「pe」の検索結果

Custom Notification Types for desktop/mobile push alerts from Flow or Apex: type creation, target channels, Messaging.CustomNotification invocation, recipient limits, bulk notification patterns. NOT for choosing channels, consent, or notification-fatigue policy — use admin/custom-notification-type-design. NOT for email alerts — use admin/email-templates-and-alerts. Trigger keywords: notiftype, notificationtypes directory, customNotifTypeName, customNotificationAction, setNotificationTypeId, targetPageRef, NotificationTypeConfig.

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Router for the 159 SfSkills `apex` skill packages. Apex and SOQL: triggers, Apex governor limits, async processing, OUTBOUND HTTP callouts, security enforcement, and test patterns. Owns calling an external API FROM Salesforce; salesforce-integration owns inbound. Generic nightly scheduling without naming code belongs to salesforce-flow. Codebase security review belongs to salesforce-security. NOT for SOSL — use salesforce-data. Use when the request mentions Apex, trigger, SOQL, Apex governor limit, batch, queueable, @future, schedulable, test class, CPU time, heap, with sharing, StripInaccessible, callout, HTTP callout, HttpRequest, call an external API, consume a REST API from Apex, Named Credential in Apex, HttpCalloutMock, Apex REST service. Finds and opens the exact skill package to read; it does not contain the guidance itself.

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Detect and install the Spec Kit `specify` CLI that every other speckit skill depends on. USE FOR: checking whether `specify` is installed/on PATH, installing it when missing, fixing "command not found: specify", confirming the CLI is new enough (>= 0.11). DO NOT USE FOR: upgrading an already-installed CLI to a newer release (use speckit-self) or verifying project tools (use speckit-check).

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。

Converts OpenAPI 3.0 JSON/YAML to TypeScript interfaces and type guards. This skill should be used when the user asks to generate types from OpenAPI, convert schema to TS, create API interfaces, or generate TypeScript types from an API specification.

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。

Corrects fluorophore spillover (conventional compensation) or spectral overlap (spectral unmixing) and applies variance-stabilizing transforms (logicle/biexponential, arcsinh, log) for flow and mass cytometry. Covers spillover-matrix estimation from single-stain controls, AutoSpill, the spillover spreading matrix and why panel design (not compensation) bounds resolution, compensate-then-transform ordering, and arcsinh cofactor choice (5 for CyTOF, ~150 for fluorescence, per-channel via flowVS). Use when correcting spectral overlap, preparing data for gating/clustering, choosing logicle vs arcsinh, deciding a cofactor, or distinguishing compensation from spectral unmixing.

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。

Annotates ChIP-seq peaks to genomic features, nearest genes, ENCODE candidate cis-regulatory elements (cCREs), and regulatory domains. Uses ChIPseeker (R), HOMER annotatePeaks.pl (CLI), pyranges (Python), GREAT/rGREAT (regulatory domain gene-set enrichment), ChIP-Enrich (locus-length-adjusted), ENCODE SCREEN cCRE classification (PLS/pELS/dELS/CA-CTCF/CA-H3K4me3), and ENCODE-rE2G for cell-type-specific enhancer-gene linking. Handles nearest-TSS vs host-gene ambiguity, promoter window definition, and feature priority. Use when assigning genomic context to peaks, linking enhancer peaks to target genes, classifying peaks against ENCODE cCRE registry, or running gene-set enrichment on peak-associated genes.

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Work up a patient with confirmed hypercalcemia using the PTH-dependent vs. PTH-independent algorithm — order the right second-tier tests (PTHrP, 25(OH)D, 1,25(OH)2D, SPEP/UPEP, urinary calcium/creatinine clearance ratio, TSH) to reach a diagnosis. Trigger when a clinician asks "what's causing this hypercalcemia", "how to work up high calcium", "what tests to order for hypercalcemia", "PTH is normal what next", "differential diagnosis of hypercalcemia", or shares a confirmed hypercalcemia and asks for the workup.

