「rag」の検索結果

Deep integration analysis for newly created artifacts

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 Agent Tool Contract — 5 principles for designing tools agents call reliably: predictable signature, rich errors, token-efficient output, idempotency, graceful degradation. Includes anti-pattern table with 8 common mistakes.

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Benchmark external agent frameworks, auto-detect source type, scan for prompt injection, and convert findings into a concrete TDD upgrade backlog for agent-studio evolution.

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Scheduled ArXiv paper monitor. Uses CronCreate to search configured keywords every 6 hours, deduplicates via MemoryRecord, and stores summaries in named memory for morning briefing integration.

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Pythonic wrapper around RDKit with a simplified interface and sensible defaults. Preferred for standard drug discovery work — SMILES/SELFIES/InChI conversion, molecule standardization and sanitization, descriptors, ECFP and other fingerprints, Tanimoto distance matrices, Butina clustering and diverse subset picking, Bemis-Murcko scaffolds and scaffold splits, BRICS/RECAP fragmentation, 3D conformer generation, SDF/CSV/Excel and cloud I/O, and parallel processing via n_jobs. Returns native rdkit.Chem.Mol objects, so it composes with RDKit throughout. Also trigger on datamol, `import datamol as dm`, dm.to_mol, dm.standardize_mol, dm.cluster_mols, or dm.pick_diverse. For advanced control or custom parameters, use the rdkit skill directly.

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Generate and optimise novel small molecules with REINVENT 4 — de novo sampling from a chemical language model, scaffold decoration with LibInvent, fragment linking with LinkInvent, and similarity-constrained analogue generation with Mol2Mol. Use this skill to set up reinforcement-learning or curriculum runs, compose a multi-parameter scoring function from docking scores, predictive models, and physicochemical desirability, and read the resulting sampled sets. Also trigger on REINVENT, LibInvent, LinkInvent, Mol2Mol, scaffold hopping, R-group replacement, linker design, chemical language model, or reinforcement-learning molecule optimisation.

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Number antibody variable domains, annotate CDRs, and assess developability from sequence. Use this skill to apply IMGT, Kabat, Chothia, Martin, or AHo numbering with ANARCI, delimit CDRs and framework regions, scan for chemical liabilities (N-glycosylation sequons, deamidation NG, isomerisation DG, oxidation, unpaired cysteine, fragmentation), compute pI, net charge, extinction coefficient and hydrophobicity, and plan humanisation by CDR grafting. Also trigger on antibody, nanobody, VHH, scFv, Fab, CDR, framework, ANARCI, abnumber, IgBLAST, OAS, SAbDab, humanization, Vernier residues, or developability.

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Navigate make-on-demand catalogues — ZINC-22 through CartBlanche and Enamine REAL Space — to find compounds that can actually be ordered. Use this skill to look substances up by ZINC identifier or structure, understand tranche partitioning by heavy-atom count and logP, and choose between screening an enumerated subset and searching a combinatorial synthon space with a fragment-growing method such as V-SYNTHES. Also trigger on ZINC22, CartBlanche, Enamine REAL, make-on-demand, tangible library, synthon, tranche, giga-scale enumeration, or ultra-large virtual screening.

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Estimate how likely a protein therapeutic is to provoke an anti-drug antibody response, and locate the sequence regions responsible. Use this skill to tile a sequence into peptides, predict class II MHC presentation across a population-representative allele panel, aggregate predicted binders into a per-region and whole-molecule risk score, compare a candidate against its closest human germline, and decide which liabilities are worth deimmunising. Also trigger on immunogenicity, anti-drug antibody, ADA, T-cell epitope, MHC class II, HLA-DRB1, NetMHCIIpan, NetMHCpan, deimmunisation, tregitope, or population coverage.

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Run Claude Code in autonomous iteration loops until task completion — PRD-based feature development, test coverage improvement, lint fixing, documentation generation, dataset creation, or framework migrations. Uses in-session loop mechanism with specialized templates. Triggers on autonomous loop, iterate until done, run until passing, keep going until, ralph, PRD execution.

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Design human-visible, machine-readable website layers for AI assistants, RAG, and agentic search. Use this skill when the user asks for llms.txt, LLM discovery plans, visible TLDR or direct-answer blocks, source trails, entity pages, markdown alternates, AI crawler policy, topic-to-URL maps, assistant-readable public content, or LLM-friendly architecture that must preserve canonical SEO strategy without hidden bot-only facts or duplicate story bodies.

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。

診斷並清理 macOS 磁碟空間，特別是「系統資料 / System Data」這類看不出內容的用量。涵蓋開發者工具殘骸（Xcode iOS DeviceSupport、Simulator runtime、DerivedData）、套件管理器快取（Homebrew、pnpm、pip、npm、cargo、go、uv）、容器與 VM 磁碟（Docker、podman、lima）、瀏覽器 profile、以及已移除 app 的孤兒 container。使用時機：(1) 使用者說磁碟快滿了、System Data 佔太多、想清空間 (2) 詢問某個資料夾或快取能不能刪 (3) 移除 app 後想清乾淨殘留檔案、完整解除安裝 (4) 想知道 Docker.raw、Group Containers、Library/Caches 這些是什麼、佔了多少。Also triggers in English — disk full, startup disk almost full, free up disk space, clean up Mac storage, what is System Data on my Mac, what is taking up space, safe to delete this cache, uninstall app leftovers, reclaim disk space, Docker.raw huge, Xcode taking too much space

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Purify water from wild sources using boiling, filtration, and chemical methods. Covers source assessment and priority ranking, sediment pre-filtering, method selection (boiling, chemical, UV, filter), altitude-adjusted boiling procedure, chemical treatment dosages, and safe storage practices. Use when needing drinking water in a wilderness setting, when available water sources are of unknown quality, in an emergency survival situation where dehydration is a risk, or when making water safe for cooking or wound cleaning.

