Audit personal finance and budgeting app spending intelligence features. Triggers: you need to evaluate transaction categorization accuracy (MCC mapping, ML classification, merchant 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。
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概要と使いどころ
Audit personal finance and budgeting app spending intelligence features. Triggers: you need to evaluate transaction categorization accuracy (MCC mapping, ML classification, merchant 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 film, television, and digital content production budgets for above-the-line (ATL) and below-the-line (BTL) cost accuracy, SAG-AFTRA/DGA/WGA/IATSE union rate compliance, fringe and payroll tax calculations, VFX bid variance analysis, post-production cost validation.
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 university and research institution funding allocation systems including RCM revenue attribution, performance-based budgeting, faculty startup package management, F&A indirect cost recovery distribution, equipment sharing and core facility recharge rates.
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。
Personal financial planner for Thailand-based users. Use this skill when the user asks for help with budgeting, tax planning involving Thai-specific products (SSF, RMF, Thai ESG, Thai ESGX, Easy E-Receipt), debt strategy at Thai bank rates, retirement planning involving ประกันสังคม (มาตรา 33/39/40), กบข., PVD (provident fund), or any personal-money question framed in baht and Thai life events. Strong activation phrases include "ช่วยวางแผนการเงิน", "วางแผนภาษี", "ปลดหนี้บัตรเครดิต", "ลดหย่อน RMF", "Help me with my Thai finances", "How much should I save in Thailand", "ม.33 vs ม.39", "เกษียณต้องเก็บเงินเท่าไหร่". Do NOT use for non-Thai financial contexts (US 401(k), Canadian RRSP, UK ISA, etc.) — different skills exist for those.
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 Waveshare ESP32-C6-Touch-LCD-1.47 board (ESP32-C6FH8, QFN32, 8 MB flash, SKU 31203 / 31201-M) — its 1.47" 172x320 JD9853 IPS panel, AXS5106L capacitive touch controller on I2C 0x63, QMI8658A IMU on I2C 0x6B, microSD/TF slot on the shared SPI2 bus, ETA6098 battery charger with VBAT sensing, USB-Serial-JTAG console, Wi-Fi 6/BLE/802.15.4 radio, and the ESP-IDF + PlatformIO setup around them. Use when working on this board: project setup, platformio.ini and sdkconfig, pin mapping and strapping pins, JD9853 bring-up, touch coordinates and calibration, LVGL memory budgeting, backlight PWM, TF card on the shared bus, battery voltage, flashing over Type-C, or debugging why something on the board does not work. This is NOT the non-touch ESP32-C6-LCD-1.47 (ST7789, 4 MB) — the two share a name and almost no pins.
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 LLM context windows deliberately — budgeting, prioritization, summarization, and retrieval instead of dumping everything in. Use when prompts grow long, costs rise, or the model loses track of key details.
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Produces a practitioner-grade Blue Sky compliance memorandum and execution plan for U.S. securities offerings. Analyzes NSMIA covered securities preemption, classifies offerings under Regulation D/Rule 506 or alternative federal exemptions, maps state jurisdictional nexus distinguishing offers from sales, and generates a state-by-state filing plan with Form D/EFD workflow, fee schedules, amendment triggers, and renewal calendars. Use this skill when advising on private placement Blue Sky compliance, Reg D notice filings, multi-state offering coordination, state securities registration exemptions, Form D filings, EFD submissions, or state fee budgeting. Also trigger when the user mentions covered securities preemption, NSMIA analysis, or asks about state notice filing requirements. Even if the user just says "Blue Sky" or "state filings for our raise," 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。
Track real-time API cost accrual during LLM execution. Activate on 'cost tracking', 'token usage', 'API costs', 'budget monitoring', 'usage metrics'. NOT for cost estimation, pricing tiers, or billing systems.
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。
How to design contextual inputs for an always-on AI agent with episodic memory. Covers what data to feed the agent, how to structure observations and triggers, ambient context capture (screen, audio, calendar), context window budgeting, and retrieval strategies that keep the agent grounded in what's actually happening. Activate on: "what should the agent observe", "context inputs for agent", "ambient context capture", "agent triggers", "agent input design", "screenpipe integration", "context window budget", "what data to feed my agent", "/always-on-agent-inputs". NOT for: memory architecture and storage (use always-on-agent-architecture), application ideas (use always-on-agent-applications), safety concerns (use always-on-agent-safety).
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。
Professional financial analysis skill for investment decisions, budgeting, financial statement analysis, and business plan evaluation. Use this skill when you need to analyze financial ratios (profitability, safety, efficiency), calculate DCF/NPV/IRR valuations, perform budget variance analysis, or conduct sensitivity/scenario analysis. Triggers include "analyze financial statements", "calculate DCF", "investment evaluation", "budget variance", "財務分析", "投資評価", "予算差異分析".
