821 件 ・ 関連度順
概要と使いどころ
Converts hunt findings into portable Sigma detection rules: choosing the right logsource, expressing robust selection/filter logic, setting level and ATT&CK tags, and validating before converting to a SIEM query. Activates for requests to write a Sigma rule, convert a hunt to a detection, or create portable SIEM detection logic.
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Use when a task needs the judgment of an Art Therapist — matching art media to a client's regulation capacity via the Expressive Therapies Continuum, scoring a standardized directive (PPAT, KFD, DAP) with a validated instrument like FEATS as part of assessment, deciding between a directive and open-studio session structure, navigating informed consent and disposition for client-made artwork, or distinguishing an art-as-therapy approach from an art-psychotherapy approach for a given client.
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Use when a task needs the judgment of a Bioinformatics Scientist — designing a differential-expression or GWAS analysis with correct multiple-testing correction, calling and triaging variants from NGS data using genotype-likelihood confidence rather than raw allele counts, interpreting a BLAST/DIAMOND homology search, choosing or building a genomics pipeline (aligner, caller, normalization method) for a specific data-generating process, or judging whether a computational-biology analysis's statistical design actually supports the biological claim being made. Distinct from a bioinformatics-technician (executes and QC-gates an established pipeline someone else designed) and a data-scientist (general product/experimentation judgment, not genomics-specific statistics) — this role owns which method and statistical model a genomics question requires, and why.
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Assess the scientific integrity and trustworthiness of publications before relying on their findings. Use this skill whenever evaluating a paper for a workflow, citing a study, building an analysis on published methods, or when a user asks about the reliability of a study. Checks for formal retractions, corrections, expressions of concern, and — critically — informal contradictions where subsequent studies failed to reproduce key findings. Integrates with PubMed, bioRxiv, and Consensus to provide a trust assessment. Use this skill for ANY publication evaluation, retraction checking, author reliability assessment, or when a user says "can I trust this paper", "is this study reliable", "has this been refuted", or "check this publication".
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Integrate multiple ENCODE data types (RNA-seq, ATAC-seq, Histone ChIP-seq, TF ChIP-seq) for a tissue/cell type to build a comprehensive regulatory landscape. Use when the user wants to answer "what are the enhancers, promoters, and regulatory elements active in my tissue, and which transcription factors control them?" by layering expression, chromatin accessibility, histone marks, and TF binding data. Follows the Mawla et al. 2023 framework for cross-assay integration of islet cell type-specific data. Handles chromatin state annotation (ChromHMM), enhancer-gene linkage, TF motif enrichment, and cell type-specific regulatory element identification. Use for ANY multi-omic analysis, enhancer discovery, regulatory network construction, or epigenomic characterization using ENCODE data.
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Use when the user wants to transact on any Volcengine commercial product — purchase/provision it, ask what it costs, or unsubscribe from it. Covers three actions: buy (purchase, subscribe, provision, open, place an order; Chinese "开通 / 购买 / 下单 / 买 / 售卖 / 订购"), price (how much does it cost, quote, billing rules, estimated spend; Chinese "多少钱 / 价格 / 报价 / 费用 / 怎么收费 / 如何计费 / 预估费用"), and unsubscribe (cancel a subscription, refund a prepaid instance; Chinese "退订 / 退款 / 取消订阅"). Trigger even when the user does not mention "sale" but expresses a clear purchase, pricing, or cancellation intent toward a Volcengine product. Only handles these three transaction actions; anything outside them is out of scope.
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Type design analysis — encapsulation, invariant expression, usefulness, and enforcement.
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。
Read, write, and debug cron expressions with field reference, scheduling logic, and common patterns.
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。
Design memorable characters with silhouette, personality, expression sheets, and turnarounds.
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。
Bulk RNA-seq differential expression — experimental design, count modeling with DESeq2/edgeR, and enrichment.
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。
Measuring emotion from behavior and physiology — facial expression, voice, EDA, and self-report 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。
Generate OpenAPI 3.1 documentation from your API codebase. Auto-detects Express, Fastify, NestJS, Django, FastAPI, Flask, Rails, Spring, Go, and more. Triggers: you need API documentation, OpenAPI spec, Swagger docs, endpoint reference, or REST API docs.
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Establish durable brand and voice context for cross-skill consumption. Generates BRAND.md (audience, positioning, do/don't editorial rules, taboo phrases, competitor differentiation) and VOICE.md (existing persona JSON re-expressed as readable prose), both written to the project root. When present, the blog orchestrator auto-loads these files for write, rewrite, brief, outline, calendar, and strategy workflows. Pairs with blog-persona, which manages the structured persona JSON. Use when user says "blog brand", "create brand context", "brand voice doc", "BRAND.md", "VOICE.md", "establish editorial brand", "brand guidelines for blog".
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Generates valid Cloud Monitoring ListTimeSeries requests and aggregation specifications from metric descriptors and resource parameters. Use when asked to create, generate, format, or build ListTimeSeries requests, JSON payloads, filter expressions, or aligner/reducer aggregations for Cloud Monitoring metrics and charts. Don't use for metric discovery or metric selection.
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Always use this skill before claiming any work is done, fixed, passing, or complete — even if it seems obvious. Also use when receiving code review feedback from any source (human or automated), when finishing a task or major feature, before committing or creating a PR, or when about to express satisfaction with work. Covers three practices: receiving feedback with technical rigor (no performative agreement), triggering code review via /code-review command or cook/fix pipelines, and verification gates (run the command, read the output, then make the claim). Never skip — the cost of false completion claims is higher than the cost of verifying. References: code-review-reception.md, requesting-code-review.md, verification-before-completion.md.
