「post」の検索結果

Provider-independent governance workflow for verifying and correcting human- or model-generated video descriptions. Use for pre-caption critique and post-caption revision, aspect-by-aspect factual review, critique precision/recall/constructiveness, second-stage peer review, calibration, appeals, versioned triplets, provenance, and acceptance reporting; not for pixel/audio QA, accessibility captioning, model training, or creative shot direction.

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。

Provider-independent motion graphics direction for AI agents producing title sequences, lower thirds, explainer graphics, product UI overlays, social ads, kinetic typography, diagrams, data callouts, brand films, and video post. Use when planning, prompting, storyboarding, specifying, implementing, reviewing, or QAing motion graphics across live footage, generated video, UI capture, data visualization, brand systems, typography, accessibility, claim integrity, runtime handoff, and iteration.

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。

Apply security-conscious thinking when generating or modifying code. Enforces trust boundary awareness, input validation, injection prevention, secrets management, and defense-in-depth authorization. Use when generating code that handles user input, authentication, authorization, database queries, external APIs, or file operations, or when the user mentions 'security review', 'secure this', 'check for vulnerabilities', 'trust boundary', 'input validation', or 'OWASP'. Loaded automatically by the code-generating molecules (code-forge, refactor-safely, bug-fix). This skill governs the security posture of generated code -- not architecture (see architecture) and not code craft (see clean-code).

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。

Apply clean code principles when generating or modifying implementation code. Enforces function focus, naming clarity, complexity management, error handling, and self-documenting style. Use when the user mentions 'clean code', 'code quality', 'coding guidelines', or 'implementation quality'. Loaded automatically by the code-generating molecules (code-forge, refactor-safely, bug-fix). This skill governs the craft of writing individual code units -- not architecture (see architecture), not security posture (see secure-coding), not test structure (see test-quality), and not refactoring workflows (see refactor-safely).

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。

Detects differential alternative splicing between conditions using rMATS-turbo (binomial LRT on junction counts), leafcutter (Dirichlet-multinomial GLM on intron clusters), MAJIQ V3 deltapsi/HET (Bayesian posterior on LSVs), SUPPA2 (empirical-null on TPM-derived PSI), or Shiba (junction-imbalance-corrected, 2025 SOTA at low coverage). Reports FDR-corrected significance and delta PSI effect sizes. Tools differ in statistical model, annotation dependence, calibration regime, and replicate-count requirements. Use when comparing splicing patterns between treatment groups, tissues, or disease states.

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。

End-to-end post-GWAS causal inference pipeline orchestrating heritability partitioning, genetic correlation, Mendelian randomization with CHP-aware sensitivity (CAUSE / LHC-MR), colocalization, fine-mapping with SuSiE / FOCUS, mediation, TWAS triangulation, cis-pQTL drug-target MR, effector-gene prioritization (L2G / PoPS / cS2G), and GenomicSEM common-factor GWAS. Use when triangulating causal inference across multiple complementary methods, prioritizing tissues via stratified LDSC, nominating or de-risking drug targets, mapping a lead SNP to a candidate effector gene, modeling shared genetic architecture across correlated traits, or producing a STROBE-MR-compliant publication-grade evidence battery from GWAS summary statistics.

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。

Preprocess CLIP-seq reads (eCLIP, iCLIP, iCLIP2, iCLIP3, irCLIP, PAR-CLIP, FLASH) with protocol-specific UMI extraction, adapter trimming, length filtering, and post-alignment PCR-duplicate collapse. Use when raw CLIP FASTQ must be turned into deduplicated, crosslink-preserving BAM input for peak calling; choosing between two-pass and single-pass adapter trimming; deciding minimum read length; or mapping UMI patterns to specific eCLIP/iCLIP/iCLIP2/iCLIP3 library preps.

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。

Validate alignment quality with insert size distribution, proper pairing rates, GC bias, strand balance, and other post-alignment metrics. Use when verifying alignment data quality before variant calling or quantification.

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。

Designs Bayesian clinical trials including Phase I dose-finding (BOIN, CRM, EWOC, mTPI-2), meta-analytic-predictive (MAP) priors with robust mixtures for external data borrowing, EXNEX for basket trials, hierarchical models for safety AE (Berry-Berry), Bayesian platform trials (I-SPY 2, GBM AGILE, REMAP-CAP), and posterior probability stopping rules. Covers FDA Bayesian Devices Guidance (2010), FDA Bayesian Methodology in Drugs Draft (January 2026), BOIN Fit-for-Purpose qualification (December 2021), and Project Optimus dose-optimisation. Use when designing dose-finding studies, platform trials, or sensitivity analyses with informative priors.

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。

Run Bayesian phylogenetic analysis with MrBayes, BEAST2, RevBayes, and PhyloBayes including MCMC convergence diagnostics and model comparison. Use when needing posterior probability support, Bayesian model averaging, site-heterogeneous models for deep phylogenies, or formal model comparison via stepping-stone sampling.