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。

Work up Malignancy-Associated Hypercalcemia (MAH) — distinguish humoral hypercalcemia of malignancy (HHM, PTHrP-driven), local osteolytic hypercalcemia, 1,25(OH)2D-mediated lymphoma hypercalcemia, ectopic PTH secretion, and multiple myeloma — and pick the right confirmatory tests and therapy direction. Trigger when a clinician asks "is this hypercalcemia from cancer", "PTHrP positive what now", "hypercalcemia in lung cancer / breast cancer / lymphoma / myeloma", "humoral hypercalcemia of malignancy", "MAH workup", or any hypercalcemia case with suppressed PTH and a known or suspected malignancy.

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Dev-only check that a drafted spec for THIS baseline repo won't ship dev-tree references to consumer installs. Catches three failure modes — shipped SKILL.md prose that references paths under `src/`, `tests/`, `scripts/`, `obj/` as runtime invocations (in ```bash fences``` OR `inline backticks`, plus shipped `.mjs`/`.js`/`.sh`/`.py` helper-file imports); new Python helpers added under `.claude/skills/<slug>/` (shipped helpers must be `.sh` or `.mjs`/`.js` going forward); and imports of modules that aren't in `obj/template/.claude/manifest.json` (consumer won't have the file). The aggregate scanner (`scan-shipped-skills.mjs`) walks only baseline-owned skill dirs (via `owner: baseline` frontmatter) at top level — `references/` and other subdirs are documentation, not runtime. BLOCKER findings hard-block implementation entry; ADVISORY surfaces but doesn't block. Read-only — surfaces a punch list; maintainer edits the spec and re-runs until CLEAN.

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。

Expert-level spectroscopy knowledge. Use when working with NMR, IR, Raman, UV-Vis, mass spectrometry, fluorescence, X-ray, electron spectroscopy, or any spectroscopic technique for structure determination or chemical analysis. Also use when the user mentions 'NMR spectroscopy', 'chemical shift', 'coupling constant', 'IR absorption', 'Raman scattering', 'UV-Vis absorption', 'fluorescence', 'XPS', 'EPR', 'mass spectrum', 'fragmentation', or 'spectral interpretation'.

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。

Resolve, validate, and audit manuscript integrity and applicable requirements for academic manuscripts and paper artifacts. Use when Codex needs to determine active paper rules from manuscript state, paper type, venue, submission stage, or workflow mode; lint a LaTeX paper project; assess submission readiness; create or update a paper policy profile; explain why a rule is active; or validate the paper-policy registries. Do not use as the primary skill for prose drafting, peer review, rebuttal writing, citation discovery, or figure/table creation.

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。

4人の異なる専門家ペルソナ（20年ベテランエンジニア、TDDエキスパート、Clean Codeエキスパート、バグハンター）で ソースコードを批判的にレビューするスキル。設計判断、テスト容易性、可読性、バグ検出の観点から コードの問題を検出し、改善提案を行う。Python/JavaScriptに対しては追加のチェックポイントを適用。 バグハンターは状態遷移、例外パス、依存関係、非同期競合に特化し、本番環境での問題を事前に検出する。 Use when reviewing source code from multiple expert perspectives to find design flaws, testability issues, code quality problems, and runtime bugs. Triggers: "critical code review", "multi-persona code review", "expert code review", "code quality assessment", "find bugs".

