1천건 · 관련도순
When the user wants SEO pages generated at scale from templates plus a dataset — "programmatic SEO," "pSEO," "directory pages," "location pages," "[keyword] + [city] pages," "integration pages," "generate 100 pages," "templated landing pages." For auditing an existing site, see seo-audit. For planning, see content-strategy.
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Use this skill when the company acts as a processor for its customers and someone asks "update our subprocessor list", "are we missing subprocessors", "we added a new tool, do we need to tell customers", "check the public subprocessor page", "where is customer data processed" or "draft the subprocessor change notice". Finds which suppliers actually receive customer personal data, compares them with the published list, records purpose, data, locations and transfer basis for each, works out the customer notice duties from the signed agreements, and writes an updated register, a change list and a draft notice for review.
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Audits Python + BigQuery pipelines for cost safety, idempotency, and production readiness. Returns a structured report with exact patch locations. Use before deploying or after a cost spike in a Python pipeline that queries BigQuery.
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Enforce output quality, evidence verification, and quality gates across security audits. Use this skill when you perform SAST, SCA, threat modeling, or security code reviews. Use this skill to verify code locations and taint traces for all findings. Use this skill to prevent the suppression of valid security findings. Use this skill to evaluate reports against quality thresholds (score ≥ 8/10) before delivery.
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Marketing leadership for scaling companies. Brand positioning, growth model design, marketing budget allocation, and marketing org design. Use when designing brand strategy, selecting growth models (PLG vs sales-led vs community-led), allocating marketing budgets, building marketing teams, or when user mentions CMO, brand strategy, growth model, CAC, LTV, channel mix, or marketing ROI.
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Use notebook-connector's Python connection helpers for Exasol, BucketFS, SQLAlchemy, and Ibis. Covers open_pyexasol_connection, open_sqlalchemy_connection, open_ibis_connection, open_bucketfs_bucket, open_bucketfs_location, get_backend, and related helper functions.
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Deploys and monitors ransomware canary files across critical directories using Python's watchdog library for real-time filesystem event detection. Places strategically named decoy files that mimic high-value targets (financial records, credentials, database exports) in locations ransomware typically enumerates first. Monitors for any read, modify, rename, or delete operations on canary files and triggers immediate alerts via email, Slack webhook, or syslog when interaction is detected, providing early warning before full encryption begins.
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Detect compromised O365 and Google Workspace email accounts by analyzing inbox rule creation, suspicious sign-in locations, mail forwarding rules, and unusual API access patterns via Microsoft Graph and audit logs.
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Use Sysinternals Autoruns to systematically identify and analyze malware persistence mechanisms across registry keys, scheduled tasks, services, drivers, and startup locations on Windows systems.
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Detect and analyze heap spray attacks in memory dumps using Volatility3 plugins to identify NOP sled patterns, shellcode landing zones, and suspicious large allocations in process virtual address space.
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Get current weather and forecasts via wttr.in or Open-Meteo. Use when: user asks about weather, temperature, or forecasts for any location. NOT for: historical weather data, severe weather alerts, or detailed meteorological analysis. No API key needed.
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Configure and distribute creator fees to multiple shareholders using the PumpFees program with BPS-based share allocation, admin management, and cross-program fee consolidation for graduated tokens.
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Reviews marketing, packaging, web or sustainability text against the environmental-claim rules the user supplies (house policy, regulator guidance extract, industry code) and returns a DRAFT claims review: every environmental claim quoted verbatim with location and family, the evidence the text or evidence pack offers for it with date and scope, the supplied rule passages that bear on each claim, observations as read, and separate question lists for legal and for marketing. No compliance, greenwashing or substantiation verdict. Use when the user asks to "review these green claims", "check this copy against our environmental claims policy", "what evidence do we have for carbon neutral here", "list the sustainability claims in this brochure" or "prepare questions for legal on this eco campaign". Do not use for mapping general factual claims to evidence, use claims-evidence-map instead. Drafts for human review; never approves, authorises or signs off.
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Reviews the text and structure of a document, slide deck or web page against the accessibility rules the user supplies, or a default set covering heading structure, image alternative text, colour used as the only cue, link text, reading order, tables and language, and returns numbered findings with location, rule, severity and a ready-to-apply fix for the author, plus proposed alt text and a list of checks that need a tool or a person. Use when the user asks to "check this document for accessibility", "review the alt text in this deck", "is this page accessible", "run an accessibility check on these slides", "find accessibility issues before I publish" or "check my headings and link text". Do not use for brand or template compliance of slides, use branded-deck-builder instead. Drafts for human review; never approves, authorises or signs off.
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Reviews one SKILL.md against the format rules and returns a findings table: strict YAML front matter with exactly name and description, name equal to the folder, description as the trigger, the eight-heading skeleton, capability-neutral wording, safety boundaries. Each finding carries severity, rule identifier, location, quoted evidence and replacement text; the verdict READY, REVISE or BLOCKED is an apparent state and the owner decides. Use when the user asks to "review this SKILL.md", "check my skill file before upload", "lint this skill description", "validate the front matter of this skill" or "score this skill folder". Do not use to write an agent's instructions field, use agent-instructions-drafter instead; for injection or leakage exposures use agent-instructions-red-team; for launch tests use agent-evaluation-plan. Drafts for human review; never approves, authorises or signs off.
