175 件 ・ 関連度順
概要と使いどころ
Set up a newsjack monitoring profile for a company so newsjack-detector can run on a schedule. Guides the user through company standing, topics, competitors, proof assets, spokespeople, RSS feed selection, optional X trend monitoring, and optional Slack delivery.
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。
Cheap, high-recall first-pass filter that removes obvious junk from a detector candidate pool before expensive story-origin research and PR judgment. Decides keep, monitor_only, or reject — never ranks, writes angles, verifies dates, or decides whether to pitch.
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 out which applicant tracking system a job uses from its application link, and give the formatting rules that system parses safely. Use when asked which ATS does this company use, will my CV get through the ATS, is my CV ATS friendly, or how should I format for Workday, Greenhouse, Lever or Taleo. Produces the detected system with the evidence, a parsing-safe formatting checklist, the file type to upload, and a check of a supplied CV against the rules.
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。
Scan support tickets, Slack channels, NPS scores, and usage patterns to flag accounts showing early churn indicators. Produces a weekly risk scorecard with severity tiers, root cause hypotheses, and suggested save plays per account. Designed for seed/Series A teams where the founder or a single CSM manages all accounts manually.
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。
Reads, inspects, and writes Flow Cytometry Standard (FCS) files from conventional, spectral, and mass cytometry (CyTOF), and parses FlowJo/Cytobank/Diva workspaces. Covers FCS 2.0/3.0/3.1/3.2 internals ($PnE linear-vs-log, $DATATYPE, $SPILLOVER vs SPILL vs $COMP, $TIMESTEP), channel/parameter metadata, the silent linearize/truncate defaults, and R (flowCore, flowWorkspace, CytoML) plus Python (FlowKit, readfcs) readers. Use when loading flow or mass cytometry data, mapping detector channels to antibodies, extracting the event matrix, choosing a reader, or bridging FCS to the scanpy/AnnData ecosystem before preprocessing.
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-only drift detector. Diffs SPEC.md against current code and reports violations grouped by severity. Writes nothing — suggests remedies via the spec or build skills but never invokes them. Triggers when the user asks to check drift, audit the spec, verify invariants, or ask whether code still matches the spec. Phrasings: "check drift", "audit the spec", "does the code still match §V", "check invariants", "spec vs 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。
Detect documentation drift against code changes, score staleness, validate API docs via AST parsing, and audit link integrity. Use when docs fall out of sync with code, preparing releases, running CI doc gates, or auditing doc accuracy.
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 patterns for porting desktop games to mobile including touch control schemes (virtual joystick, gesture detection), UI scaling for small screens, performance optimization for mobile GPUs, battery life management, and platform-specific features. Use when creating mobile ports or cross-platform mobile builds. Trigger keywords: TouchScreenButton, virtual_joystick, gesture_detector, InputEventScreenTouch, InputEventScreenDrag, mobile_optimization, battery_saving, adaptive_performance, MOBILE_ENABLED.
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-skill signal detector - finds entities or themes surfaced independently by 3+ different skill categories within 48h and surfaces them as high-confidence write opportunities
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。
Draft, audit, or minimally revise English- or Chinese-language academic prose to reduce formulaic, vacuous, mechanically repetitive, or process-leaking language while preserving claims, evidence strength, logical relations, manuscript-wide terminology identity, document-level pattern variation, and scholarly register. Use for papers, abstracts, grants, cover letters, and reviewer responses when the user asks to de-AI, humanize, audit AI-like phrasing, or rewrite text without changing meaning. English is primary; Chinese is supported. Not for detector evasion, policy circumvention, pure translation, non-academic copy, or adding facts, citations, examples, or author experiences that the source does not contain.
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。
Monitor existing content for ranking drops and trigger refresh workflows. Triggers on: "check for content decay", "which content needs updating", "content refresh", "ranking drops", "traffic decline", "stale content", "content audit", "what to refresh", "outdated content", "content performance check", "update old articles", "declining rankings", "content maintenance", "refresh priority list", "which articles are losing traffic", "SEO content audit".
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。
模糊去重工具。使用标准库相似度匹配检测并处理数据集中的近似重复记录，可发现非完全一致但高度相似的记录。 当用户提到模糊去重、近似重复检测、相似度去重、文本去重等需求时使用此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。
接入资源格式识别工具。读取单个文件或目录中的接入资源，识别文本、表格、文档、图像、HTML、数据或未知类型，输出带推荐处理路由的格式识别结果文件。 当用户提到格式识别、资源类型预判、采集入口分流、为文本/表格/文档/图像/HTML 选择后续处理路径等需求时使用此 skill。 即使用户没有明确说出"格式识别"，只要任务涉及在采集入口判断文件类型并分配推荐处理路由，就应该使用此 skill。 不负责读取正文内容、提取图像元信息、表格采集、文档解析、格式转换或实际执行后续处理。
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。
精确去重工具。使用pandas精确匹配检测并处理数据集中的完全重复记录，速度快、无额外依赖。 当用户提到精确去重、完全重复检测、数据去重等需求时使用此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。
Mine lost deal notes to identify recurring objection patterns. Create objection response playbooks from won deals.
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。
Remove the AI tells readers react to in an Instagram caption or carousel slide: 2026 vocabulary by density, reveal bridges, staccato stacks, stacked triads, performed sincerity, emoji storms; caps em dashes. Includes --mode audit (first-125 hook, length, hashtags, emoji, CTA, media) and --mode profile. Not for beating AI detectors (no edit reliably does). Not for writing from scratch (use ig-caption-writer or ig-carousel-planner). Keywords: humanize, de-AI caption, audit before posting.
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。
Pre-ship gate — runs detector, verifies brief and tokens, applies the 10-pass finish bar, ranks findings by feedback hierarchy. Use when the user wants to ship, merge, or finalize a surface and needs a verdict (READY / NOT READY / BLOCKED) before committing. Invoke when the user asks for finalize on their UI, or mentions 'finalize' alongside design / UI / frontend 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。
Medicinal chemistry filters for compound triage. Drug-likeness rules (Lipinski Ro5, Veber, Oprea, CNS, leadlike, REOS, Golden Triangle, Ro3), structural alerts (PAINS, NIBR, Lilly Demerits), chemical group detectors, complexity metrics, and filter composition query language. Built on RDKit/datamol. For hit-to-lead filtering, library design, ADMET pre-screening. For molecular I/O use rdkit-cheminformatics or datamol.
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。
Detect anomalies and outliers in construction data: unusual costs, schedule variances, productivity spikes. Statistical and ML-based detection methods.
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 AI-generated writing patterns in prose. Use when reviewing docs for slop, vague language, or identity leaks before publishing.
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 codebase bloat via dead code, duplication, complexity, and doc bloat scans. Use when codebase feels large or before a release.
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。
Detect friction signals; graduate patterns into rules. Use for session retrospectives.
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。
Mine lost deal notes to identify recurring objection patterns. Create objection response playbooks from won deals.
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。
Routes face-alignment installation, import checks, landmark-detection workflows, and detector-backend selection.
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。