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Generates structured cyber threat intelligence reports at strategic, operational, and tactical levels tailored to specific audiences including executives, security operations teams, and technical analysts. Use when producing finished intelligence products from raw collection data, creating sector threat briefings, or delivering post-incident intelligence assessments. Activates for requests involving CTI report writing, threat briefings, intelligence products, finished intelligence, or executive security reporting.

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Export the current chat session as a structured Markdown work timeline or blog-draft seed. Use when the user asks for a session log, work log, timeline, 作業ログ, ブログネタ, blog draft, article seed, Zenn, Qiita, or はてな. Do not use for verbatim dialogue export or distilled reusable knowledge only.

Perform static reverse engineering and analysis on Windows Portable Executable (PE) files to identify malicious indicators without executing the file. Use this skill during Incident Response, malware triage, or threat hunting to safely extract metadata, imported APIs, exported functions, embedded strings, and packed indicators from suspicious Windows binaries (.exe, .dll, .sys).

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Full-funnel paid advertising operations for B2B SaaS. Use this skill for PPC strategy, Google Ads optimization, LinkedIn Ads, social media advertising, programmatic buying, creative strategy, attribution modeling, budget allocation, budget pacing and planned-vs-delivered reconciliation, audience overlap and campaign self-competition audits, suppression lists, ROAS improvement, media spend optimization, and the media no auction sells — newsletter and podcast sponsorships, community and industry-publication placements, paid review-site listings on G2 and Capterra, and pay-per-lead content syndication. It also covers buying on the AI answer surface — ads inside Google AI Overviews and AI Mode that existing Search, Shopping and Performance Max campaigns already serve into with no opt-out, no placement targeting and no segmented reporting, and ChatGPT Ads and Microsoft Copilot as separate opt-in platforms with their own plan-tier reach limits, no negative keywords, and a landing-page crawler gate. It also owns the conversion signal the bidding algorithms learn from — CRM pipeline stages (SQL, opportunity, closed-won) sent back to Google Ads, LinkedIn, Meta and Microsoft Ads through offline conversion import, enhanced conversions for leads, the Google Data Manager API and the LinkedIn Conversions API, with click-ID capture, stage values, dedupe, EEA consent signals and retractions. It also gates connected TV (CTV) and streaming video for B2B — whether a reach medium belongs in the plan, how a vendor ties a TV household to a target account (member data, IP-to-account graph or contextual), the server-side ad insertion (SSAI) fraud questions, Programmatic Guaranteed deals, and a holdout lift test because CTV has no click. It also runs person-led paid social — LinkedIn Thought Leader Ads and Meta partnership ads that put spend behind an employee's or creator's post — on a paid-usage term, an in-post disclosure check and an end-date register, because the platform approval carries no term. Also triggers on: CTV, connected TV, OTT, streaming TV ads, should we run CTV, LinkedIn CTV, B2B CTV, account-based CTV, SSAI fraud, thought leader ads, boost an employee's post, sponsor a creator's post, partnership ads, whitelisting, creator usage rights, PPC, Google Ads, LinkedIn Ads, social ads, programmatic, ad creative, attribution, media budget, paid campaigns, ROAS, CPA, ad spend, newsletter sponsorship, podcast sponsorship, community sponsorship, sponsor a newsletter, content syndication, pay-per-lead, cost per lead vendor, media kit, rate card, insertion order, direct buy, publisher partnership, make-good, G2 paid listing, Capterra ads, review site advertising, sponsorship ROI, budget pacing, we underspent our budget, are our campaigns competing with each other, audience overlap, self-competition, campaign cannibalization, suppression list, exclusion list, ad frequency across channels, how many ad accounts do we have, ads in AI Overviews, AI Mode ads, ChatGPT Ads, OpenAI Ads Manager, Copilot ads, conversational ads, should we advertise on ChatGPT, can we buy our way into the AI answer, our ads are showing in AI Overviews and we cannot report on it, context hints, OAI-AdsBot, our ad landing page fails review, robots.txt is blocking our ads, our paid leads are junk, Google Ads is optimizing for the wrong leads, offline conversion import, OCI, enhanced conversions for leads, send CRM stages back to Google Ads, upload SQLs to LinkedIn, LinkedIn Conversions API, LinkedIn CAPI, Meta conversion leads, CRM to ad platform, gclid, li_fat_id, msclkid, value-based bidding, optimize for pipeline not form fills, low match rate, conversion lag.