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。

Research podcasts, episodes, and audio content by searching YouTube (where most podcasts crosspost), web sources, and transcript databases. Discover relevant shows, track guest appearances, and analyze topic coverage in the podcast ecosystem.

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。

Search discussions, track communities, analyze posts, and discover trends on Reddit through SandBase. Use when asked for Reddit research, community analysis, trending topics, discussion monitoring, content discovery, or audience insight beyond customer-focused research.

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。

Analyze sentiment in any text — reviews, social posts, feedback, or articles. Returns sentiment polarity (positive, negative, neutral), confidence score, and key phrases driving the sentiment. Useful for brand monitoring, customer feedback analysis, and content evaluation.

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。

Track hashtag performance across Instagram, TikTok, Twitter, and Xiaohongshu simultaneously. Monitors post volume, engagement rates, top contributors, and content patterns for campaign tracking, trend research, and community activation measurement.

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。

Analyze hiring patterns, job market demand, salary signals, and talent competition across LinkedIn and Apollo. Covers job posting analysis, company hiring velocity, role requirement trends, and competitive talent landscape 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。

Search companies, enrich profiles with firmographic data, find job postings, and track company news through Apollo. Covers company search, detailed enrichment (industry, size, funding, tech stack), hiring activity, and news monitoring for B2B sales intelligence.

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。

Analyze content performance across YouTube, TikTok, Instagram, and Twitter to identify what works. Compares engagement rates, format effectiveness, posting cadence impact, and audience response patterns across platforms for content strategy optimization.

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。

Internal publisher module for /codeck. Exports deck to PDF or PPTX with post-export QA. User-facing export requests should enter through /codeck; this skill defines the export behavior.

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。

Cross-agent self-inspection of your AI-agent stack. Audits skills, MCP servers, hooks, plugins, commands, credentials, and memory files across Claude Code, Codex, OpenClaw, and NanoClaw. Produces a structured inventory and narrative briefing with cross-ecosystem risk analysis. Use when the user asks to audit their own setup, check what they have installed, review their agent stack security posture, or understand cross-tool interactions. Use when a user has accumulated skills/plugins/MCP servers over time and wants visibility into their attack surface. Use after installing new skills or plugins. Do NOT use for vetting external code before install (that is repo-forensics). Do NOT use for incident response during active attacks. Do NOT use for fixing or patching vulnerabilities (forensify is read-only).

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。

Use when a devopsdays event that is already listed on the site has to be cancelled or postponed, and its pages need to stop advertising dates, registration, and sponsorship.

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。

Validate database integrity, test migrations forward and backward, verify schema constraints, manage seed data, detect migration drift, and identify query performance issues. Covers PostgreSQL, MySQL, MongoDB with Prisma, TypeORM, Drizzle, and SQLAlchemy, plus Testcontainers test databases. Use when: "database test," "migration test," "migration rollback," "rollback test," "data integrity," "SQL test," "schema validation," "seed data," "query performance," "Testcontainers." Not for: synthetic data generation/masking at scale — use test-data-management; Docker/IaC test-environment provisioning — use test-environments; SQL injection — use security-testing. Related: test-data-management, test-environments, security-testing, ci-cd-integration.

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。

Define, track, and act on QA metrics: test coverage percentage, flakiness rate, defect escape rate, MTTR, test execution time trends, automation ROI, quality gates, and SLAs for test suites. Includes metric formulas, realistic targets by company stage, and the action to take when each metric goes red. Use when: "QA metrics," "test metrics," "quality KPIs," "test health," "flakiness rate," "defect escape rate." Not for: building the dashboard UI (Allure/Grafana) — use qa-dashboard; measuring coverage gaps and mutation score — use coverage-analysis. Related: qa-dashboard, coverage-analysis, ci-cd-integration, release-readiness, quality-postmortem.

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。

Use production telemetry as INPUT to design new tests. Covers OpenTelemetry integration with tests, trace-based assertions, log-informed test creation, production-error analysis for coverage gaps, and telemetry-driven test prioritization. Use when: "trace-based testing," "design tests from logs," "OpenTelemetry assertions," "production errors point to test gaps," "telemetry-driven testing." Not for: safe rollout techniques (flags, canary) during release — use testing-in-production. Not for: scheduled post-deploy probes — use synthetic-monitoring. Not for: triaging CI failures — use ai-bug-triage. Related: testing-in-production, synthetic-monitoring, qa-metrics, ai-bug-triage.

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。

Test REST and GraphQL APIs with Playwright APIRequestContext, Supertest, or standalone HTTP clients. Covers schema validation with Zod 4/AJV, auth flow testing, CRUD lifecycle tests, error and header validation, pagination, and performance assertions. Use when: "API test," "endpoint test," "REST test," "GraphQL test," "schema validation," "Postman replacement." Not for: consumer-driven contract verification (Pact, broker) — use contract-testing; browser UI flows — use playwright-automation. Related: contract-testing, test-data-management, ci-cd-integration, playwright-automation.

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。