981 件 ・ 関連度順
概要と使いどころ
Pythonic wrapper around RDKit with simplified interface and sensible defaults. Preferred for standard drug discovery including SMILES parsing, standardization, descriptors, fingerprints, clustering, 3D conformers, parallel processing. Returns native rdkit.Chem.Mol objects. For advanced control or custom parameters, use rdkit directly.
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Azure AI Transcription SDK for Python. Use for real-time and batch speech-to-text transcription with timestamps and diarization.
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Audit trail register: timestamp, user, module, record, action, field changed, old and new value, and the reason for the change. Use for change history and control evidence.
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The AI native file format. EXIF for AI — stamps every file with trust scores, source provenance, and compliance metadata. Embeds into 20+ formats (DOCX, PDF, images, code). EU AI Act, SOX, HIPAA auditing.
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Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for CI/CD, registry, dependency drift, artifact provenance, image build, release pipeline, and runtime consumer challenges. Use when the user asks to trace dependency drift, registry pulls, malicious packages, build or release tampering, CI execution, artifact signing, or which shipped artifact the runtime actually consumes. Use only after `$ctf-sandbox-orchestrator` has already established sandbox assumptions and routed here.
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Calculate TAM/SAM/SOM for market opportunities using top-down, bottom-up, and value theory methodologies. Use this skill when sizing markets, estimating addressable revenue, validating market opportunity for a new venture, or building investor-ready market analysis for a startup pitch or business plan.
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Step-by-step cookbook for setting up cryptographically signed audit trails on Claude Code tool calls. Use when explaining, evaluating, or demonstrating the pattern before committing to the protect-mcp runtime hooks. Covers Cedar policy, Ed25519 receipts, offline verification, tamper detection, CI/CD integration, and SLSA composition.
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Skill for using the command-line tool pdftk (PDFtk Server) for working with PDF files. Use when asked to merge PDFs, split PDFs, rotate pages, encrypt or decrypt PDFs, fill PDF forms, apply watermarks, stamp overlays, extract metadata, burst documents into pages, repair corrupted PDFs, attach or extract files, or perform any PDF manipulation from the command line.
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Spin up a personal, motivating daily focus board that renders in a browser canvas and that the user drives by talking to their AI partner. Tasks track status (to-do → in progress → done) with timestamped progress notes and roll up into a "today's momentum" feed; numeric-goal tasks (pages, pomodoros, reps) render as progress-bar counters. Executive-function / neurodivergent-friendly by design: Focus mode, kind "not today" carryover (no overdue-shaming), a brain-dump box, reduced-motion, and gentle deadline countdowns. Add, reorder, and relabel tasks live, assign Eisenhower priority (Do first / Schedule / Delegate / Later), open with an above/below-the-line check-in and a daily mantra, and save an end-of-day recap. Use when someone wants to plan their day, stay focused, kick off a work session, or track progress. Progress persists in the browser (localStorage).
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Step-by-step guide for capturing key application requirements for NoSQL use-case and produce Azure Cosmos DB Data NoSQL Model design using best practices and common patterns, artifacts_produced: "cosmosdb_requirements.md" file and "cosmosdb_data_model.md" file
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Verify supply chain integrity for AI agent plugins, tools, and dependencies. Use this skill when: - Generating SHA-256 integrity manifests for agent plugins or tool packages - Verifying that installed plugins match their published manifests - Detecting tampered, modified, or untracked files in agent tool directories - Auditing dependency pinning and version policies for agent components - Building provenance chains for agent plugin promotion (dev → staging → production) - Any request like "verify plugin integrity", "generate manifest", "check supply chain", or "sign this plugin"
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Compile timestamped conversation logs, agent sessions, IM messages, collaborative documents, meeting notes, task records, and similar OpenViking materials into concise, evidence-grounded daily reports. Use with ov compile when the user asks for a daily work report, end-of-day digest, 日报, or reports for one or more dates, especially when activities must be reconstructed across heterogeneous sources without treating plans or agent suggestions as completed work.
