「iteration」の検索結果

Identify and classify agent failures occurring before execution starts

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Systematic methodology for identifying and exploiting cryptographic implementation weaknesses in real-world applications. Covers padding oracle attacks against CBC-mode ciphers with PKCS7 padding (Vaudenay's original attack through modern padbuster automation), ECB mode exploitation including block cut-and-paste and byte-at-a-time decryption, hash length extension attacks against SHA1/SHA256/MD5-based MACs using HashPump, RSA vulnerabilities including small public exponent, common modulus, Bleichenbacher PKCS1v1.5 padding oracle, and Coppersmith's method for partial key recovery. Addresses weak PRNG exploitation targeting time-seeded generators and Mersenne Twister MT19937 state recovery from observed outputs, timing side-channel attacks against comparison operations, nonce reuse in AES-GCM leading to authentication key recovery, and key derivation weaknesses including insufficient iteration counts and missing salts. Primary tooling includes padbuster, RsaCtfTool, hashpump, and PyCryptodome for building custom exploit payloads. Maps to CWE-327 (Use of a Broken or Risky Cryptographic Algorithm), CWE-328 (Use of Weak Hash), and CWE-330 (Use of Insufficiently Random Values). Emphasizes black-box identification of vulnerable implementations before transitioning to targeted exploitation.

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Design, critique, route, and implement Gantt charts and schedule visualizations. Use when the user mentions Gantt charts, project schedules, roadmaps with task spans, milestones, dependencies, predecessors, critical path, baselines, WBS, resource plans, capacity timelines, MS Project, Primavera P6, Jira Advanced Roadmaps, GitHub Projects, Smartsheet, monday.com, Asana, ClickUp, Azure DevOps iterations, or importing/exporting project-management data for a timeline chart.

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Create UI mockups at three fidelity levels — ASCII wireframes for quick iteration, standalone HTML mockups for delivery with requirements, and live prototypes for interaction testing.

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Use when you need design-first, spec-driven, skimmable prompts for UI generation. Covers prompt structure, constraints, variations, typography/spacing rules, and iteration workflow for consistent UI outputs.

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Autonomous iteration loop: modify, verify, keep/discard against any metric

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Write JavaScript code in n8n Code nodes. Use when writing JavaScript in n8n, using $input/$json/$node syntax, making HTTP requests with this.helpers / the $helpers global, working with dates using DateTime, troubleshooting Code node errors, choosing between Code node modes, or doing any custom data transformation in n8n. Always use this skill when a workflow needs a Code node — whether for data aggregation, filtering, API calls, format conversion, batch processing logic, or any custom JavaScript. Covers SplitInBatches loop patterns, cross-iteration data, pairedItem, and real-world production patterns. Also use when asked why a Code node or workflow is slow, which execution mode is faster, or how to cut per-item overhead on large datasets. EXCEPTION — for the AI-agent-callable Custom Code Tool (@n8n/n8n-nodes-langchain.toolCode, a tool attached to an AI Agent), use the n8n-code-tool skill instead; it has a different runtime contract.

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Guide users through a structured workflow for co-authoring documentation. Use when user wants to write documentation, proposals, technical specs, decision docs, or similar structured content. This workflow helps users efficiently transfer context, refine content through iteration, and verify the doc works for readers. Trigger when user mentions writing docs, creating proposals, drafting specs, or similar documentation tasks.

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Autonomous improvement loop: scan codebase metrics, scaffold experiment files, run agent-driven iterations until metric improves

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Orchestrates end-to-end autonomous AI research projects using a two-loop architecture. The inner loop runs rapid experiment iterations with clear optimization targets. The outer loop synthesizes results, identifies patterns, and steers research direction. Routes to domain-specific skills for execution, supports continuous agent operation via Claude Code /loop and OpenClaw heartbeat, and produces research presentations and papers. Use when starting a research project, running autonomous experiments, or managing a multi-hypothesis research effort.

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持久战略：面对长期、复杂、短期不可能速胜的任务，客观评估态势，划分战略防御 / 相持 / 反攻三阶段，判定当前所处阶段，设置阶段转换条件，并在困难阶段仍给出局部进攻点。当任务跨多个会话或多轮迭代、资源暂时不足、或出现"想放弃"与"一把梭"两种情绪时触发；任务能在当前会话完成时不触发。 English: Protracted strategy. For long-horizon work that cannot be won quickly, assess the situation objectively, divide the effort into defense / stalemate / counter-offensive stages, name the current stage and its exit condition, and always identify a local offensive even while accumulating. Trigger when work spans many sessions or iterations, resources are temporarily short, or you notice either defeatism or a rush to finish; skip when the task fits in the current session.