エラーや例外シナリオを顧客体験(CX)の観点で体系的に分析し、改善優先度を付ける スキル。6軸評価（影響度・頻度・復旧容易性・メッセージ品質・感情的影響・ ビジネスコスト）でスコアリングし、Impact vs Effort マトリクスで改善施策を 優先順位付けする。Use when analyzing error scenarios from customer experience perspective, evaluating error message quality, prioritizing error UX improvements, or creating CX-focused error analysis reports. Triggers: "CXエラー分析", "error experience", "エラーUX改善", "customer experience error", "エラーメッセージ品質", "error scenario analysis", "顧客体験エラー評価"

Marketing analytics and data-driven optimization for B2B SaaS campaigns. Use this skill when analyzing marketing performance, optimizing conversion rates, running A/B tests, conducting customer research, creating marketing dashboards, building attribution models, analyzing funnel metrics, or storytelling with data. Also triggers on: marketing ops, performance analytics, CRO, A/B testing, data storytelling, customer insights, tracking plan, event taxonomy, UTM taxonomy, GA4 audit, consent mode, instrumentation contract, sample size calculation, minimum detectable effect, test duration, not enough traffic to A/B test, statistical significance, Bayesian vs frequentist, sample ratio mismatch, experiment feasibility, martech stack, marketing tech stack audit, tool consolidation, build vs buy, vendor evaluation, shadow IT tools, ESP/CRM/platform migration, switching cost, cutover plan, suppression list migration, data portability, customer interviews, survey design, sampling frame, non-response bias, how many people should I interview, thematic saturation, voice of customer, jobs-to-be-done, buyer persona research, is this finding real, data enrichment, which enrichment provider should we buy, waterfall enrichment, contact data quality, match rate, our list data is bad, email verification, catch-all domain, accept-all, bounce rate from bad data, B2B data decay, how often should we re-verify contacts, ZoomInfo vs Apollo vs Clearbit evaluation, cost per usable record, where did this list come from, GDPR Article 14 notice, purchased list compliance, suppression screening, TAM list building, demand planning, marketing plan, how many leads do we need, what pipeline target should marketing carry, funnel model, top-down vs bottom-up plan, plan of record, annual marketing planning, quarterly planning, pipeline coverage we have to create, sales cycle lag, our leads cannot close this quarter, carry-in pipeline, scenario planning, conservative moderate aggressive forecast, stretch target, reforecast, re-forecast triggers, assumption register, capacity ceiling, addressable audience ceiling, marginal cost per lead, blended CPL is wrong, we missed plan and nobody knows why.

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。

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. Also triggers on: 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.

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 working with Aws Codepipeline — aWS CodePipeline CI/CD pipeline management and execution analysis. Covers pipeline inventory, stage and action status, execution history, pipeline triggers, artifact stores, and action type configurations. Use when inspecting pipeline health, debugging failed stages, reviewing execution history, or auditing pipeline configurations.

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 working with Aws Data Pipeline — aWS Data Pipeline workflow management and execution analysis. Covers pipeline inventory, pipeline definitions, execution status, object status, task runner health, and pipeline scheduling. Use when inspecting data pipeline health, debugging failed executions, reviewing pipeline definitions, or auditing pipeline schedules.

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。

OpenCode | The open source AI coding agent — What is OpenCode? OpenCode is an open source agent that helps you write code in your terminal, IDE, or de

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。

Systematic strategic planning framework for philosophy and interdisciplinary academic papers targeting preprint platforms (PhilArchive, arXiv, PhilSci-Archive). Use when users want to: (1) plan a paper on a specific topic, (2) identify research gaps and assess originality, (3) develop optimized paper outlines, (4) prepare for preprint submission, or (5) understand platform requirements and writing standards. Triggered by phrases like 'plan a paper on,' 'help me design a paper about,' 'identify research gaps in,' 'is this idea original,' or when users need structured research planning. The skill guides through three phases: Platform Analysis (identifying target venue and studying sample papers), Theoretical Framework (AI-driven literature search and gap identification), and Outline Optimization (structured design with reviewer-perspective self-assessment). Each phase includes quality evaluation standards and validation checkpoints.

