When the user wants to figure out which marketing actually drives conversions and revenue, choose or interpret an attribution model, or reconcile conflicting numbers across tools. Also use when the user mentions "attribution," "attribution model," "first-touch vs last-touch," "multi-touch," "which channel drives revenue," "what's my real CAC," "my dashboards disagree," "Google/Meta says X but GA says Y," "media mix model," "MMM," "incrementality," "geo lift," "holdout test," "how did you hear about us," "self-reported attribution," "dark social," or wants to instrument attribution themselves — "stitch my bookings to their source," "SavvyCal/Calendly attribution," "close the identify gap," "track conversions on a third-party domain," "first-party / self-hosted attribution." For event tracking setup and UTMs, see analytics. For ad-platform pixels/CAPI, see ads. For pipeline and CRM revenue reporting, see revops. For the AI-search attribution blind spot, see ai-seo.
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。
Nexus-JPF/note-companion☆ 8692026年10月13日 更新
When the user wants to set up, improve, or audit analytics tracking and measurement. Also use when the user mentions "set up tracking," "GA4," "Google Analytics," "conversion tracking," "event tracking," "UTM parameters," "tag manager," "GTM," "analytics implementation," "tracking plan," "how do I measure this," "track conversions," "Mixpanel," "Segment," "are my events firing," or "analytics isn't working." Use this whenever someone asks how to know if something is working or wants to measure marketing results. For choosing attribution models, comparing multi-touch/MMM/incrementality, or reconciling conflicting numbers across tools, see attribution. For A/B test measurement, see ab-testing.
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。
Nexus-JPF/note-companion☆ 8692026年10月13日 更新
Verification-first methodology for the Jurisdicción Especial para la Paz (JEP), Colombia's transitional justice court under the 2016 Acuerdo Final with FARC-EP. Citations are verified against jep.gov.co before use. Covers the 11 macrocasos (from Caso 01 secuestro through Caso 11 violencia sexual, including Caso 03 falsos positivos), the three sanction tiers (propias, alternativas, ordinarias), TOAR, and the SIVJRNR sister bodies (CEV, UBPD). Guards the key structural distinctions (Sala de Reconocimiento vs Tribunal para la Paz; comparecientes FARC-EP vs Fuerza Pública vs terceros civiles; Acto Legislativo 01/2017 vs Ley Estatutaria 1957/2019). Research aid, not legal advice.
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。
lawve-ai/awesome-legal-skills☆ 8642026年10月3日 更新
Act as experienced opposing counsel to attack, undermine, and expose weaknesses in a legal argument, submission, witness statement, or structured reasoning. Produces a six-part adversarial analysis: 1. A core theory of attack identifying the single most effective way to defeat the argument; 2. A reconstructed version of the opposing argument stripped of rhetoric to expose its fragility; 3. Primary lines of attack grouped by category (legal misstatement, evidential gaps, causation failures, internal inconsistency, over-reliance on assertion, procedural weakness); 4. An "if I were the judge" section showing how a sceptical tribunal would dismantle the argument; 5. Surgical strikes - 3 to 5 high-impact points ready for oral submissions; and 6. An analysis of what the argument is trying to hide. Written in formal, adversarial British English for a legally trained audience.
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。
lawve-ai/awesome-legal-skills☆ 8642026年10月3日 更新
Matter scoping across the full pre-execution arc — organise client data into a structured brief, capture the agreed baseline, or reconstruct scope mid-flight. Use when making sense of client information before a proposal, scoping a new matter, running a kickoff, defining scope, mapping stakeholders, or inheriting a matter mid-flight. Trigger on: 'make sense of this', 'structure this for the proposal', 'scope this matter', 'new matter', 'kickoff', 'what are we doing', 'who are the stakeholders', 'what does success look like', 'matter setup', 'intake', 'I've inherited this matter', 'organise this client data'.
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。
lawve-ai/awesome-legal-skills☆ 8642026年10月3日 更新
Searches the domestic courts of 122 jurisdictions — 153 databases, 49 automated — for extradition and arrest-warrant surrender decisions, each in its own language and vocabulary. Answers the question no commercial database does: how are OTHER executing states treating this requesting state, or this ground? Searching by requesting state localises its name per jurisdiction (AE becomes 'Emiratele Arabe Unite' in Romania, 'Emirati Arabi Uniti' in Italy), so the sweep finds what those courts actually wrote. Every hit passes a relevance gate; every search leaves a dated report, so the research is reconstructable months later. Use when asked what foreign courts have said about surrender to a given state, whether any European court has refused extradition on prison conditions, assurances or Article 3, for comparative extradition research, or to build a foreign-authority section of an extradition argument. Not for domestic case law of the user's own jurisdiction, and never a substitute for reading the judgment.