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 designing, reviewing, or troubleshooting Salesforce formula fields. Triggers: 'formula field', 'cross-object formula', 'null handling', 'compile size', 'HYPERLINK', 'IMAGE', 'why is formula slow', 'formulaTreatBlanksAs', 'BlankAsZero', 'blank field handling', 'field-meta.xml formula', 'CustomField formula deploy', 'formula returns blank', 'formula field read-only on data load'. NOT for a formula field slowing a SOQL query or blocking an index — use apex/formula-field-performance-and-limits. NOT for Formula resources inside a Flow — use flow/flow-formula-and-expression-patterns.
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Use this skill when designing or building CRM Analytics Data Prep recipes — including node selection, join patterns, bucket field configuration, formula expressions, and scheduling. Triggers: 'build a recipe', 'join datasets in analytics', 'bucket a measure field', 'schedule a recipe', 'data prep transformation'. NOT for dataflow JSON and its node types — use admin/analytics-dataflow-development. NOT for tuning a slow or oversized dataset — use data/analytics-dataset-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。
Use this skill when building, debugging, or optimizing CRM Analytics dataflows — defining node types (sfdcDigest, Append, Augment, computeExpression, computeRelative, Flatten, dim2mea, sfdcRegister), scheduling runs, handling run failures, and tuning performance. NOT for doing the same transformation in a Data Prep recipe — use admin/analytics-recipe-design. NOT for dataset field types, refresh schedules, or row limits — use admin/analytics-dataset-management.
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 monitoring, diagnosing, or managing Batch Apex, Scheduled Apex, Queueable, and Flow scheduled jobs: Setup > Apex Jobs, AsyncApexJob queries, concurrent limits, failure detection, and notification patterns. NOT for writing the Batch or Schedulable class itself — use apex/batch-apex-patterns or apex/apex-scheduled-jobs. NOT for BatchApexErrorEvent alerting in code — use apex/scheduled-apex-failure-detection-and-monitoring. Trigger keywords: Setup > Scheduled Jobs, Apex Flex Queue, CronTrigger, CronJobDetail, FlowInterview, System.abortJob, System.schedule, CRON expression, Holding status, BLOCKED state, reschedule after sandbox refresh, scheduled job runbook.
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 enabling, configuring, or monitoring Change Data Capture (CDC) entity selection, channel enrichment, and delivery usage limits from an admin perspective. Covers the PlatformEventChannel and PlatformEventChannelMember metadata, the standard ChangeEvents channel, custom __chn data channels, enrichedFields, filterExpression, destructive deselection, and PlatformEventUsageMetric / EventBusSubscriber monitoring. Trigger keywords: change data capture, CDC, entity selection, change event, platform event channel, channel member, enrichment, event delivery allocation. NOT for writing an Apex change-event trigger — use apex/change-data-capture-apex. NOT for subscribing an external system over Pub/Sub or CometD — use integration/change-data-capture-integration.
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Orchestrate AI coding agents (Claude Code, Codex, OpenCode) in isolated sandboxes using the @ai-hero/sandcastle SDK. Use when the user needs to (1) run agents AFK in Docker/Podman containers, (2) build multi-agent pipelines with plan-execute-review patterns, (3) run parallel agents on separate worktrees, (4) create iterative agent loops with maxIterations, (5) extract structured output from agent runs, (6) set up sandcastle in a new or existing project, or (7) write prompt files with template args and shell expressions.
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Orchestrate work as a cyclic directed graph of subagent-executed nodes with transition criteria on edges, budgeted cycles, and per-node gates (runtime verification, metric, or artifact). Use when the user says "workgraph", "run this as a graph", "graph this work", or when a goal has parallel branches, feedback loops, or mixed gate types that a linear loop cannot express. Every node is sized to a 64k context budget, so small goals run as a two-node do/verify graph and large goals scale out without caps. For clock-driven or metric-driven single loops, timeboxed-iterating and autoresearch remain lighter.
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。
Firmware development for the 40-pin ESP32-S3-WROOM-1 camera board — the Freenove ESP32-S3-WROOM (FNK0085) and the AliExpress "ESP32-S3 CAM" / "ESP32-S3-WROOM N16R8 CAM" clones that copy its header: 20 pins a side, a 24-pin DVP camera FPC connector for an OV2640/OV3660, an on-board microSD slot on the SDMMC bus, a WS2812, two USB-C sockets (CH343 bridge and native USB), ESP32-S3-WROOM-1-N8R8 or N16R8 with 8 MB octal PSRAM. Use when working on this board or any ESP32-S3 DVP camera board: project setup, platformio.ini, the qio_opi PSRAM memory type, camera and SD_MMC pin maps, esp_camera_init failures, PSRAM not found, frame buffer allocation, SD card mount failures, which GPIOs are left once the camera is wired, strapping pins, ADC1/ADC2, flashing over the two USB ports, BOOT/RESET recovery, brownouts, or debugging why the camera, the card or the board does not work.
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。
Helps users discover and install agent skills when they ask questions like "how do I do X", "find a skill for X", "is there a skill that can...", or express interest in extending capabilities. This skill should be used when the user is looking for functionality that might exist as an installable skill.
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。