4,044 件 ・ 関連度順
概要と使いどころ
Semantically search past Claude Code sessions to recall commands, solutions, and context from prior conversations. TRIGGER on 'remember when', 'last time', 'we did this before', 'how did we', or /woz-recall.
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。
Med-sector overview across med.medicines_biotech and med.medical_devices with med trends, catalysts, FDA-decision context, and a cross-sector ripple map (quantified sign/magnitude per name). Use to frame any biotech/pharma/device analysis before diving into a single name.
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。
Vaccine catalyst analysis across the two-gate path: CBER BLA review and the ACIP recommendation gate that turns FDA approval into commercial availability. Lot release, procurement milestones, pediatric bridging, and healthy-population efficacy context — dated, verified, and sized per event.
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。
Med-adapted recent-quarter review: last print financials, pipeline-milestone awareness, and FDA-event context — reads the quarter through the med lens (milestones moved, runway, regulatory updates) rather than generic financials alone.
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 production workflow for recutting long talking-head, podcast, interview, webinar, panel, lecture, livestream, founder call, or customer-call footage into short clips, highlight reels, trailers, audiograms, captioned vertical videos, and social cutdowns. Use when an agent must ingest source recordings, transcribe and diarize speakers, select quotes without misrepresentation, preserve context, handle consent/rights/disclosures, clean jump cuts and audio, add captions, graphics, lower thirds, b-roll, platform variants, synthetic-media boundaries, review packets, delivery specs, and recut QA.
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。
Restructure existing code safely without changing externally observable behavior. Composes context, design, architecture, code quality, and testing guardrails into a characterization-first refactoring workflow. Use when the user says 'refactor this', 'clean this up', 'untangle this module', 'move this to the right layer', 'simplify this code', or 'improve this structure'.
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 enhancement pipeline for an existing Lattice skill — rewrites a molecule or atom to modern-capable-model grade: restores degraded grammar, deduplicates, hardens gates and branching to one-unambiguous-action precision, verifies zero behavioral loss against a pre-capture diff, then runs the combined QA gate (skill-review, skill-tighten, skill-validate) and an independent fresh-context verifier, fixing everything found. Consumer-first: optimized for first-time open-source users on fresh repos with minimal .lattice/ setup, running capable models. Use when the user says 'enhance this skill', 'upgrade this molecule', 'modernize this skill', 'optimize this skill', 'make this skill production grade', 'full enhancement', 'polish this molecule like design-blueprint', or names a molecule/atom to overhaul. For gap-finding only use skill-review; for conventions only use skill-validate — this skill runs the whole loop end to end.
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。
Investigate, reproduce, and safely fix a bug with regression protection. Composes context, diagnosis, architecture, code quality, and testing guardrails into a reproduce-first repair workflow. Use when the user says 'fix this bug', 'debug this', 'investigate this failure', 'patch this regression', 'repair this issue', or 'why is this broken'.
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。
Load project-specific context -- tech stack, architecture overview, directory layout, trusted sources, and conventions -- so that all skills operate with awareness of what this project actually is. Use when a knowledge base document exists, or when the user asks about the project's tech stack, architecture, conventions, framework, directory layout, or says 'tell me about this project', 'what are we using?', 'what's our stack?', or 'what framework is this?'. Use the knowledge-priming-refiner to create a knowledge base document.
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 implementation code from an approved design blueprint or verbal requirements. Composes context anchoring, architecture, clean code, DDD, security, and test quality into an inside-out implementation workflow. Use when moving from design to code, implementing approved contracts, or when the user says 'implement', 'code this', 'build it', 'forge the code', or 'generate the 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。
Use when the user wants to design, rewrite, refine, or vary emotional acting prompts for live-action AI video characters. Translate abstract emotions, dialogue, subtext, and scene context into concise, observable, temporally ordered micro-performance directions. Preserve the user's existing character, scene, camera, and dialogue requirements unless they explicitly ask to change them. Do not use for general story writing, shot design, action choreography, or visual asset design when emotional performance is not the main task.