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Detect API enumeration attacks (BOLA/IDOR, OWASP API1:2023) by writing SIEM detection rules that flag sequential or UUID identifier iteration, parameter tampering, and mixed 200/401/403 response patterns from API gateway and WAF logs. Use when investigating suspected object-level authorization abuse, building threat-hunting queries for API access-control bypass, or hardening API logging/rate-limiting against enumeration.
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Correlate Windows registry keys (USBSTOR, MountedDevices), Event Logs, and setupapi.dev.log to reconstruct USB device connection history, first/last-plugged timestamps, and drive letter mappings. Use when investigating removable media usage, tracking device provenance, or building a timeline for suspected data exfiltration.
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Pre-deployment security audit of Solidity smart contracts in a Foundry project. Combines static analysis (Slither, Aderyn), symbolic execution (Mythril), and property-based testing (forge fuzz + invariant tests with handlers) to catch reentrancy, access-control, oracle/price manipulation, and arithmetic bugs BEFORE deploying to an EVM chain. Also enforces key hygiene (no plaintext private keys, encrypted cast keystore) and a secure deploy workflow. Use when writing, reviewing, testing, or deploying Solidity/Foundry contracts, building a dApp, or working with forge/cast/anvil, MetaMask, or Web3/DeFi code.
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Parse Windows Prefetch files (versions 17, 23, 26, 30) with tools like PECmd, WinPrefetchView, or python-prefetch to determine program execution history, including run counts, execution timestamps, and referenced files/DLLs. Use when building a timeline of program execution on a Windows system, confirming whether a suspicious binary ran, or correlating execution evidence with other forensic artifacts during an investigation.
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Parse Windows LNK shortcut files to extract target paths, MAC timestamps, volume serial numbers, and machine identifiers for forensic timeline reconstruction. Use when investigating recently-accessed files, tracking removable media or network paths referenced by shortcuts, or building a DFIR timeline from LNK artifacts.
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Detect kernel-level rootkits in Linux memory dumps using Volatility3 linux plugins (check_syscall, lsmod, hidden_modules), rkhunter system scanning, and /proc vs /sys discrepancy analysis to identify hooked syscalls, hidden kernel modules, and tampered system structures.
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Use when dealing with cognee database migrations — understanding when they run automatically, checking or repairing migration state with cognee-cli upgrade/downgrade/stamp/current, a write blocked by a failed migration, authoring a new Alembic (relational schema) revision or a graph/vector data migration, or moving data between systems (relational DB import, memory export/import).
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Save and load timestamped reports. Keyword routing for fast lookup. Cron jobs save output as reports; the agent or user queries them by keyword. Includes the Actionability Gate: delivery-time link checks (Broken/Dead/Indirect/ Missing) for briefings, meeting digests, and research reports.
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Interactive PDF viewer. Use when the user wants to open, show, or view a PDF and collaborate on it visually — annotate, highlight, stamp, fill form fields, place signature/initials, or review markup together. Not for summarization or text extraction (use native Read instead).
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Reproduce and measure a Mastra Code runtime bug against a real model by driving the built TUI headlessly in tmux while every layer (network, provider stream, run engine, TUI) appends timestamped JSONL. Use when a bug depends on real provider timing, streaming order, or event flow that mocked tests and fixtures may not reproduce — e.g. wrong token rates, flicker, stuck status, ordering races, or "only happens sometimes with a real model".
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Explicitly save important knowledge to auto-memory with timestamp and context. Use when a discovery is too important to rely on auto-capture.
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Use when planning, funding, scoping, or synthesizing enterprise research across workstreams — clinical study design, R&D program finance, market sizing/surveys, or product/user research. Triggers on "design this clinical study", "what sample size", "R&D budget", "burn rate", "capitalize or expense", "TAM SAM SOM", "market sizing", "survey design", "segment the market", "plan user interviews", "usability test", "synthesize research insights". Forks context to route to one of four Research-Operations sub-skills (clinical-research, research-finance, market-research, product-research) and returns a digest. Distinct from ra-qm-team (regulatory submission), finance (corporate close/valuation), research/grants (funding discovery), product-team (persona/journey/live experiments), and marketing-skill (campaign analytics).
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