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。
lawve-ai/awesome-legal-skills☆ 8642026年10月3日 更新
Monthly CFO workflow for a company or agency — pull raw data from bank + payment processor + payroll + expense management, categorize and reconcile, compute end-of-month cash via transaction-sum method, update a scenario projector for forward forecasting, write the monthly snapshot report, surface decisions to leadership. Modes — monthly (default; the standing report), weekly (thin cash pulse), scenario (ad-hoc modeling in the projector), pickup (resume where the prior run left off). Anonymized team-scope sibling to personal-cfo (which handles personal household finances). Composes with company-brain (report gets stored + wiki-indexed there), toolify (wire company-specific data sources), loopify (schedule the monthly + weekly runs). Triggers on "/company-cfo," "/cfo," "monthly cash report," "do the CFO snapshot," "CFO monthly," "let's run CFO," "cash projection," "runway forecast," "monthly financials," "cash pulse."
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。
coreyhaines31/makerskills☆ 8602026年10月9日 更新
Expert Godot shader patterns for batch-safe hitflash, alpha-scissor foliage/dissolve, screenspace postFX, depth reconstruction, triplanar, and instance uniforms — not first-shader tutorials. Trigger on draw-call batching breaks, discard vs depth-prepass, foliage shadows, post-process quads, or world-position FX. Keywords: instance uniform, ALPHA_SCISSOR, hint_screen_texture, hint_depth_texture, global uniform, sampler2DArray, canvas_item, spatial, post-processing.
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。
thedivergentai/Game-Dev-Agentic-Skills☆ 8502026年10月14日 更新
Expert multiplayer for desync, rollback, dedicated --headless servers, interest culling, and bandwidth spikes: ENet/WebRTC choice, authority, secure RPCs, client prediction/reconcile, and adaptive sync. Trigger on rubber-banding, cheat-able clients, peer floods, late join, or profiler Network spikes — not only greenfield online games. Keywords: multiplayer, RPC, ENetMultiplayerPeer, MultiplayerSynchronizer, authority, client prediction, rollback, interest management, headless, desync.
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。
thedivergentai/Game-Dev-Agentic-Skills☆ 8502026年10月14日 更新
Expert Godot shader patterns for batch-safe hitflash, alpha-scissor foliage/dissolve, screenspace postFX, depth reconstruction, triplanar, and instance uniforms — not first-shader tutorials. Trigger on draw-call batching breaks, discard vs depth-prepass, foliage shadows, post-process quads, or world-position FX. Keywords: instance uniform, ALPHA_SCISSOR, hint_screen_texture, hint_depth_texture, global uniform, sampler2DArray, canvas_item, spatial, post-processing.
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。
thedivergentai/Game-Design-Agentic-Skills☆ 8502026年10月13日 更新
Expert multiplayer for desync, rollback, dedicated --headless servers, interest culling, and bandwidth spikes: ENet/WebRTC choice, authority, secure RPCs, client prediction/reconcile, and adaptive sync. Trigger on rubber-banding, cheat-able clients, peer floods, late join, or profiler Network spikes — not only greenfield online games. Keywords: multiplayer, RPC, ENetMultiplayerPeer, MultiplayerSynchronizer, authority, client prediction, rollback, interest management, headless, desync.
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。
thedivergentai/Game-Design-Agentic-Skills☆ 8502026年10月13日 更新
Net asset value (NAV) reconciliation and tie-out for Chinese funds and investment portfolios. Adapts the original nav-tieout skill for A-share holdings, Chinese fund accounting standards, and domestic custody arrangements. Triggers on "A股净值核对", "NAV计算", "NAV tie-out China", "基金净值", "net asset value [fund]", or "portfolio valuation [date]".
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。
jwangkun/claude-for-financial-services-cn☆ 8332026年9月14日 更新
When we combine gene-editing technology and sequencing technology, we need to reconstruct a lineage tree from alleles generated and calculate the similarity between each pair of groups. FindIndel() and IndelForm() function will help you align each read to reference sequence and generate scar form strings respectively. IndelIdents() function will help you to define a scar form for each cell or read. IndelPlot() function will help you to visualize the distribution of deletion and insertion. TagPro
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。
bioMate-AI/biomate-bioconductor-kb☆ 7962026年6月21日 更新
Query a user's TrailSnap photo library through scoped MCP tools to find photos, reconstruct memories, build person timelines, create evidence-backed narratives, or propose an album plan for explicit in-app approval. Use for the user's own TrailSnap library; never claim a proposal was executed or changed the library.
