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概要と使いどころ
Calculus and continuous transformation — derivatives, integrals, ODEs, Taylor series, and optimization. Computes rates of change, accumulates quantities over intervals, solves differential equations, and classifies critical points. Use when computing derivatives or integrals, solving ordinary differential equations, performing Taylor series approximations, finding critical points, or analyzing continuous change and motion.
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。
Classic image manipulation with Python Pillow - resize, crop, composite, format conversion, watermarks, brightness/contrast adjustments, and web optimization. Use this skill when post-processing AI-generated images, preparing images for web delivery, batch processing image directories, creating responsive image variants, or performing any deterministic pixel-level image operation. Works standalone or alongside bria-ai for post-processing generated images.
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。
Analyze upstream specs (agentskills.io, Claude Code plugin/marketplace format, OpenAI Codex plugins/marketplace, OpenClaw, MCP and MCP Registry, CodeRabbit, APM) for changes, identify gaps in skillsaw's rule coverage, and create or update PRs to close those gaps. Use when performing periodic maintenance on the skillsaw linter.
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。
Automatically creates user-facing changelogs from git commits by analyzing commit history, categorizing changes, and transforming technical commits into clear, customer-friendly release notes. Turns hours of manual changelog writing into minutes of automated generation.
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。
Formal oracle for abductive inference that selects the minimal hypothesis best explaining a set of observations. Provides three sub-oracles: MCMC via monad-bayes, Gemini for natural language, and propagator networks for constraint domains. Use when performing hypothesis selection, explaining observations, or solving inference-to-best-explanation problems.
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。
Reviews Python code across type safety, error handling, security, performance, modern patterns, design clarity, typed-boundary compliance, test quality, and documentation. Use when performing code review, PR review, pre-merge quality checks, or assessing Python for security vulnerabilities, bare except clauses, Any usage outside boundaries, or missing input validation at system boundaries.
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 a single skill's quality against its stated purpose. Classifies the skill's purpose type, then scores applicable quality categories — universal dimensions always apply; structural dimensions (scripts, references, assets) are scored only when warranted by the skill's purpose. A focused 20-line behavioral skill with no bundled resources scores fully on all applicable categories. Use when auditing skill quality, checking marketplace readiness, evaluating skill completeness, performing pre-publication evaluation.
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。
Generates one worker task prompt conforming to the CLEAR + selective CoVe task design standard and swarm-task-planner structure. Use when creating or rewriting a single task entry or task block inside a plan — providing a title and brief description as input.
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 PLAN artifact from SAM Stage 2 needs contextualization against actual codebase state — grounds the design plan in reality by performing scope analysis (NEW/MODIFY/COMPLETE classification), conflict detection between plan assumptions and codebase patterns, and resource mapping to concrete file paths and integration points. Produces an updated ARTIFACT:PLAN registered via MCP with a Contextualization section appended.
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。
This skill should be used when analyzing Claude Code session transcripts, reviewing agent performance, finding anti-patterns or tool misuse, mining workflow patterns, running kaizen analysis, debugging agent behavior, or performing session forensics.
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 modifying, converting, or transforming structured data with dasel v3 — in-place mutations, format conversion, batch operations, array manipulation, object construction, and merge patterns across JSON, YAML, TOML, XML, CSV, HCL, INI
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 engine optimization strategies and tactics for organic growth. Use when optimizing content for search, conducting keyword research, performing SEO audits, or building link strategies.
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 quality control, non-conformance investigation, root cause analysis, corrective action, and supplier quality management in regulated manufacturing. Informed by quality engineers with 15+ years experience across FDA, IATF 16949, and AS9100 environments. Includes NCR lifecycle management, CAPA systems, SPC interpretation, and audit methodology. Use when investigating non-conformances, performing root cause analysis, managing CAPAs, interpreting SPC data, or handling supplier quality issues.
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 Scrum Master specializing in agile transformation, team facilitation, and continuous improvement. Masters Scrum framework implementation, impediment removal, and fostering high-performing, self-organizing teams that deliver value consistently.
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。
Debug and troubleshoot ElevenLabs conversational AI agents and Twilio calls. Use when diagnosing agent issues, analyzing failed calls, troubleshooting audio problems, investigating conversation breakdowns, reviewing error logs, or optimizing underperforming agents. Includes transcript analysis, error diagnosis, and performance troubleshooting.
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。
Guide for performing Node.js version upgrades in the Electron project. Use when working on the roller/node/main branch to fix patch conflicts during `e sync --3`. Covers the patch application workflow, conflict resolution, analyzing upstream Node.js changes, building, running the Node.js test suite, and proper commit formatting for patch fixes.
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。
Guide for performing Chromium version upgrades in the Electron project. Use when working on the roller/chromium/main branch to fix patch conflicts during `e sync --3`. Covers the patch application workflow, conflict resolution, analyzing upstream Chromium changes, and proper commit formatting for patch fixes.
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。
Intelligent pattern selection for Fabric CLI. Automatically selects the right pattern from 242+ specialized prompts based on your intent - threat modeling, analysis, summarization, content creation, extraction, and more. USE WHEN processing content, analyzing data, creating summaries, threat modeling, or transforming text.
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。
mcp-atlassian is a Model Context Protocol server that connects AI assistants to Atlassian Jira and Confluence. It enables searching and managing Jira issues, reading and editing Confluence pages, and performing project management tasks through natural language via any MCP-compatible client.
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 sales enablement strategist for building high-performing sales teams. Use when designing sales training programs, onboarding and ramp plans, sales playbooks, coaching frameworks, certification programs, or competitive intelligence distribution. Covers content strategy, tool adoption, performance measurement, and continuous learning systems. Use for building sales academies, creating enablement content, and optimizing sales productivity.
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。
Structured review process for Remotion video implementations. Analyzes spec compliance, detects common timing/easing issues, validates asset quality, and provides prioritized revision lists. Use when reviewing Remotion code against design specs or performing quality assurance on video compositions. Trigger phrases "review video code", "check spec compliance", "audit Remotion implementation".
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 customer health scoring and analytics guidance. Use when designing health scores, building churn prediction models, analyzing usage metrics, identifying at-risk accounts, creating executive dashboards, or performing cohort analysis. Use for leading indicator development, customer data enrichment, risk escalation frameworks, and retention analytics.
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。
Adjusts reported earnings for non-recurring items, accounting policy choices, and run-rate normalizations. Use when performing QofE analysis, adjusting EBITDA, or validating seller financial presentations.
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。
Master memory forensics techniques including memory acquisition, process analysis, and artifact extraction using Volatility and related tools. Use when analyzing memory dumps, investigating incidents, or performing malware analysis from RAM captures.
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。