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Audit an existing mathematical, logical, algorithmic, or technical proof from its stated conclusion backward as a bounded AND/OR graph of exact obligations. Use to reconstruct conclusion dependencies, determine whether a proof-supplied route establishes the conclusion, or expose hidden assumptions, unmet side conditions, cycles, overly strong steps, or silent route switches. For a source-mapped Lamport rendering use convert-lamport, and for forward hierarchy, construct, and scope conformance use forward-lamport before this skill. This does not decide full theorem-level entailment by searching for a different proof; do not turn the audit into a linear reversed proof, exhaustive proof search, or replacement proof.

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Audit an existing Lamport-style hierarchical mathematical proof forward for validity and whether its hierarchy, scope, dependencies, side conditions, and proof constructs discharge the stated theorem. Use when the central question concerns a top-down proof with numbered levels, subproofs, ASSUME/PROVE, SUFFICES, PICK, CASE, DEFINE, Q.E.D., or prose equivalents. For an ordinary proof that first needs source-preserving hierarchy, use convert-lamport; for conclusion-first AND/OR obligation reconstruction, use reverse-lamport. Do not use to generate or replace a proof, or to audit Lean, Coq, Isabelle, or other proof-assistant source.

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。

Write a structured client status report for a consulting engagement. Use when a consultant says "write my weekly status update", "I need to send a status report", "draft the client update", "what should be in the weekly report", "client wants a progress update", "help me write the RAG status", "I need to report on blockers", "end of week update to the client", or "help me communicate what's stuck". Also trigger when someone needs to communicate engagement progress, surface blockers to the client, or flag decisions that need to be made by the sponsor.

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Gathering and documenting Salesforce marketing reporting requirements: defining KPIs, choosing an attribution model (First Touch / Last Touch / Even Distribution / Multi-Touch), selecting the right Campaign Influence configuration, and mapping business questions to report types and dashboard features. NOT for actually building the Campaign Hierarchy and CCI models - use admin/campaign-planning-and-attribution. NOT for CRM Analytics dataset and dashboard requirements - use admin/analytics-requirements-gathering.

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Imports gene expression count matrices from featureCounts, HTSeq, STAR ReadsPerGene, Salmon/kallisto via tximport or tximeta, RSEM, 10X Genomics MTX/H5, AnnData H5AD, and RDS. Handles silent-miscounting traps (featureCounts -p v2.0.2 API break, STAR strandedness column choice, salmon NumReads-sum without tximport, RSEM non-integer expected_count, GENCODE _PAR_Y suffix, zero-length-transcript TPM divide-by-zero), and encodes the tximport countsFromAbundance decision tree with the "lengthScaledTPM is not TPM" warning. Use when assembling a gene-by-sample count matrix from aligner or quantifier output, importing salmon/kallisto for DESeq2 vs limma-voom, choosing strandedness column for STAR, debugging zero-count panics, or building tx2gene mapping.

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。

Scans CopilotKit's public product / pricing / Premium pages at the start of every weekly report to produce the authoritative list of COMMERCIAL surfaces (Premium · CopilotKit Enterprise · Intelligence Platform · paid tiers) and detect any newly-added or changed commercial feature since last week. This list defines what the report's 🏢 Enterprise section is about — CopilotKit's commercial/paid product, NOT "CopilotKit running inside an enterprise company." Emits the surface list + a free-vs-paid classifier the report uses to decide "does this issue hit a commercial surface?", plus a diff of what changed. Runs as a subagent (many web fetches) so the orchestrator's context stays small. Invoked by weekly-report (spawned at report start) and the enterprise skill; also triggers on "scan product surfaces", "what's premium", "commercial surfaces", "did we add a premium feature".

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Generate the ≤10-minute Loom walkthrough script for a completed Weekly Community Signal report — a plain spoken briefing that dives straight into what the team needs to know, walking the report top to bottom (CopilotKit page first, then AG-UI in the same order). Straightforward and factual, NOT a radio show or a performance; no hype opener, no blame framing. Runs after every report (invoked by weekly-report) and on "loom script", "walkthrough script", "record the loom", "narrate the report".

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Creates stakeholder communications including investor updates, board reports, annual impact reports, and partner communications aligned with B Corp PSG standards. Use when user asks about investor relations, board communications, stakeholder reporting, impact reports, annual reports, or partner/supplier communications.

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Publish a proposal, offer, or pitch as a tracked link and report back whether it's getting read (view analytics after sending). Use when the user says "send the proposal", "did they open it", "track whether they read it", "share the offer". Not for recurring client reports (use client-reporter) or general research shares (use report-publisher).

