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概要と使いどころ
The only memory skill that watches on its own. No database. No vectors. No manual saves. Just an LLM observer that compresses your conversations into prioritised notes, consolidates when they grow, and recovers anything missed. Five layers of redundancy, zero maintenance. ~$0.00/month (using free-tier models). While other memory skills ask you to remember to remember, this one just pays attention.
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。
Budget Allocation & ROI Projector. Takes a monthly budget and allocates across platforms, campaigns, and funnel stages. Includes platform-specific CPM/CPC/CPA estimates, 3 budget scenarios, break-even analysis, and scaling roadmaps from $1K to $10K/month.
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。
Turn ONE topic, talking-head video, or photo into a finished Vox-style paper-collage explainer / ad video on the MuAPI platform (api.muapi.ai) + local ffmpeg — script, collage keyframes, motion, voice-over, music, captions, all automated. Three input modalities: a topic (B-roll), a talking-head video (A-roll mode), or a single photo of a person/product anchored into the collage (C-roll mode).
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。
Fix Riverpod "Cannot use Ref or modify other providers inside life-cycles/selectors" crash in @riverpod provider bodies. Use when: (1) Crash during provider disposal with this exact error message, (2) Using keepAlive() with timer-based disposal, (3) Async callbacks (.then, .catchError) try to use ref.read() or ref.invalidateSelf(), (4) Error occurs after ref.onCancel/onResume/onDispose callbacks fire. Solution: wrap ref operations in try-catch or avoid using ref in async callbacks entirely.
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。
Fix Gorse recommendation engine pods crashing with "user: unknown userid 65532" error. Use when: (1) Gorse master/server/worker pods show CrashLoopBackOff or Error status, (2) Logs show "failed to get user directory" with unknown userid, (3) Running gorse containers with runAsNonRoot security context and custom UID. The gorse images call os.UserHomeDir() at startup which requires the UID to exist in /etc/passwd.
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。
Configure static outbound IP addresses for Google Cloud Run jobs/services. Use when: (1) External service needs to whitelist your IP (archive.org, APIs, firewalls), (2) Cloud Run requests appear from random/changing IPs, (3) Need consistent source IP for crawlers, scrapers, or API clients running on Cloud Run. Requires VPC connector + Cloud NAT + static IP reservation. Works for both Cloud Run services and jobs.
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。
Choose and validate RuVector or AgentDB memory for an agent application, including provenance, isolation, retention and workload-specific retrieval benchmarks.
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。
Turn a song into a beat-synced music video with Guaardvark's Director: song analysis, per-cut shot prompts, storyboard keyframes, image-to-video renders, cuts on the beat. Use when the user says "music video", "video for this track", or wants visuals timed to a song. Has an approval gate before GPU spend.
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。
Operate a running Guaardvark: GPU and VRAM state, plugin start/stop, logs, Celery tasks, the Interconnector sync to other machines, overnight RAG autoresearch, and infographics. Use when the user asks what is using the GPU, why a job is stuck, to start or stop ComfyUI/Audio Foundry/Swarm, to sync another box, to run autoresearch, or to make an infographic.
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 implementing aI model selection interface.
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。
Convert structured project-note JSON manuscripts into validated EPUB and optional Kindle-clickable PDF files. Use when the user asks to turn project notes, book-system JSON, FIRE-indexed notes, Luhmann/Zettelkasten numbered chunks, table-of-contents cards, index cards, cross-linked project notes, or manuscript JSON into an EPUB/PDF with chapter directories, keyword index cards, weighted links, bidirectional backlinks, versioned filenames, chapter-splitting plans, and full link 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。
Render Obsidian-style weighted graph views from book JSON, keyword indexes, TOCs, card data, or node-link data. Use when the user asks for Obsidian graph view, graph view png, weighted graph, keyword graph, directory-keyword graph, spherical graph visualization, or high-weight nodes centered with clear Chinese labels.
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。
Convert FIRE analysis cards, Chinese knowledge notes, or project-note JSON into validated EPUB books with directory cards, chapter cards, keyword index cards, backlinks, and GitHub-shareable ebook assets. Use when Codex needs to teach or automate the path from `fire-analysis-card` outputs to `project-note-json-to-epub` style EPUB files, including sample JSON manuscripts and attached `.epub` deliverables.
