。

Establish durable brand and voice context for cross-skill consumption. Generates BRAND.md (audience, positioning, do/don't editorial rules, taboo phrases, competitor differentiation) and VOICE.md (existing persona JSON re-expressed as readable prose), both written to the project root. When present, the blog orchestrator loads these files, fenced as untrusted data, for write, rewrite, brief, outline, calendar, and strategy workflows. Pairs with blog-persona, which manages the structured persona JSON. Use when the user says "blog brand", "create brand context", "BRAND.md", "VOICE.md", "establish editorial brand". Not for learning a voice from existing posts (blog-style) or managing persona JSON (blog-persona).

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。

Manage Google Security Operations (SecOps) SOAR cases throughout their lifecycle. Use when listing, creating, inspecting, updating, or closing SOAR cases; adding investigative comments and notes; updating case priority or description; or linking and grouping security alerts within cases. Supports both remote Google SecOps MCP tools and local fallback tools. Don't use for SIEM UDM searches or detection rule authoring.

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。

Plans, executes, and validates Google Kubernetes Engine (GKE) cluster upgrades and maintenance operations for both Standard and Autopilot clusters. Produces upgrade plans, pre/post-upgrade checklists, maintenance runbooks with gcloud commands, release channel strategy, and troubleshooting guides. Handles node pool upgrade strategies (surge, blue-green), version compatibility, PDB management, and workload-specific concerns (stateful, GPU, operators). Use this skill whenever the user mentions GKE upgrades, Kubernetes version bumps, node pool maintenance, GKE patching, cluster version management, release channel selection, maintenance windows, surge upgrades, stuck upgrades, or any GKE lifecycle management task — even casual mentions like "we need to upgrade our clusters" or "plan our next GKE maintenance" or "our upgrade is stuck." Don't use for GKE cluster creation, application onboarding, general networking/routing setup, or security policy configurations (use gke-basics or relevant GKE skills instead).

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。

Wire the current repository through the Caveman Cloud gateway so every LLM request is measured — cost, tokens, latency — with zero behavior change. Use when the user pastes the Caveman setup prompt, says "set up caveman", or wants LLM spend observability added to an app. Requires the gateway URL and a Cave API key (the setup prompt carries both).

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 any time a .pptx or .potx file is involved in any way — as input, output, or both. This includes: creating slide decks, pitch decks, or presentations; reading, parsing, or extracting text from any .pptx or .potx file (even if the extracted content will be used elsewhere, like in an email or summary); editing, modifying, or updating existing presentations; combining or splitting slide files; working with templates (.potx), layouts, speaker notes, or comments. Trigger whenever the user mentions "deck," "slides," "presentation," or references a .pptx or .potx filename, regardless of what they plan to do with the content afterward. If a .pptx or .potx file needs to be opened, created, or touched, use this 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。

Provides data-retrieval best practices, tool selection guidance, and performant SQL query syntax for BigQuery telemetry across INFORMATION_SCHEMA, Cloud Monitoring, and the REST API. Use when the telemetry to fetch is already known, selecting telemetry tools, writing performant INFORMATION_SCHEMA queries, retrieving telemetry for diagnosing single-job performance bottlenecks, investigating slot contention, job concurrency and queue latency, analyzing reservation capacity, utilization and autoscaling saturation, or auditing capacity-based and on-demand compute and storage resource billable usage. Don't use for root-cause diagnosis or symptom troubleshooting when the cause is unknown (use bigquery-troubleshooting first), or for writing or optimizing business logic SQL (use bigquery-optimization).

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。

Analyzes Google Cloud BigQuery slot consumption, query costs, and execution bottlenecks using INFORMATION_SCHEMA. Use when diagnosing slow BigQuery queries, slot starvation, high on-demand query costs, unpartitioned table scans, or join performance issues. Don't use for generic BigQuery administration (use bigquery-basics), BigQuery ML (use bigquery-ai-ml), or DataFrame operations (use bigquery-bigframes).

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。

Migrating Classic Knowledge (KnowledgeArticleVersion / Article Types) to Lightning Knowledge (Knowledge__kav with record types): article-type-to-record-type mapping, multi-language translation preservation, data category re-architecture, file attachment porting, version and publication-state retention, channel visibility translation, and downstream Case Feed / Community / Bot rewiring. NOT for new Lightning Knowledge setup or editorial publishing workflow design (use admin/knowledge-base-administration).

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。

Tune moflo's memory stack for speed, RAM, and index quality. Covers HNSW parameters (M, efConstruction, ef), vector quantization, batch operations, and common bottlenecks. Use when scaling past ~100k entries or when search latency regresses.

