274 件 ・ 関連度順
概要と使いどころ
Deliberate session retrospective — look back over what you just did, distill the durable, reusable lessons (not session trivia), and write them to the learnings memory namespace, deduped against what is already stored. Use at the END of a meaningful chunk of work to capture high-signal lessons worth keeping long-term. The curated counterpart to moflo's passive session-continuity capture.
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。
Triage Linear or Jira backlogs and run bug sweeps via the Composio CLI. Bulk-fetch issues, deduplicate, relabel, reassign, and post summaries all from the shell.
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。
Prepare high-quality datasets for LLM fine-tuning with filtering, deduplication, augmentation, and RLHF data formatting. Activate on: fine-tuning data, training data curation, RLHF dataset, data quality filtering, SFT dataset. NOT for: model training infrastructure (ai-engineer), prompt engineering without fine-tuning (prompt-engineer).
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。
Align preprocessed CLIP-seq reads (eCLIP, iCLIP, iCLIP2, PAR-CLIP) to genome with STAR or bowtie2 using crosslink-preserving parameters, choosing between unique-mapper-only and multi-mapper-aware alignment for repeat-binding RBPs, deciding STAR vs HISAT2 memory trade-offs, and applying ENCODE-compatible filters. Use when turning preprocessed CLIP FASTQ into a deduplicated, MAPQ-filtered BAM ready for peak calling or crosslink-site detection.
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。
Guides AI agents through Senzing entity resolution workflows using the Senzing MCP server. Covers data mapping to Senzing format, SDK code generation (Python, Java, C#, Rust, TypeScript/Node.js), documentation search, error troubleshooting, sample data access, reporting and visualization, SDK setup guides, and V3-to-V4 migration. Use when working with entity resolution, record matching, record linkage, deduplication, Senzing SDK integration, data mapping for Senzing ingestion, or troubleshooting Senzing error codes. Also use when the user mentions matching records across data sources, finding duplicate entities, identity resolution, master data management, or needs to resolve who is who across datasets.
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。
Adaption AI SDK for synthetic data augmentation and dataset adaptation. Use when building data pipelines with the Adaption Python SDK, uploading datasets (local files, Hugging Face, Kaggle), running augmentation/adaptation jobs, configuring brand controls (hallucination mitigation, safety categories, length), recipe specifications (reasoning traces, deduplication, preference pairs, prompt rephrase), evaluating dataset quality, downloading results, or any workflow involving `pip install adaption`, `from adaption import Adaption`, Adaptive Data, or the adaptionlabs.ai API. Also trigger when the user mentions synthetic data generation for fine-tuning, dataset augmentation pipelines, DPO preference pair generation, or grounding-based hallucination reduction on training data.
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 optimizing AGENTS.md or copilot-instructions.md — deduplicates against .augment/ content, enforces line budgets, and focuses each file on its audience.
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。
Manage agent-skill lifecycles across local, global, project, Skill Hub, skills.sh, GitHub, plugin-cache, and system roots. Use when searching, recommending, installing, updating, upgrading, syncing, merging, auditing, deduplicating, cleaning, packaging, publishing, or validating skills; choosing project versus global scope; verifying upstream source, stars, or installs; or working with skill-upgrade, check_upstreams.ps1, sync-pull/push, junctions, skills-lock.json, or skill-upstreams.json. Do not use for ordinary software-package upgrades or non-skill file cleanup.
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。
Manage Agent Skills across Codex, Claude Code, local/global/project roots, Skill Hubs, GitHub, skills.sh, and managed plugin caches. Use when searching, installing, updating, upgrading, syncing, merging, auditing, deduplicating, cleaning, packaging, publishing, validating, resolving upstream sources, choosing runtime or scope, or working with skill-upgrade, check_upstreams.ps1, Claude Code plugins, skills-lock.json, or skill-upstreams.json. Do not use for ordinary software-package upgrades or non-skill file cleanup.
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 every Convex audit (authz, reviewer, advisor, insights) into one scored, deduped readiness report with an ordered fix plan — Lighthouse for your backend.
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 every Convex audit (authz, reviewer, advisor, insights) into one scored, deduped readiness report with an ordered fix plan — Lighthouse for your backend.
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。
Maintain a support docs pack — dedup, length budgets, and no splintering — and land changes as a reviewed pull request. Use when a support thread, or a hand-off from Support assist, surfaces a new resolution, a correction to an existing one, or a deployment quirk worth recording. Not for ordinary code changes.
