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Rigorous, defensible email-spoofability verdict and SPF supply-chain risk analysis computed from published DNS alone. Deepens the record-level SPF/DMARC/DKIM/BIMI/MTA-STS/DNSSEC fetch recipes in the offensive-osint arsenal (§16.14) with the reasoning that section doesn't do: a priority-ordered composite verdict for whether an attacker can actually land header-From-spoofed mail in an inbox, and by which vector (exact-domain vs subdomain) — grounded in the single most-misunderstood distinction in email security: the envelope MAIL FROM that SPF authenticates vs the visible header From: that only DMARC governs. Explains precisely why SPF -all/~all alone is NOT spoof-proof without DMARC enforcement, and why SPF +all bypasses DMARC even under p=reject pct=100. Covers RFC 7208 §4.6.4's 10-DNS-lookup / 2-void-lookup PermError fail-open condition with a runnable stdlib-only lookup-counter script, plus the SPF-include-takeover supply-chain vector (an attacker re-registering a dead include inherits SPF-pass authority over the victim domain) with strict transient-vs-NXDOMAIN discrimination discipline so a temporary SERVFAIL is never mistaken for a takeover lead. Fully passive: DNS TXT reads only, no mail sent, no RCPT TO probe, no API keys. Use when auditing a domain's real spoofing resistance (not just its published records), explaining to a client why 'we have SPF -all' does not mean they're covered, investigating an SPF PermError or an unusually long include chain, evaluating a dead SPF include as a takeover lead, or writing a defensible spoofability finding for a deliverable.

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Guide for running tests in the openai-dotnet repository. Use this when asked to run, debug, or validate tests, or when writing new tests. Explains test modes (Playback, Record, Live), how to identify recorded vs non-recorded tests, environment variable configuration, and what to do when recordings are missing or stale.

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Build AI-powered software with TypeSafe: small units of AI intelligence you can use like programming primitives. Its System One models, including Jev, turn natural language and application state into typed judgments and probabilities that code can combine. Use when a feature needs programmable common sense, when brainstorming what AI could make possible in an app, or when an LLM prompt-and-parse step could become a structured decision. Applications include routing, ranking, extraction, verification, and interactive experiences; these are starting points, not the limits. Read live docs and cookbooks to find useful patterns and discover new combinations.

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Author and edit `.svg` files in a Grida editor session — live-canvas binding, SVG output style, and parse-error recovery. Use when creating or modifying an SVG document.

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Write any link or URL so it resolves where it is rendered, not where it lives in the repo. Use when authoring or editing a link — in docs, source docstrings, READMEs (incl. npm-published), or product UI: docs cross-refs, "see SECURITY.md", universal `/_/` routes, GitHub URLs.

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TypeScript code shape inside a well-named module — taste, not lint. Prefer one class or namespace per file (the unit a test targets) over scattered free exports; consolidate related code, don't fragment. The unit of code should be the unit of spec. Use when authoring TS in `editor/grida-canvas*`, `editor/lib/`, or `packages/*`. Sibling to the `naming` skill; React-specific shape lives in `code-react`.

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Guides work on the Grida file format (.grida) from the TS side: the I/O packages that read/write it (loading, archive packing, clipboard) and the frozen schema bindings. Use when working with .grida files in the editor or packages, or debugging format round-trip issues. (The schema and the Rust decoder live in the engine repo.)

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React-specific code shape in the Grida editor. Hooks cannot be tested or benchmarked and silently break tuned UX under layered composition, so they are barred from the engine and main system — load-bearing logic lives in classes and namespaces, hooks only as thin edge wires. `data-testid` follows component-root discipline: one per significant component, not scattered. Use when authoring React in `editor/grida-canvas-react/`, `editor/components/`, `editor/scaffolds/`, or `editor/app/*`.

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Guides authoring, organizing, and referencing test fixtures in this repo. Use when creating new fixtures, writing tests that depend on fixtures, or deciding what should be checked into git. Engine fixtures (rendering corpora) live in the engine repo.

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Establish what is actually true and current for the surface you are about to change — not just search. Grounding = locate the authoritative source and reconcile sources that disagree (code vs doc, migration vs schema, memory vs current code, live vs archived), not take the first hit. Use before any grep/find/explore of the codebase or docs, when deciding which of several definitions is the real one, or when a doc or memory conflicts with the code. Covers the source-of-truth hierarchy, reconciliation discipline, scoped ripgrep, and the docs/tags.yml + docsearch.py index.

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Structured approach to workplace conflicts, performance discussions, and challenging feedback using preparation-delivery-followup framework. Use when preparing for tough conversations, addressing conflicts, giving critical feedback, or navigating sensitive workplace discussions.

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Excalidraw canvas toolkit for creating, editing, and refining diagrams on a live canvas. Use when an agent needs to (1) draw or lay out diagrams, (2) iteratively refine them by describing the scene and screenshotting its own work, (3) export/import .excalidraw files or PNG/SVG images, (4) save/restore canvas snapshots, (5) convert Mermaid to Excalidraw, or (6) perform element-level CRUD, alignment, distribution, grouping, duplication, and locking. Primary interface is the bundled CLI (npx -y mcp-excalidraw-server <command>) which auto-starts the canvas server; MCP tools and a REST API are equivalent alternatives.