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。
LC044/TrailSnap☆ 7872026年10月13日 更新
Run the fixed 6-step session-opening sequence — pwd, read progress, git log, count remaining features, init.sh, smoke-test last feature — before touching any new work. The orientation ritual that lets fresh-context sessions reconstruct project state in under a minute.
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。
Archive228/loopkit☆ 7552026年7月15日 更新
Blameless post-mortem structure, incident timeline reconstruction, response evaluation, and organizational learning
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。
nWave-ai/nWave☆ 6172026年9月16日 更新
Acceptance test creation methodology for the DISTILL wave. Domain knowledge for the acceptance designer agent: port-to-port principle, prior wave reading, wave-decision reconciliation, graceful degradation, and document back-propagation.
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。
nWave-ai/nWave☆ 6172026年9月16日 更新
Runs once by hand on the first day and once a month after that, on the first weekday, light browser lane. On the first run it researches the business from its own public surfaces before asking anything, writes the strategy folder, seeds the pipeline, reconciles the schedule table, and registers the recurring jobs. On every monthly run it re-reads the evidence the kit produced, applies what changed to the files it owns, and carries every member written setting across verbatim. It holds every outbound action unless you released the channel, and it never enters a credential.
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。
markfulton/ai-employees☆ 6132026年10月10日 更新
Runs once by hand on the first day and once a month after that. On the first run it researches the business from its own public presence, writes the charter with a source and a date beside every conclusion, discovers the AI Employees actually installed on this machine within a bounded search, writes the map every other routine in this kit reads, seeds the priorities and the watchlist once, builds the fleet dashboard, and registers this Employee's own seven jobs. On every monthly run it re-runs discovery and reconciles the map against what is really there. It never writes into another Employee's folder, never registers a job it does not own, sends only where you released the channel, spends only where you released it, and never touches a credential.
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。
markfulton/ai-employees☆ 6132026年10月10日 更新
Runs once by hand on the first day and once a month after that. On the first run it researches the business from its own public surfaces before asking anything, reads the account structure once, writes the plan folder, seeds the board, creates the creative doctrine, builds the dashboard, and registers the recurring jobs. It asks about exactly two things, the monthly ceiling and the daily cap, because those are the two numbers that decide how much money can leave. On every monthly run it re reads the evidence, corrects what the ledgers prove wrong, and reconciles drift.
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。
markfulton/ai-employees☆ 6132026年10月10日 更新
Weekly, browser heavy, read only on every screen. Fixes a scoring window that neither double counts nor loses an hour, reads the member's search performance console and analytics property, verifies each range actually applied before reading a figure, reconciles every number against what this Employee published, writes the week's scoreboard and the short rolling state file every other routine reads, and files what it found as cards rather than doing the work itself. It types nothing on any screen, changes no setting, publishes nothing, and never touches a credential.
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。
markfulton/ai-employees☆ 6132026年10月10日 更新
Weekdays, file work only, no browser at all. Walks every AI Employee installed on this machine, reads each one's own run log strictly read only, classifies every routine as running, stopped loudly, stopped silently, or paused, ages the faults, folds the decision register, and writes the one short brief the member opens first. It never writes into another Employee's folder, sends only where you released the channel, spends only where you released it, and never touches a credential.
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。
markfulton/ai-employees☆ 6132026年10月10日 更新
Collect Amazon.com written product reviews at scale through Woot's public review AJAX route, retain every attempt and error log, reconcile partial runs, and normalize exact review text into auditable JSONL. Use for VOC, competitor review mining, low-star complaint analysis, listing research, or batch ASIN review acquisition without Amazon credentials. Amazon data layer of the bggg VOC suite (shared project folder; orchestrated by industry-orchestrator, reported by bggg-voc-report).
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。
binggandata/bggg-skills☆ 6062026年8月13日 更新
Reverse JavaScript-based custom DSL/VM interpreters, non-standard WASM-like runtimes, and risk-control engines. Use when analyzing IIFE or switch-based opcode dispatchers, extracting instruction tables, recovering bytecode semantics, capturing VM state at runtime, or reconstructing execution flow.
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。
coco-research/coco☆ 5992026年10月14日 更新