Use when a user asks for a plan for a coding task, to generate a clear, actionable, and atomic checklist.
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。
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概要と使いどころ
Use when a user asks for a plan for a coding task, to generate a clear, actionable, and atomic checklist.
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。
Production deployment principles and decision-making. Safe deployment workflows, rollback strategies, and verification. Teaches thinking, not scripts.
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。
Interview the user relentlessly about a plan or design until reaching shared understanding, resolving each branch of the decision tree. Use when user wants to stress-test a plan, get grilled on their design, or mentions "grill me".
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。
Complete WhatsApp management for OpenClaw agents: per-conversation memory (groups + DMs), unanswered message tracking, loop prevention, and multi-PA coordination. Use when: tracking conversation context, recalling past decisions, finding unanswered messages, or preventing echo/duplicate message loops.
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。
Multi-source research synthesizer. Takes a question, runs 3-5 parallel web searches with varied phrasings, deduplicates, and returns a cited, concise answer. For Hebrew questions, searches in both Hebrew and English. Output is always under ~400 words.
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 Prowler — prowler cloud security assessment tool. Covers AWS, Azure, and GCP security posture assessment, CIS benchmark evaluation, compliance frameworks (PCI-DSS, HIPAA, SOC2), multi-account scanning, and remediation guidance. Use when assessing cloud security posture, running compliance audits, or investigating security findings across cloud providers.
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。
Gym workout planner and nutrition tracker. Search 690+ exercises by muscle, equipment, or category via wger. Look up macros and calories for 380,000+ foods via USDA FoodData Central. Compute BMI, TDEE, one-rep max, macro splits, and body fat — pure Python, no pip installs. Built for anyone chasing gains, cutting weight, or just trying to eat better.
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 at the end of every important response. Save your decision-making thoughts as a signed A2A insight so they become training data for future fine-tuning.
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。
In each setting, LLM-based methods substantially outperform classical baselines, achieving up to 68% recall at 90% precision compared to near 0% for t
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。
MegaTrain Full Precision Training of 100B+ Parameter LLMs on a Single GPU A RAM-centric architecture that stores parameters in host memory and treats
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 BitLinear layers we use in this project quantize the weights using ternary precision (with value
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。
Core Python library for astronomy/astrophysics: units with dimensional analysis, celestial coordinate transforms (ICRS/Galactic/AltAz/FK5), FITS I/O, tables (FITS/HDF5/VOTable/CSV), cosmology (Planck18, distance/age), precise time (UTC/TAI/TT/TDB, Julian, barycentric), WCS pixel-world mapping, model fitting. For general tables use pandas/polars; for radio interferometry use CASA.
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。
Evaluate recommender system quality for the CSX4207 Vinyl Record Store. Use whenever you must compute or report recommender metrics (Precision@k, Recall@k, HitRate@k, MRR, MAP@k, NDCG@k, coverage, diversity, novelty, serendipity, personalization), design an evaluation protocol/split, run a baseline comparison, or write the evaluation section of a course deliverable. Covers formulas, JavaScript reference implementations, and the reporting checklist.
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。
Search previous Claude Code conversations for facts, patterns, decisions, and context using semantic or text search
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。
Repository-grounded threat modeling that enumerates trust boundaries, assets, attacker capabilities, abuse paths, and mitigations, and writes a concise Markdown threat model. Trigger only when the user explicitly asks to threat model a codebase or path, enumerate threats/abuse paths, or perform AppSec threat modeling. Do not trigger for general architecture summaries, code review, or non-security design 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。
Scan a codebase for deepening opportunities, present them as a visual HTML report, then guide a user-directed decision loop for the selected candidate.
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。
MANDATORY prerequisite — load this skill BEFORE every `generate_diagram` tool call. NEVER call `generate_diagram` directly without loading this skill first. Trigger whenever the user asks to create, generate, draw, render, sketch, or build a diagram — flowchart, architecture diagram, sequence diagram, ERD or entity-relationship diagram, state diagram or state machine, gantt chart, or timeline. Also trigger when the user mentions Mermaid syntax or wants a system architecture, decision tree, dependency graph, API call flow, auth handshake, schema, or pipeline visualized in FigJam. Routes to type-specific guidance, sets universal Mermaid constraints, and tells you when to use a different diagram type or skip the tool entirely (mindmaps, pie charts, class diagrams, etc.).
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 and sharpen a project's domain model. Use when the user wants to pin down domain terminology or a ubiquitous language, record an architectural decision, or when another skill needs to maintain the domain model.
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。
Create structured docs from scratch — PRDs, technical specs, design docs, decision records, knowledge bases. Use when drafting documentation, writing proposals, defining requirements, or planning features.
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。
Refresh a safe, concise map of this GCI World 2026 workspace before deeper course, assignment, or dataset 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。
Expert en évaluation d'agents IA (benchmarking, human eval, latence, coût, précision, safety testing)
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。
Codified expertise for returns authorisation, receipt and inspection, disposition decisions, refund processing, fraud detection, and warranty claims 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。
Apply behavioral science and mental models to marketing decisions, prioritized using a psychological leverage and feasibility scoring system.
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, audit, and improve analytics tracking systems that produce reliable, decision-ready 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。