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Builds a DRAFT quiz from the training content the user supplies (slide deck, manual, e-learning script, session transcript, procedure): numbered questions with the correct answer, distractors drawn from the content itself, an explanation quoting the source passage with its location, a difficulty tag (Recall, Apply, Analyse) with its basis, and a coverage table showing which sections and objectives each question tests and which are left uncovered. Use when the user asks to "build a quiz from this deck", "write knowledge check questions for this module", "create an assessment from this training", "test understanding of this procedure" or "which sections does this quiz cover". Do not use for a reader-facing question and answer page built from documents, use faq-builder instead; for writing the procedure itself from notes or a walkthrough, use sop-drafter. Drafts for human review; never approves, authorises or signs off.
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Reviews a proposal, business case, deck or plan in character as an Investor archetype and returns a DRAFT review in the chat with a verdict whose conditions read as terms, findings that cite the exact passage, capital-allocation risks, what would change the verdict and five interrogation questions. Use when the user asks to "run an investor review", "what would an investor say about this", "pressure-test the capital case" or "prepare me for the investment committee". Do not use for internal budget, cost or finance-function review, use cfo-reviewer instead; for revenue forecast and pipeline, use cro-reviewer. Drafts for human review; never approves, authorises or signs off.
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Reads a cash forecast (spreadsheet, model export, pasted table or the narrative that accompanies it) and returns a DRAFT assumptions sheet: every assumption the forecast rests on, stated or implied by the figures, with its value as read, its location in the model, the cash lines it drives, its stated source or "not stated", the evidence that would test it, an owner, and one neutral challenge question, so a reviewer can work through the assumptions one by one. Use when the user asks to "list the assumptions behind this cash forecast", "what is this cash flow forecast assuming", "prepare the challenge questions for the treasury review", "pull out the drivers of the 13-week cash forecast" or "build an assumptions register for the liquidity plan". Do not use for actuals against budget by line, use budget-variance-explainer instead; do not use for the case behind a capital request, use capex-request-pack instead. Drafts for human review; never approves, authorises or signs off.
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Registry of reusable agent sessions and slot allocation: claim a free scheduled-task slot instead of creating a new session, set its prompt and fire time, and release it when done. Use when you need to spawn or reuse a visible background session.
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- Geolocate and chronolocate a photo or video from visual evidence alone — plate and phone number formats, road markings, utility poles, bollards, signage typefaces, architecture and vegetation for… Use when asked where or when a picture was taken, to verify a claimed location without GPS or EXIF, or to match a scene against Google Earth, Street View, Yandex Panoramas, Mapillary or KartaView
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React bindings for TanStack Router: RouterProvider, useRouter, useRouterState, useMatch, useMatches, useLocation, useSearch, useParams, useNavigate, useLoaderData, useLoaderDeps, useRouteContext, useBlocker, useCanGoBack, Link, Navigate, Outlet, CatchBoundary, ErrorComponent. React-specific patterns for hooks, providers, SSR hydration, and createLink with forwardRef.
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Knowledge base from MIL-HDBK-338B (Electronic Reliability Design Handbook). Use for electronic reliability engineering: R/M/A theory, reliability specification/allocation/prediction, parts management and derating, reliable circuit and fault-tolerant design, environmental and human performance reliability, FMEA/FMECA/FTA/sneak circuit analysis, design reviews and testability, FRACAS, reliability demonstration and growth testing, and systems-level R&M parameters. Covers selected Part 2 design-guidance topics only; skips large annex/part-stress tables. Guidance handbook — not a contractual requirement text. Does not replace MIL-HDBK-217 prediction libraries, service-specific reliability regs, or safety standards (see mil-std-882).
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Knowledge base from the FAA Requirements Engineering Management Handbook (DOT/FAA/AR-08/32). Use for writing requirements for real-time, embedded control systems — the avionics/medical slant — via the Handbook's eleven recommended practices: system overview and boundary (monitored/controlled variables), operational concepts (use cases), environmental assumptions, change-tolerant functional architecture (dependency diagrams), safety-driven architecture revision (FHA/PSSA/fault tree), system modes, detailed behavior and performance requirements (ideal value + tolerance + latency), the four-variable model bridge to software requirements (MON/CON/NAT/REQ, IN'/REQ'/OUT', DO-178B mapping), subsystem allocation, and rationale. Carries the Isolette Thermostat and Flight Control System worked examples. Slanted toward control systems with sensors and actuators; thin on information-system / enterprise / agile requirements, on requirements-management tooling, and on the formal-methods internals of SCR/RSML/SpecTRM (it names them, does not re-teach them). Does not reproduce the IEEE/DO-178B/ARP standards it cites.
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Knowledge base from the FAA Human Factors Design Standard (HF-STD-001B, 2016) — the FAA's consolidated human-factors / human-systems-integration design criteria for systems it manages, operates, or maintains. Use for requirement-level design rules on: general human-factors design principles; automation and function allocation; designing equipment for maintenance; displays, controls, and visual indicators; alarms, audio, and voice communications; the computer-human interface (information presentation, coding, interaction styles, windows, dialogue); keyboards, input devices, and workstation/workplace ergonomics; system security, personnel safety, environment, anthropometry, and user documentation; plus intended-use and tailoring guidance. It is a quantified, source-attributed synthesis (heavily citing MIL-STD-1472G, MIL-HDBK-759C, DOD-HFDG-ATCCS, NUREG-0700, NASA-STD-3000, ANSI, OSHA, ISO 9241). Complements nasa-hsi as a parallel HSI tradition from the civil-aviation domain. Scope limits: it is design criteria, NOT an HSI lifecycle/process model (use nasa-hsi, nasa-npr-7123, or dau-se-guidebook for process); it does NOT reproduce the third-party standards it cites; it is FAA-acquisition-oriented (ATC, towers, TRACONs, airway facilities), not a general consumer-UX guide; and it is thin on modern touchscreen/mobile, web, and AI-driven interface patterns and on quantitative human-reliability analysis.
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