「event」の検索結果

Detects m6A modifications from Oxford Nanopore direct-RNA-seq (DRS) signal using m6Anet (multiple-instance-learning over DRACH 5-mer signal). Covers the upstream pipeline (Dorado/Guppy basecalling -> minimap2 map-ont -> nanopolish eventalign -> m6anet dataprep -> m6anet inference), per-site vs per-read probability including the mod_ratio stoichiometry column, the DRACH-only constraint, minimum-coverage thresholds (20-50 reads/site), multi-condition comparison via xPore/Nanocompore/ELIGOS, Dorado native modification calling (RNA004, 2024+), and the cDNA-vs-DRS distinction (cDNA Nanopore CANNOT detect modifications). Use when calling m6A from ONT DRS without immunoprecipitation, choosing m6Anet vs xPore vs Nanocompore vs ELIGOS vs Dorado native, interpreting probability_modified vs mod_ratio vs per-read probabilities, deciding between m6Anet (known DRACH sites) and Dorado/Remora (genome-wide screening), pinning RNA002 vs RNA004 chemistry and basecaller versions, or troubleshooting eventalign/dataprep failures.

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Detect, date, and contextualize whole-genome duplication (WGD / paleopolyploidy) events using wgd v2 (Chen et al 2024), KsRates (Sensalari 2022 substitution-rate-corrected Ks dating), DupGen_finder (Qiao 2019), MAPS (Li 2018 phylogenomic), POInT (Conant 2008 ordered-block), SLEDGe (2024 ML-based), Whale.jl (Bayesian DL+WGD), and synteny-anchored paranome construction. Use when identifying ancient polyploidy from Ks distributions and synteny block analysis, positioning WGD events relative to speciation, distinguishing tandem from segmental from WGD duplications, dating the 2R/3R vertebrate / fish / salmonid WGDs, building paranome and Ks-age mixture models, applying KsRates substitution-rate correction across lineages, or testing alternative biased-fractionation / dosage-balance models post-WGD.

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Reconcile gene trees against a species tree under probabilistic models of duplication, transfer, and loss (DTL) using ALE (Szöllősi 2013 amalgamated likelihood), GeneRax (Morel 2020 ML reconciliation), AleRax (Morel 2024 co-estimation), Whale.jl (Bayesian DL+WGD), RANGER-DTL 2 parsimony, NOTUNG, ecceTERA, and Treerecs. Use when inferring ancestral gene-family content, distinguishing duplication from horizontal transfer from differential loss, rooting deep species trees from gene-content signals (STRIDE / Williams 2017 ALE-rooting), counting DTL events per branch, refining noisy gene trees against a species tree, modeling WGD events jointly with DTL, or producing publication-grade gene-family histories for phylogenomic / comparative analyses.

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Recommend runtime and V2 scene management: run recommendation requests, manage recommend scenes and rules, and verify the deployed recommendation path.

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Guides Metronome usage-based billing integration decisions — event ingestion (single and batch, idempotency, billable metrics), contract design (rate cards, overrides, dimensional pricing, products), invoicing lifecycle (grace periods, finalization, Stripe sync), credit and commit management (prepaid, postpaid, thresholds, auto-recharge), and Stripe integration (arrears invoicing, tax providers, line item limits). Use when building, modifying, or reviewing any Metronome integration — including ingesting usage events, creating customers, contracts, or rate cards, designing billable metric group keys, managing credits and commits, configuring invoicing, syncing invoices with Stripe Billing, billing AI applications for token usage, setting up self-serve (PLG) pricing, reviewing customer health, commit burn, portfolios, or renewals, or migrating from Stripe Billing Meters to Metronome.

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AWS Lambda serverless functions for event-driven compute. Use when creating functions, configuring triggers, debugging invocations, optimizing cold starts, setting up event source mappings, or managing layers.

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Discover when you are most active and most productive with Claude Code by bucketing sessions and events into hour-of-day and day-of-week bins from their timestamps, then flagging peak versus low-output windows. Uses the session list, per-session events, and analytics daily trends. Use when planning a schedule or deciding when to do deep work versus lighter tasks.

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Audit hook delivery health from Agent Monitor data — balance PreToolUse vs PostToolUse (a gap means tools that started but never reported back), detect missing Stop/SubagentStop terminators (sessions/subagents that never closed), and check for stale ingestion (no recent events). Use when hooks look unreliable or events seem to be dropping.

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Produce a detailed report on APIError events from Agent Monitor data — counts over time, which sessions and models are affected, and the likely root cause (rate limits, overload/529, or context-window pressure) inferred from each event's summary and data payload. Use when API errors spike or when you need to explain why requests are failing.

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Compare two sessions side-by-side using Agent Monitor data — per-model token usage (input/output/cache_read/cache_write + compaction baselines), pricing engine cost breakdowns, workflow intelligence (complexity scores, tool flow transitions, subagent effectiveness), session metadata (thinking_blocks, turn_count, turn_duration_ms, usage_extras), and full event timelines with all 10+ event types.