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Prepare and validate research-only clinical decision-support evaluation, evidence-profile, cohort, survival, biomarker/model, privacy, and governance artifacts. Use for aggregate or synthetic research documentation and traceability—not patient care or live clinical operation.

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Use this skill whenever the user wants to create, read, edit, or manipulate Word documents (.docx files) or Word templates (.dotx files). Triggers include: any mention of 'Word doc', 'word document', '.docx', '.dotx', or requests to produce professional documents with formatting like tables of contents, headings, page numbers, or letterheads. Also use when extracting or reorganizing content from .docx or .dotx files, inserting or replacing images in documents, performing find-and-replace in Word files, working with tracked changes or comments, or converting content into a polished Word document. If the user asks for a 'report', 'memo', 'letter', 'template', or similar deliverable as a Word or .docx file, use this skill. Do NOT use for PDFs, spreadsheets, Google Docs, or general coding tasks unrelated to document generation.

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Create, edit, analyze, or convert Excel spreadsheets (.xlsx, .xlsm, .xltx) where the workbook file is the primary deliverable. Use for formulas, formatting, financial models, multi-sheet workbooks, and tabular cleanup exported to Excel. Also applies to .csv/.tsv when the user wants spreadsheet output. Do NOT use for Word documents, HTML reports, standalone Python scripts, database pipelines, or Google Sheets API work.

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Create and audit editable scientific posters in macro-free PowerPoint (.pptx) from author-approved local content and assets. Use when the requested deliverable is a PowerPoint research/conference poster and exact physical, printer, accessibility, provenance, and package-security checks are required.

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Entry P0 primary router and operating doctrine for HackSkills. Use when the task involves web application testing, API security assessment, recon, vulnerability triage, exploit path planning, authorized pentest, code audit, source-leak mining, middleware audit, SOC triage, detection engineering, incident response, or choosing the right next category skill before any deep topic skill. Also use when the user mentions 安全工程师, 渗透测试, 红队, 蓝队, 代码审计, 源码泄露, SRC. Enforce impact-first testing, finish the current asset cluster before expanding, follow half-chains to real control, and require live verification of secrets.

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Use for "how does X work", code walkthroughs before changing something, and placement / ownership / layering questions ("where should this live", "which package owns this", "is this the right layer"). Explains subsystem architecture, runtime flow, onboarding mental models. Use why for motivation.

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Periodic pass that keeps a project's verification skill and feature map honest: parallel source readers per feature, one live session driving every feature, at most one PR of proven corrections. Use for /maintain-verification-skill or "audit the verify skill".

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Apply to multi-step work (sweeps, migrations, runs of similar edits) and to how you stack commits and PRs. Break work into small units that each end in a verifiable state, check each before the next, and order delivery so the sequence proves itself to a reviewer.

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Reconstruct your recent working context from your own chat history, live state, and the shared record (user reports, prior fixes, incidents), then hand back a tight current-state brief. Use for 'recall my work on X', 'catch me up', 'what have I been working on', 'where did I leave off', before starting or resuming work, and before telling the user that something was never recorded.

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Apply lean thinking to UX: hypothesis-driven design, collaborative sketching, and rapid experiments instead of heavy deliverables. Use when the user mentions "Lean UX", "design hypothesis", "outcome over output", "design studio method", "assumption mapping", "lightweight research", "too much design documentation", or "get the team designing together". Also trigger when reducing design-documentation overhead, getting cross-functional teams to co-design, or running fast usability experiments. Covers hypothesis statements, MVPs for UX, and cross-functional collaboration. For Build-Measure-Learn, see lean-startup. For usability audits, see ux-heuristics.

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Build a weekly cadence of customer touchpoints using Opportunity Solution Trees, assumption mapping, and interview snapshots. Use when the user mentions "continuous discovery", "opportunity solution tree", "weekly interviews", "assumption testing", "discovery habits", "product trio", "outcome-based roadmap", "how do I talk to customers regularly", "we keep building things nobody uses", or "connect research to the roadmap". Also trigger when setting up regular customer feedback loops, prioritizing which experiments to run, or tying discovery insights to delivery work. Covers experience mapping, co-creation, and prioritizing opportunities. For interview technique, see mom-test. For team structure, see inspired-product.

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Guided journey from a live website that underperforms to a prioritized, evidence-backed backlog of conversion, usability, message, and speed fixes - each shipped as a testable experiment. Orchestrates eight skills phase by phase - cro-methodology, ux-heuristics, refactoring-ui, web-typography, storybrand-messaging, high-perf-browser, made-to-stick, design-everyday-things - asking the user questions at every decision point and recording results in the project docs/ folder (WEBSITE.md, DESIGN.md, IMPROVE-WEBSITE-PLAN.md) so the journey resumes across sessions. Use when the user wants to fix a landing page that isn't converting, diagnose why visitors leave, audit for clarity and usability, or says 'the homepage feels off but a redesign didn't help'. No site yet, create-website; converts but needs traffic, grow-website; if the friction is in a product app, not the marketing site, improve-app; if one specific flow leaks, conversion-optimization. For one framework in isolation, invoke that skill directly.

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