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。
Extrahiert aus einem Chatverlauf (aktuelle Session oder Transkript-Dateien) einen wiederverwendbaren Skill — oder verbessert einen sehr ähnlichen existierenden Skill, statt ein Duplikat zu erzeugen. Nutze diesen Skill bei „mach daraus einen Skill", „das sollten wir als Skill festhalten", „extrahiere Skills aus diesem/alten Chatverläufen", „diese Arbeitsweise wiederverwendbar machen", oder bei `/skill-extract`. Deckt auch Bulk-Läufe über viele alte Transkripte ab (mit Datenreduktion über Subagenten). Für wiederkehrende AUTOMATISIERUNGEN (Cron/Schedule/Loop) stattdessen den Schwester-Skill workflow-extract nutzen.
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。
Ordnet freiwillig bereitgestellte Kontaktdaten datensparsam und erkennt mögliche Dubletten.
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。
Dual-layer PR review tool (Raven's Verdict). Runs adversarial cynical review and edge case hunter in parallel, merges and deduplicates findings into professional engineering output. Use when user asks to 'review a PR' and provides a PR url or id.
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。
Review content quality before anything is shown or sent (vault notes, outgoing drafts, dedup merges, service files) and return an explicit pass, fail or manual-review verdict. The counterpart of a post-build test gate: that one asks whether the build works, this one whether the writing is fit to show. Triggers: "/taste-check <path|text>", "/taste", "check this note".
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 an investor-outreach wave end to end: assemble the batch of targets, personalize pitches from real templates, send from the designated account, and log every touch in the CRM. Walks the exact checklist with rate limits and dedup against everyone already contacted. Triggers: "/notpeople-wave", "next outreach batch".
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。
Route a new rule, preference or policy edit into every home it belongs in (always-loaded canon, memory, the behavioral codex, a skill, a hook) and leave a trace in the always-loaded layer so parallel sessions pick it up on their own. Flow: dedup recall, classify by form, write to all homes, back up, report. Triggers: "/intake", "record this rule", "route this to its homes".
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。
Import any source into an Obsidian vault as well-linked atomic notes: social posts, Telegram HTML exports, ChatGPT JSON, voice-note transcripts, WhatsApp exports, Apple Notes, Notion dumps, pasted text, articles. Handles structure, frontmatter, provenance, dedup against existing notes and a closing RAG reindex. Triggers: "/obsidian-ingest", "import this into the vault", "file this".
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。
Watch a live lead funnel with a zero-token dispatcher and surface salient events as short advice: replied but no scheduling link, link sent with no booking in 24h, awaiting reply. Deduped so it never nags twice, and read-only. Triggers: "/cofounder-watch", "what does the cofounder see", "funnel signals".
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。
Operational guide for the NV oOS Model Foundry (Proposal 067) — the cluster fine-tuning flywheel. Phase 1 shipped: the Corpus Foundry (Pro addon, addons/pro/includes/model-foundry/) — consent-gated, deduplicated, PII-scrubbed corpus exporters (trajectory_v1, preference_v1, docs_v1) with deterministic holdout splits and R12 provenance manifests. Covers the governance contract, row schemas, output layout, filter seams, the registration pattern for foundry tool slices, how to add a new exporter, and the test/validation gates. Use when extending the Corpus Foundry, debugging corpus exports, wiring a new data source, or continuing Phases 2–6 (train-worker, registry/serving, eval gate, fleet sharing).
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。
Audit server-side paid-media measurement including server-side tag management, platform conversion APIs, event taxonomy, browser/server deduplication, consent, hashing, data quality, observability, and privacy. Use for server-side tracking, sGTM, server-side tagging, CAPI, Events API, event_id, pixel debugging, first-party measurement, or conversion data loss.
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。
Implements BLoC (v9.x) event-driven state management for Flutter with unidirectional data flow using the flutter_bloc package. Use when implementing Bloc/Cubit classes, mapping Events to States, consuming state with BlocBuilder/BlocListener/BlocConsumer, applying event transformers (restartable/droppable/sequential) for concurrency control, setting up BlocProvider/MultiBlocProvider DI, integrating Freezed for sealed union types and exhaustive pattern matching, or testing with blocTest. Ideal for enterprise apps requiring business logic separation, precise concurrency control (search debouncing, form deduplication), or event replay debugging.
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。