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Quick dashboard health and status overview — checks the Agent Monitor API (port 4820), reports session/agent/event counts from /api/stats, confirms WebSocket connectivity, reads the redacted hook status returned by /api/settings/info, and shows data freshness (last event timestamp). Use to verify the monitoring system is operational.

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One-line summary of key Agent Monitor metrics — active sessions, total cost from the pricing engine, events today from daily_events, top tool from tool_usage, and current model from the most recent session. Use for a fast at-a-glance check without leaving the terminal.

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MANDATORY for every coding agent (Claude Code, Codex, or any other) — keep this repository's documentation in sync after any change to behavior, configuration, interfaces, events, schema, or features. Use automatically at the end of change-sets that alter an env var, event type, hook or state behavior, API, schema, WebSocket message, MCP tool, CLI command, or user-facing feature, and whenever the user asks to update documentation.

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Analyze Claude Code usage trends over time using the Agent Monitor's analytics API — daily session counts, daily event counts, token volumes by type, model distribution, tool usage rankings, and agent/event type distributions across 365-day retention windows.

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Diagnose Claude Code hook installation, delivery, and ingestion issues. Checks hook configuration, connectivity, event flow, and identifies common problems. Use when events are not appearing in the dashboard.

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Debug a specific session by inspecting its full event chain (PreToolUse, PostToolUse, Stop, SubagentStop, Compaction, APIError, TurnDuration, Notification events), agent hierarchy (recursive parent/child tree with subagent_type and depth), token usage with compaction baselines, workflow intelligence data (orchestration DAG, error propagation by depth), and session metadata (thinking_blocks, turn_count, total_turn_duration_ms).

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Use when structuring Unity 6.3 C# code: ScriptableObject data vs runtime state, events and services, inventory, health, save and load, Input System actions and key rebinding, async with Awaitable, assembly definitions, Enter Play Mode and domain reload, .meta files, Git, Smart Merge and LFS. Also when 'my save works in the Editor but not in the build', statics keep values on the second Play, events fire twice or never, an await runs after its object died, rebinds are lost on relaunch, a renamed class loses its data, a scene merge breaks.

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How to actually instrument product analytics correctly. Event taxonomy, property design, naming conventions, schema versioning, identity stitching, funnel design, retention cohorts, North Star metric selection, dashboard hygiene, instrumentation debt, and the failure modes that produce data nobody trusts. Triggers on product analytics setup, event taxonomy, tracking plan, instrumentation, schema versioning, North Star metric, retention cohorts, funnel design, naming conventions, instrument new feature, audit existing analytics, dashboard reconciliation, instrumentation debt, Mixpanel setup, Amplitude setup, PostHog setup, warehouse-native analytics. Also triggers when the team has data but cannot trust it, or when designing instrumentation for a new feature, or when auditing an existing setup that has drifted.

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Designing free-to-paid conversion flows for SaaS products. Trigger moments, paywall design, value demonstration, upsell vs downsell, win-back flows, churn prevention. Honest about paywall-everywhere (gates everything aggressively), free-forever-trap (no upgrade path surfaces), and value-triggered-upgrade (paywall surfaces at moments of demonstrated value) patterns. Triggers on upgrade flow, paywall, free-to-paid, freemium conversion, trial conversion, plan upgrade, subscription upgrade, win-back flow, churn prevention. Also triggers when free-to-paid conversion is low, when paywalls are blocking the wrong moments, or when upgrade flows are being scoped for the first time.

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End-to-end analytics implementation for web and SaaS: GA4, Google Tag Manager, event taxonomy, conversion tracking, and UTM strategy. Use when building a tracking plan, debugging missing events, setting up GTM, or auditing existing analytics.

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When the user wants to reduce churn, build cancellation flows, set up save offers, recover failed payments, or implement retention strategies. Also use when the user mentions 'churn,' 'cancel flow,' 'offboarding,' 'save offer,' 'dunning,' 'failed payment recovery,' 'win-back,' 'retention,' 'exit survey,' 'pause subscription,' 'involuntary churn,' 'people keep canceling,' 'churn rate is too high,' 'how do I keep users,' or 'customers are leaving.' Use this whenever someone is losing subscribers or wants to build systems to prevent it. For post-cancel win-back email sequences, see emails. For in-app upgrade paywalls, see paywalls.

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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.

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Expert patterns for input handling covering InputMap actions, InputEvent processing, controller support, rebinding, deadzones, and input buffering. Use when setting up player controls, implementing input systems, or adding gamepad/accessibility features. Keywords InputMap, InputEvent, gamepad, controller, rebinding, deadzone, input buffer.

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Expert blueprint for romance games and dating sims (Tokimeki Memorial, Monster Prom, Persona social links) focusing on affection systems, multi-stat relationships, dated events, and route branching. Use when building relationship-centric games, social simulations, or otome games. Keywords romance, dating sim, affection system, relationship stats, date events, character routes, love interest.

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