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Capture a full DevTools-protocol trace of any browser automation — CDP firehose, screenshots, and DOM dumps — then bisect the stream into per-page searchable buckets. Use when the user wants to debug a failed run, audit network/console/DOM activity, attach a trace to an in-progress session, or feed structured per-page summaries back into an agent loop so its next iteration learns from the last one.

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Create or update GoClaw agent skills with eval-driven iteration. Use for new skills, skill scripts, references, benchmark optimization, description optimization, eval testing, extending agent capabilities.

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Autonomous NeMo-RL research agent workflow for directed hypothesis testing and open-ended discovery. Guides agents through the full experiment lifecycle: understanding recipes and environments, wiring RL or NeMo-gym runs, launching reproducible baselines and iterations, analyzing results, preserving human oversight, and using git plus TSV logs as the research ledger. Do NOT use for: bug fixes, code review, documentation, refactoring, dependency updates, or single-file changes.

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Validate and use CUDA graph capture in Megatron Bridge, including local full-iteration graphs and Transformer Engine scoped graphs for attention, MLP, and MoE modules.

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Use this skill when the user is invoking doca_flow_dpa_perf on DPA-capable hardware (ConnectX-7 minimum supported, ConnectX-8 recommended, or BlueField-3) to measure rule update / disable rates on the DPA-offloaded DOCA Flow path — picking the active / passive device split, choosing workload-shape axes (burst, queue, completion threshold, workers, hash pipe algo, PSL tables), or reading Kops/sec iteration stats and the optional self-test. Trigger even when the user does not explicitly mention "doca_flow_dpa_perf" or "DPA Provider" — typical implicit phrasings include "how fast can the DPA program path-selector entries", "baseline rule-update rate on ConnectX-8", "tool reports zero ops on my BlueField", "self-test sentinel never shows on tcpdump", or "is my BlueField-2 DPA-capable". Refuse and route elsewhere for the host / DPU-CPU Flow path (doca-flow-perf), Flow pipeline tuning (doca-flow-tune), writing doca-flow / doca-dpa applications, or DOCA install — those belong to other skills.

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Build translation applications using Azure Translation SDKs for JavaScript (@azure-rest/ai-translation-text, @azure-rest/ai-translation-document). Use when implementing text translation, transliteration, language detection, or batch document translation.

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Azure AI Text Translation SDK for real-time text translation, transliteration, language detection, and dictionary lookup. Use for translating text content in applications. Triggers: "text translation", "translator", "translate text", "transliterate", "TextTranslationClient".

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Detect backtest iteration stagnation and generate structurally different strategy pivot proposals when parameter tuning reaches a local optimum.

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Auto-grow a pro-workflow wiki by running a budget-capped BFS research loop over pluggable source fetchers (web, arXiv, GitHub). Each iteration pops a seed from the queue, fetches sources, drafts a wiki page, dedupes claims against existing pages, enqueues follow-up seeds. Halts on budget cap, depth cap, or convergence. Use when the user says "research <topic>", "grow the <slug> wiki", "auto-research", or wants a knowledge base that builds itself overnight.

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Configure a local development workflow for Anthropic Claude API projects. Use when setting up dev environment, configuring hot reload, or establishing a fast iteration cycle with the Messages API. Trigger with phrases like "anthropic local dev", "claude dev setup", "anthropic development workflow", "test claude locally".

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Set up iterative design-to-code development loop with Anima SDK. Use when rapidly iterating on Figma-to-code output, comparing framework outputs, or building a local preview server for generated components. Trigger with: "anima local dev", "anima dev loop", "anima preview", "anima iteration".

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Build native-feeling, benchmark-quality mobile app screens (Expo / React Native). Use when designing or implementing any mobile UI — screens, flows, onboarding, paywalls, tab bars, sheets, settings, empty states — or when polishing motion, navigation, typography, dark mode, or perceived performance. Enforces Apple HIG fidelity, semantic colors, native controls, anti-slop discipline, navigation semantics (push vs replace, modal vs sheet vs overlay, the one-way doors where back must not exist), purposeful Reanimated motion, a full-motion simulator-verified iteration loop, and a study-real-apps-first workflow (pairs with the Appllama MCP). Trigger on "build a screen", "make this screen better", "design the onboarding", "wire up this flow", "polish the UI", "make it feel native", or any mobile design/implementation task.

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Claude-native deep research using DAG-based query planning, parallel subagent execution, and gap-driven iteration. No external API needed.

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