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。
Identify differentially accessible chromatin regions across conditions using DiffBind, csaw, DESeq2, or edgeR. Use when comparing ATAC-seq accessibility between treatment groups, choosing between consensus-peak vs sliding-window approaches, picking the correct normalization (full library vs reads-in-peaks), correcting batch with SVA/RUVseq, or interpreting log2FC and FDR thresholds in a chromatin context.
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。
Build tissue and condition-specific metabolic models using GIMME, iMAT, and INIT algorithms with expression data constraints. Create models that reflect cell-type specific metabolism. Use when building tissue-specific metabolic models or integrating transcriptomics with FBA.
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 and track antimicrobial resistance genes using AMRFinderPlus and ResFinder with epidemiological context. Monitor resistance trends and identify emerging resistance patterns. Use when screening genomes for AMR genes or tracking resistance in surveillance programs.
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。
Annotate CLIP-seq peaks or crosslink sites to RNA features (5'UTR, CDS, 3'UTR, intron, splice junction, snoRNA, tRNA, ncRNA, repeat elements) with ChIPseeker, RCAS, RBP-Maps (Yeo splicing regulatory maps), and bedtools, applying feature-priority hierarchies, transcript-context resolution, and metagene aggregation. Use when characterizing where in transcripts an RBP binds, comparing peak distribution across regions, generating splicing-regulatory maps relative to alternative-splicing events, or distinguishing exonic vs intronic vs UTR binding.
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。
Workflow for constraint-based metabolic modeling, context-specific models, gene essentiality, and systems-level 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。
Identify direct miRNA-target interactions from AGO HITS-CLIP, AGO-CLEAR-CLIP (chimeric reads), HEAP (Halo-Ago2 mouse), chimeric eCLIP / miR-eCLIP (deep miRNA-target profiling), or CLASH using chimeric-read processing pipelines, seed-pairing analysis, and 3' auxiliary pairing rules. Use when distinguishing direct miRNA targets from indirect, integrating CLIP-derived target maps with TargetScan / miRDB / DIANA predictions, applying canonical 7mer-8mer seed matching with 3' UTR context, or recovering miRNA-mRNA chimeras at scale.
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。
Build targeted outreach lists with verified contact information, professional context, and conversation starters. Combines Apollo company data, LinkedIn profiling, and email verification to produce ready-to-send outreach campaigns for sales, PR, and partnership teams.
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 potential leads with verified contact information, professional backgrounds, company context, and social presence. Combines LinkedIn profiling, email verification, company enrichment, and social signals for sales-ready prospect 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。
Source technical and professional talent by combining LinkedIn profiles, GitHub contributions, and company intelligence. Identifies candidates with specific skills, assesses expertise depth, and provides outreach context for recruiting teams.
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 personalized email outreach by researching prospects, verifying email addresses, building company context, and generating relevant talking points. End-to-end outreach preparation from prospect identification to send-ready 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。
Use trace-mcp through bb to search indexed code and recall project decisions with compact context.
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。
Build Rust TUI apps with SuperLightTUI v0.20 (immediate-mode terminal UI). Use this skill when the user asks to create, modify, or debug terminal UI code in this repo, or asks "how do I X in SLT / TUI / terminal", or types Korean triggers like "터미널 UI", "TUI 만들어줘", "SLT로", "ratatui 대신". Read REFERENCES.md for feature flags and doc pointers; grep `src/context/` and `src/widgets/` before inventing any API.
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。
Build Rust TUI apps with SuperLightTUI v0.23 (immediate-mode terminal UI). Use this skill when the user asks to create, modify, or debug terminal UI code in this repo, or asks "how do I X in SLT / TUI / terminal", or types Korean triggers like "터미널 UI", "TUI 만들어줘", "SLT로", "ratatui 대신". Read REFERENCES.md for feature flags and doc pointers; grep `src/context/` and `src/widgets/` before inventing any API.
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。