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Use when advising, planning, reviewing, reporting, operating, or improving CTO and technology leadership work across strategy, cybersecurity management, SME/COE, functional and technical requirements, framework selection, people, organization, delivery, risk, KPI, roadmap, budgeting, governance, audit, R&D, stakeholder communication, culture, politics, and sector-specific leadership.
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。
Knowledge base from the SD-22 DMSMS Guidebook (DSPO, FY24 working draft). Use for managing Diminished Manufacturing Sources and Material Shortages (DMSMS) and obsolescence across a long-lived system's life cycle: the five-step process (Prepare, Identify, Assess, Analyze, Implement) plus the Strategize overlay; standing up a DMSMS Management Team (DMT) and Management Plan (DMP); risk-based monitoring and surveillance (the risk cube, predictive tools, vendor surveys, GIDEP/DLA PDNs, critical-materials analysis); health assessments and resolution timing; costing and selecting resolutions (life-of-need buys, substitutes, redesign, technology refreshment) by AoA/BCA; and budgeting/executing resolutions through modification funding and the ECP process. Defense-sustainment / DoD-acquisition framing throughout. Does NOT teach general systems engineering, parts-management standards, or contracting law in depth, and does not reproduce DoD policy text or the source's tables and figures.
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。
Shared types, SKILL.md renderer, and token budgeting for skillit plugins
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。
Axis-by-axis interview methodology for establishing engineering performance budgets during architecture PRD compilation. Use when conducting the Step 10.5 performance budget interview in /create-prd-compile.
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。
Token budgeting discipline for all agents. Treats tokens as a resource from session start — not just when the buffer hits 60%. Covers prompt compression, context hygiene, handoff packing, and HOT memory pruning.
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。
Financial analyst agent skill and plugin for Claude Code, Codex, Gemini CLI, Cursor, OpenClaw. Ratio analysis, DCF valuation, budget variance, rolling forecasts. 4 Python tools (stdlib-only).
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Use this skill when the user asks the cost of pulling a Motor Vehicle Record (MVR) in a specific state, or wants to compare MVR fees across multiple states, or is budgeting annual compliance costs for a multi-state fleet. Reference the canonical fee table below; flag that fees change (re-verify with state DMV before annual budget planning).
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Use when a carrier owner, CFO, or controller asks how to build an annual budget, monthly P&L model, cash flow forecast, scenario plan, or break-even analysis for a trucking operation. Covers revenue modeling, cost structures, capital planning, and the discipline of tracking actuals vs budget.
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。
Complete personal finance system — budgeting, debt payoff, investing, tax optimization, net worth tracking, and financial independence planning. Use when managing money, building wealth, paying off debt, planning retirement, or optimizing taxes. Zero dependencies.
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。
Comprehensive OSINT methodology for external red-team operations and authorized attack-surface assessments. Covers the 5-stage recon pipeline (seed discovery, asset expansion, enrichment, exposure analysis, reporting), asset-graph discipline with 29 asset types, severity rubric (CRITICAL/HIGH/MEDIUM/LOW/INFO), confidence upgrade workflows, time budgeting, asset-level triage rules, scale-based tactics, identity-fabric mapping (Entra/Okta/ADFS/Google/SAML/M365 Teams+SharePoint+OAuth), API and auth-map methodology, JavaScript deep analysis, mobile attack surface, cloud attack surface, breach×identity correlation, detectability tagging, detection-aware probing (back-off, persona rotation), read-only validator discipline, WAF/CDN bypass + origin discovery, vulnerability prioritization (CVE/EPSS/KEV), phishing infrastructure planning + pretext development, bug bounty submission templates, client deliverable templates with risk translation, threat-actor investigation (incl. RU/CN pivots), cryptocurrency tracing,...
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。
Complete personal finance system — budgeting, debt payoff, investing, tax optimization, net worth tracking, and financial independence planning. Use when managing money, building wealth, paying off debt, planning retirement, or optimizing taxes. Zero dependencies.
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。
Track real-time API cost accrual during LLM execution. Activate on 'cost tracking', 'token usage', 'API costs', 'budget monitoring', 'usage metrics'. NOT for cost estimation, pricing tiers, or billing systems.
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。
How to design contextual inputs for an always-on AI agent with episodic memory. Covers what data to feed the agent, how to structure observations and triggers, ambient context capture (screen, audio, calendar), context window budgeting, and retrieval strategies that keep the agent grounded in what's actually happening. Activate on: "what should the agent observe", "context inputs for agent", "ambient context capture", "agent triggers", "agent input design", "screenpipe integration", "context window budget", "what data to feed my agent", "/always-on-agent-inputs". NOT for: memory architecture and storage (use always-on-agent-architecture), application ideas (use always-on-agent-applications), safety concerns (use always-on-agent-safety).
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。