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。

สร้าง chatbot flow, FAQ bank, escalation rule, reply template สำหรับ Line OA/Facebook Inbox/IG DM

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。

Packaging Designer — บรรจุภัณฑ์ box/bottle/label, dieline, material selection, print spec, shelf impact, CMYK/RGB color management

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。

Firmware development for the ESP32-C3 0.42" OLED board (ESP32-C3FH4, QFN32) — the ABRobot / 01Space "ESP32-C3-0.42LCD" mini board and its clones, sold as "ESP32-C3 SuperMini with OLED" and "ESP32 C3 OLED development board". Covers its 72x40 SSD1306 OLED on I2C, the single I2C bus, blue LED on GPIO8, BOOT button on GPIO9, USB Serial/JTAG console, ADC1, Wi-Fi/BLE, and the ESP-IDF + PlatformIO setup around them. Use when working on this board or a bare ESP32-C3: project setup, platformio.ini and sdkconfig, pin mapping and strapping pins, getting the 0.42-inch display to show something other than snow, U8g2 offsets, adding a second I2C device, flashing over USB-C, or debugging why something on the board does not work.

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。

Firmware development for the WeAct Studio RP2350A Core Board (RP2350A — dual Cortex-M33 @ 150 MHz, 520 KB SRAM, 4 MB or 16 MB QSPI flash) in both of its revisions, RP2350A_V10 and RP2350A_V20 — the 40-pin Pico-2-shaped header, 3-or-4-channel 12-bit ADC, PWM, PIO, USB-C CDC, the V1.0 LDO vs V2.0 buck-boost power wiring, and the PlatformIO + arduino-pico (earlephilhower) setup around them. Use when working on this board, a WeAct RP2350 core board of unknown revision, or any Raspberry Pi Pico 2 / RP2350A clone: project setup, platformio.ini, board = rpipico2 vs weact_rp2350b, telling V1.0 and V2.0 apart, pin mapping, LED and KEY pins, powering it from a battery, 4 MB vs 16 MB flash, erratum RP2350-E9 pull-down trouble, BOOT/RESET UF2 flashing, or debugging why something on the board does not work.

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。

Firmware development for the WeAct Studio "Black Pill" (STM32F411CEU6) and its clones such as the DFRobot DFR0864 — the 25 MHz HSE and 32.768 kHz LSE crystals, PC13 LED, K1 button, USB-C wired straight to USB_OTG_FS, ROM DFU flashing, the SPI-flash footprint, and the STM32Cube HAL + PlatformIO setup around them. Use when working on this board or any STM32F411CE/F401CC Black Pill: project setup, platformio.ini, clock and PLL configuration for 96 MHz plus 48 MHz USB, pin mapping on the 48-pin package, USB CDC console, RTC on the LSE crystal, the internal temperature sensor, ADC accuracy, DFU flashing and recovery, or debugging why something on the board does not work.

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。

Firmware development for the Beetle — the CJMCU / DFRobot "Mini Arduino Leonardo" USB board (ATmega32U4 @ 16 MHz, 5 V, 21×28 mm, castellated pads) — its native USB (CDC serial + HID keyboard/mouse/joystick), Caterina bootloader and 1200 bps touch upload, ten exposed I/O pads, four PWM pins across Timer0/Timer1, five ADC channels, I2C on D2/D3, SPI on the back-side ICSP pads, 28 KB usable flash and 2.5 KB SRAM, and the PlatformIO + Arduino AVR core (`board = leonardo`) setup around them. Use when working on this board or any ATmega32U4 Leonardo/Micro/Pro-Micro-class clone: project setup, platformio.ini, why the board shows up as two different serial ports, uploads that fail or hang, recovering a bricked or HID-spamming board by shorting the ICSP reset pads, pin mapping and which pads are missing, PWM/timer conflicts, Servo and tone, USB HID keyboard projects, the SRAM budget, powering from the + pad, or debugging why something on the board does not work.

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。

Diagnose failures in SKMTC sessions — no output, wrong output, error messages, failed bundle builds, parseIssues, "Registered definition mismatch", ref cycles, "Module not found" in generated code, or any other broken behavior. Applies across both CLI usage and generator authoring contexts. Use this skill when the user asks "why isn't my generator working", "no output for X", "wrong output", "what does this error mean", "manifest says X", "bundle failed", "INVALID_SCHEMA", "INVALID_DEPENDENCY_REF", "Registered definition mismatch", "Module not found" (in generated code), "ConfigValidationError", or reports any other SKMTC failure. This skill encodes a **verify-first epistemic stance** — read the manifest, check parseIssues, reproduce the failure before proposing fixes. Distinct from `skmtc-cli` and `skmtc-generator` which guide *doing*; this skill guides *diagnosing*.

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 Emacs as a channel. Opens an interactive chat buffer and org-mode integration so you can talk to NanoClaw from within Emacs (Doom, Spacemacs, or vanilla). Uses a local HTTP bridge — no bot token or external service needed.

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 Discord bot channel integration to NanoClaw.

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。