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, maintain, or migrate functional skills; supports creating from a requirement brief and migrating an existing legacy skill directory into a functional skill 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。
Migrate lane for fskill-creator; analyzes a legacy skill directory into behavior map, function split proposal, and source evidence.
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。
Plan, build, place, and validate physically meaningful Blender object assemblies, including manufactured part boundaries, mechanical seams, mounting interfaces, pivots, hierarchy, constraints, instancing, modular grids, connector planes, and precision snapping. Use when several objects must form one product, machine, architectural module, vehicle, furniture item, mechanism, or environment structure without incorrectly welding independent parts, eyeballing alignment, or leaving continuous shells as overlapping primitives.
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 source code statically to detect potential functional bugs including null dereferences, incorrect condition checks, unreachable code, inconsistent state updates, logic errors, resource leaks, and type mismatches. Report suspicious code locations with detailed explanations, severity levels, and confidence assessments. Use when reviewing code for bugs, performing code audits, or when the user asks to find bugs, detect issues, analyze code for problems, or perform static analysis.
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。
Statically analyze code to detect security vulnerabilities including buffer overflows, injection risks (SQL, command, XSS), insecure deserialization, improper authentication, hard-coded credentials, and unsafe cryptography. Use when: (1) Performing security code review, (2) Analyzing code for OWASP Top 10 vulnerabilities, (3) Identifying CWE-classified weaknesses, (4) Generating security audit reports, (5) Reviewing code before deployment, or (6) Assessing third-party code security. Findings categorized by CWE ID and severity (Critical/High/Medium/Low).
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 failing tests to detect functional bugs in code. Takes repository and failing test output as input, analyzes execution behavior, assertions, and stack traces to identify suspicious code regions and root causes. Use when debugging test failures, investigating regression bugs, or understanding why tests fail. Explains the bug mechanism, identifies affected code, and suggests fixes based on test expectations vs actual behavior.
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 semantic-level bugs by analyzing whether code behavior matches its intended purpose inferred from function/variable names, comments, docstrings, and documentation. Use when users need to: (1) Find logic errors where implementation contradicts stated intent, (2) Identify off-by-one errors and boundary mismatches, (3) Detect inverted logic or wrong operators, (4) Catch missing edge case handling, (5) Verify code matches its documentation. Highlights mismatches between intent and implementation across multiple programming languages.
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。
Identifies non-deterministic or unreliable tests through static code analysis and test result analysis. Use when Claude needs to find flaky tests, analyze test reliability, or investigate intermittent test failures. Supports Python (pytest, unittest) and Java (JUnit, TestNG) test frameworks. Trigger when users mention "flaky tests", "intermittent failures", "non-deterministic tests", "unreliable tests", or ask to "find flaky tests", "analyze test stability", or "why tests fail randomly".
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 design quality issues in code including high coupling, low cohesion, God classes, long methods, and other code smells. Use when: (1) Reviewing code architecture and design quality, (2) Identifying refactoring opportunities, (3) Detecting God classes or classes with too many responsibilities, (4) Finding high coupling or low cohesion issues, (5) Analyzing code maintainability and technical debt. Detects coupling smells, cohesion problems, complexity issues, size violations, and encapsulation problems with actionable refactoring suggestions.
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 detected vulnerabilities to assess realistic exploitability by examining control flow, input sources, sanitization logic, and execution context. Use when users need to: (1) Determine if a vulnerability is actually exploitable in practice, (2) Assess severity and impact of security issues, (3) Prioritize vulnerability remediation, (4) Understand attack vectors and exploitation conditions, (5) Generate exploitability reports with proof-of-concept scenarios. Focuses on injection vulnerabilities (SQL, command, XSS, path traversal, LDAP) with detailed analysis of reachability, controllability, sanitization, and impact.
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 and analyzes ambiguous language in software requirements and user stories. Use when reviewing requirements documents, user stories, specifications, or any software requirement text to identify vague quantifiers, unclear scope, undefined terms, missing edge cases, subjective language, and incomplete specifications. Provides detailed analysis with clarifying questions and suggested improvements.
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。