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Start and maintain a fire using friction, spark, and solar methods. Covers site selection, material grading (tinder/kindling/fuel), fire lay construction (teepee, log cabin, platform), ignition techniques (ferro rod, flint & steel, bow drill), flame nurturing, and Leave No Trace extinguishing. Use when needing warmth, light, or a signal in a wilderness setting, when boiling water for purification, when cooking foraged food, or in an emergency survival situation requiring heat or morale support.

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Cultivate edible and medicinal mushrooms from spawn through fruiting. Covers substrate preparation, inoculation methods, incubation conditions, fruiting chamber management, harvest timing, and successive flushes for oyster, shiitake, lion's mane, and other commonly cultivated species. Use when growing edible mushrooms without the risks of wild foraging, when a reliable supply of fresh culinary or medicinal mushrooms is needed, or when exploring mycelial ecology through hands-on cultivation practice.

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Design sustainable on-call rotations with balanced schedules, clear escalation policies, fatigue management, and handoff procedures. Minimize burnout while maintaining incident response coverage. Use when setting up on-call for the first time, scaling a team from 2-3 to 5+ engineers, addressing on-call burnout or alert fatigue, improving incident response times, or after a post-mortem identifies handoff issues.

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Set up centralized log aggregation with Loki and Promtail (or ELK stack), including log parsing, label extraction, retention policies, and integration with metrics for correlation. Use when consolidating logs from multiple services into a searchable system, replacing local log files with centralized queryable storage, correlating logs with metrics and traces, implementing structured logging with label extraction, or troubleshooting production incidents requiring cross-service log analysis.

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Apply collective intelligence coordination patterns — stigmergy, local rules, and quorum sensing — to organize distributed systems, teams, or workflows without centralized control. Covers signal design, agent autonomy boundaries, emergent behavior cultivation, and feedback loop tuning. Use when designing distributed systems without a coordination bottleneck, organizing teams that must self-coordinate, building event-driven architectures with shared state communication, or replacing fragile centralized orchestration with resilient emergent coordination.

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AI multi-path reasoning coherence using bee democracy — independent evaluation of competing approaches, waggle dance as reasoning-out-loud, quorum sensing for confidence thresholds, and deadlock resolution. Use when forage-solutions has identified multiple valid approaches and a selection must be made, when oscillating between options without committing, when justifying an architecture or tool choice with structured reasoning, or before an irreversible action where the cost of the wrong choice is high.

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Creation and genesis — generative ideation from void, structured emergence from ambiguity, and the discipline of bringing new patterns into existence. Maps Brahma's creative power to AI reasoning: transforming cleared space into coherent new structures, seeding possibilities, and nurturing nascent ideas through their fragile early stages. Use after shiva-bhaga dissolution has cleared stale patterns, when facing a genuinely novel problem with no obvious template, or when incremental modification has reached its limits and a fresh design is needed.

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Use when working with iOS/macOS Keychain Services (SecItem queries, kSecClass, OSStatus errors), biometric authentication (LAContext, Face ID, Touch ID), CryptoKit (AES-GCM, ChaChaPoly, ECDSA, ECDH, HPKE, ML-KEM), Secure Enclave, secure credential storage (OAuth tokens, API keys), certificate pinning (SecTrust, SPKI), keychain sharing across apps/extensions, migrating secrets from UserDefaults or plists, or OWASP MASVS/MASTG mobile compliance on Apple platforms.

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Testing React SPAs: React Testing Library + Vitest/Jest for components and hooks, msw for network mocks, Playwright/Cypress for e2e. Query priority, user events, async assertions, mocking patterns. Use this skill to: - Pick the right runner (Vitest vs Jest) and setup. - Write component tests with RTL using accessible queries. - Test custom hooks via renderHook. - Mock network with msw at the boundary. - Set up Playwright or Cypress for end-to-end coverage. Do NOT use this skill for: - General React conventions (see react-conventions). - State management testing patterns specific to a store lib (see react-state-management). - Form-specific testing (apply react-forms patterns inside test).

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Choose, configure, launch, and collect bounded subagents for research and engineering decisions. Root agents and delegation-capable subagents should read this before delegating: every task requires an explicit model tier, and high-leverage work such as research ideation, round planning, plateau pivots, large research reviews, hard optimization, disputed evidence, and expensive experiment portfolios requires frontier judgment.

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This skill should be used when the user asks to "explore the app", "/qa", "auto-test the app", "find bugs in my app", "猴子测试", "自动探索", "随便点一下看看", "测一下全 app 看有没有崩", "smoke explore", or wants autonomous exploration of an Android or iOS app to surface crashes / ANRs / unexpected states. Drives the app via ui-mcp + mobile-mcp, tracks visited pages and clicked elements via report-mcp's state graph, captures crashes via log-mcp, and produces a Markdown report with bug list + coverage stats.

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。