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Polish an existing report, deck, or HTML page to the ReportRoom design bar — visual hierarchy, typography, charts, dark mode, OG/social link preview. Use when the user says "make it beautiful", "improve the design", "it looks plain", "fix the layout" about something already written or published. Not for creating content from scratch (use report-publisher or deck-publisher).

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。

Load this skill whenever you are filing, reviewing, or generating accessibility bug reports — whether from automated tool output, manual testing, user reports, or testing with disabled people. The purpose of this skill is to make accessibility findings easier to report accurately, connect them to real people and tasks, and let developers reproduce, understand, and fix them without unnecessary back-and-forth. Absolutely always describe the barrier and its task impact before citing a WCAG criterion. Under no circumstances guess a disability diagnosis, treat automated tool output as a conformance conclusion, or expose secrets/personal data in a report.

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Implement a phishing report button in email clients with automated triage workflow that analyzes user-reported suspicious emails and provides feedback to reporters.

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。

Reads one export transaction, order or shipment description and returns a DRAFT export review pack: parties to screen with a screening checklist, an item classification worksheet, a red-flag review, licence-determination questions and open items. Use when the user asks to "prepare the export review for this order", "pre-check this shipment for export control", "who do we need to screen on this deal", "build the classification worksheet for this item" or "assemble the trade-compliance file for this technology transfer". Do not use for vendor security or due-diligence screening of a supplier's questionnaire answers; use vendor-risk-screening-brief instead. Never classifies, screens, clears, decides licence need or releases a shipment; trade compliance does. Drafts for human review; never approves, authorises or signs off.

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Turns reported data problems (messages, tickets, meeting notes, complaints) into one DRAFT issue log: one row per issue with the symptom as reported, dataset and fields named, reproduction steps, affected reports, first seen date, reporters, a suggested owner, and blank severity, root cause and status cells for the owner. Never asserts a root cause, severity or fix. Use when the user asks to "log these data issues", "turn these complaints about the numbers into an issue list", "build the data quality backlog", "which reports are hit by this data problem" or "write up the reproduction steps for this data bug". Do not use for exploring or profiling a dataset, use dataset-insight-pack instead; for an IT incident write-up, use incident-postmortem-drafter; for tracking fix actions once assigned, use corrective-action-tracker. Drafts for human review; never approves, authorises or signs off.

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ISTQB/JSTQB のテスト完了（test completion）活動のうち、テスト実行結果の評価と完了基準（exit criteria）判定を支援するスキル。テスト実行ログ（test-execution-log.md）と test-plan の完了基準を突き合わせ、完了とみなせるかを判定した test-summary-report.md を作る。テスト完了時の最終レポートにも、テスト途中の中間評価にも使える。「テスト結果をまとめて」「完了基準を満たしたか判定して」「テストレポートを書いて」「今どこまでテストが進んだか評価して」と依頼されたときに使う。単発のテスト作成依頼（単にユニットテストを書きたいだけ）は対象外。/test-report <テスト対象名> で明示的に呼び出されたときのみ使用する。

Fold a fresh export of an already-imported Telegram chat into a vault, adding only the new messages. Idempotent by message id, so it never duplicates. Triggers: "re-import <chat>", "update the telegram import".

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Generate a structured report on completed work, a feature area, or a topic. Saved to the reports directory. Invoked by saying "report", "generate report", or "summarize work".

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Operational guide for the base+pro → Content Graph ecosystem port loop — porting Pro addon files byte-identical into plugins/nvoos-content-graph-pro cluster-by-cluster (transform rules, byte-identity verifier, standalone-only wiring, dual-matrix validation, tracker updates, PR + self-merge). Use when the user asks to "continue the loop", "do the next cluster", "port <toolkit> to CG Pro", or resumes a Wave E/F port session.

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Background processing and heavy computations using Dart Isolates with Isolate.run(), compute() function, and platform channels. Use this skill when performing CPU-intensive operations without blocking UI (image processing, data parsing, encryption), implementing background tasks that prevent jank or frame drops, handling large file operations (JSON parsing, database migrations), running parallel computations, fixing UI freezes caused by main thread blocking, using compute() for one-off background work, creating long-lived Isolates with ReceivePort/SendPort, implementing multi-threaded algorithms, debugging isolate communication issues, or preventing memory leaks from unclosed ReceivePorts. Covers isolate spawn, message passing, ReceivePort cleanup (CRITICAL for leak prevention), SendPort communication patterns, error handling, serialization rules, and performance optimization for compute-heavy operations.

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Expert en portail citoyen (CNI, passeport, permis, casier judiciaire, état civil, DZ)

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。