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Guide for diagnosing and improving MSBuild project evaluation performance. Only activate in MSBuild/.NET build context. USE FOR: builds slow before any compilation starts, high evaluation time in binlog analysis, expensive glob patterns walking large directories (node_modules, .git, bin/obj), deep import chains (>20 levels), preprocessed output >10K lines indicating heavy evaluation, property functions with file I/O ($([System.IO.File]::ReadAllText(...))), multiple evaluations per project. Covers the 5 MSBuild evaluation phases, glob optimization via DefaultItemExcludes, import chain analysis with /pp preprocessing. DO NOT USE FOR: compilation-time slowness (use build-perf-diagnostics), incremental build issues (use incremental-build), non-MSBuild build systems. INVOKES: binlog MCP server tools (evaluations, evaluation_global_properties, evaluation_properties, imports, properties); falls back to dotnet msbuild -pp:full.xml for preprocessing, /clp:PerformanceSummary.

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。

Nest.js framework expert specializing in module architecture, dependency injection, middleware, guards, interceptors, testing with Jest/Supertest, TypeORM/Mongoose integration, and Passport.js authentication. Use PROACTIVELY for any Nest.js application issues including architecture decisions, testing strategies, performance optimization, or debugging complex dependency injection problems. If a specialized expert is a better fit, I will recommend switching and stop.

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Orchestrates an end-to-end immune-repertoire pipeline from FASTQ to clonotypes, diversity, overlap, somatic hypermutation and lineages, routing on two forks. Use when deciding bulk vs single-cell (bulk amplicon/RNA-seq -> MiXCR analyze preset -> VDJtools/immunarch depth-normalized diversity and overlap -> figures; 10x paired VDJ -> MiXCR 10x preset or Cell Ranger -> scirpy gene-expression integration, chain QC, clonotype clusters); and TCR vs BCR (TCR -> exact CDR3-nt+V/J clonotypes, VDJtools diversity is fine; BCR -> somatic hypermutation makes exact clonotypes wrong -> Immcantation distToNearest/findThreshold clonal clustering, germline reconstruction, SHM, Dowser lineages); selecting the MiXCR 4.x preset by chemistry and activating its license; downsampling to equal depth before comparing diversity or overlap; and optionally annotating antigen specificity.

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。

Orchestrates an end-to-end MeRIP-seq / m6A-seq analysis from raw FASTQ to differential m6A peak calls and metagene plots, chaining fastp adapter trimming, STAR splice-aware alignment (NO deduplication for non-UMI MeRIP), deepTools replicate-concordance + IP-enrichment QC, PreSeq saturation curves, exomePeak2 (transcript-aware Poisson GLM) peak calling, optional MACS3 broad-peak cross-check, DRACH motif confirmation as a sanity check (NOT a per-peak filter), exomePeak2 differential calling via the four-BAM-vector interface (bam_ip + bam_input control; bam_treated_ip + bam_treated_input treatment), ChIPseeker annotation, and the canonical Guitar metagene with stop-codon enrichment as the biological QC anchor. Use when running a complete MeRIP analysis from raw reads, when chaining the constituent epitranscriptomics skills (merip-preprocessing -> m6a-peak-calling -> m6a-differential -> modification-visualization), or when wrapping the pipeline in Snakemake / Nextflow.

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。

The live fieldwork layer for psycho-logic — go look at the actual target market NOW instead of reasoning from your training-data stereotype of it. Use when a psycho-logic move needs grounding in a specific place: the user asks 'what do competitors in [region/country] actually do', 'what's the real price band / norm here', 'how do local leaders position themselves', 'research this market before we localise', 'what signals trust to buyers in X', or is about to launch/adapt in a market you haven't studied. Runs structured web research in the local language — local competitors and their signals, price bands, category conventions, review/trust sources, local terminology, taboos and regulations — and synthesises a compact perception profile the four moves consume. Inspired by Rory Sutherland's *Alchemy*. Routed to from psycho-logic; pair with cultural-context (the lens that tells you what to look for). 日本語・中文の相談（「現地の実態を調べて」「调研当地市场」）にも使う。