'dap' 검색 결과

Strengthen LDAP and Active Directory services by reviewing encrypted connections, signing, channel binding, access controls, and audit logging. Use the guidance to organize security settings, validate them in a test environment, and document implementation evidence.

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• Reviewing LDAP or Active Directory security settings
• Organizing encrypted connections and authentication protections
• Checking audit logging and monitoring arrangements

Review Active Directory permissions with ldap3, a Python library for directory queries. Identify excessive access granted to non-administrative accounts, explain potential privilege escalation paths, and produce a JSON report with affected objects and remediation recommendations.

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• Auditing excessive Active Directory permissions
• Investigating privilege escalation paths from ordinary accounts
• Reporting affected objects and permission remediation recommendations

Adaption AI SDK for synthetic data augmentation and dataset adaptation. Use when building data pipelines with the Adaption Python SDK, uploading datasets (local files, Hugging Face, Kaggle), running augmentation/adaptation jobs, configuring brand controls (hallucination mitigation, safety categories, length), recipe specifications (reasoning traces, deduplication, preference pairs, prompt rephrase), evaluating dataset quality, downloading results, or any workflow involving `pip install adaption`, `from adaption import Adaption`, Adaptive Data, or the adaptionlabs.ai API. Also trigger when the user mentions synthetic data generation for fine-tuning, dataset augmentation pipelines, DPO preference pair generation, or grounding-based hallucination reduction on training data.

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Helps build or improve reusable OpenCLI website commands in JavaScript. It uses observed page behavior, captured requests, and existing adapters to guide implementation, then checks definitions and tests real command behavior and failure handling.

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• Turning repeated website tasks into OpenCLI commands
• Improving an existing website adapter
• Investigating API requests before implementation

Plan protein characterization experiments with Adaptyv's cloud laboratory, estimate costs, submit sequences, track progress, and retrieve measured results. Supports binding, thermal stability, expression, fluorescence, and enzyme activity workflows through the API and Python SDK.

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• Plan binding screens for candidate protein sequences
• Estimate experiment costs before submission
• Track laboratory progress and retrieve results

Develop and migrate LangBot messaging adapters for Event-Based Agents, its event-driven architecture. Check conversion into shared event and message formats, implement platform APIs, and verify behavior through unit tests and real platform interactions.

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• Adding a messaging platform adapter to LangBot
• Migrating an existing adapter to the EBA layout
• Testing event and message conversion in both directions

Build multi-platform chat bots with Chat SDK (`chat` npm package). Use when developers want to (1) Build a Slack, Teams, Google Chat, Discord, Telegram, GitHub, Linear, or WhatsApp bot, (2) Use Chat SDK to handle mentions, direct messages, subscribed threads, reactions, slash commands, cards, modals, files, or AI streaming, (3) Set up webhook routes or multi-adapter bots, (4) Send rich cards or streamed AI responses to chat platforms, (5) Build or maintain a custom adapter or state adapter. Triggers on "chat sdk", "chat bot", "slack bot", "teams bot", "google chat bot", "discord bot", "telegram bot", "whatsapp bot", "@chat-adapter", "@chat-adapter/state-", "custom adapter", "state adapter", "build adapter", and building bots that work across multiple chat platforms.

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Design and implement adaptive filters using DSP System Toolbox System objects. Use when working with adaptive filtering, system identification, noise cancellation, echo cancellation, active noise control (ANC), channel equalization, inverse system identification, or adaptive prediction. Covers dsp.LMSFilter, dsp.RLSFilter, dsp.FilteredXLMSFilter, dsp.FrequencyDomainAdaptiveFilter, dsp.AffineProjectionFilter, dsp.BlockLMSFilter, dsp.AdaptiveLatticeFilter, dsp.FastTransversalFilter, maxstep(), and algorithm selection for adaptive filtering problems. Replaces deprecated adaptfilt.* objects (removed R2020a).

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Test the Senpi adapter and task engine against the real senpi binary in an isolated environment. Check task and team behavior, record evidence in a consistent location, and verify that the existing agent directory remains untouched.

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• Verify adapter behavior after code changes
• Test task execution and team recovery
• Check that skills reach child tasks

Investigate NTLM relay, an attack that forwards authentication messages to another service, by comparing Windows login events with host inventories. Use the supplied queries and audits to identify suspicious sources, weaker authentication, and gaps in signing enforcement.

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• Investigating mismatched login source addresses and hostnames
• Building SIEM rules to detect NTLM relay
• Auditing SMB and LDAP signing requirements

Helps fine-tune large language models with LoRA and QLoRA, methods that train small sets of additional parameters. Covers memory-conscious training, configuration choices, saving adapters, and switching task-specific adapters on a shared base model.

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• Fine-tune a model with limited GPU memory
• Choose LoRA settings for a specific task
• Switch task-specific adapters on one base model

Cultural adaptation for translated content. Run AFTER blog-translate completes. Adjusts brand examples, CTAs, legal references, and formality for the target market (German, French, Japanese, Spanish, etc.). Deep cultural adaptation of translated blog posts. Goes beyond translation to swap brand examples, adapt CTAs, substitute legal references, localize statistic sources where possible, and adjust formality (Sie/du, tu/vous, formal/informal). Built-in profiles for DACH, Francophone, Hispanic, and Japanese markets, plus a custom-locale template. Makes content feel locally authored, not translated. Use when user says "localize blog", "blog localize", "cultural adaptation", "adapt for Germany", "adapt for France", "lokalisieren", "localiser", "adaptar".

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Cultural adaptation for translated content. Run AFTER blog-translate completes. Adjusts brand examples, CTAs, legal references, and formality for the target market (German, French, Japanese, Spanish, etc.). Deep cultural adaptation of translated blog posts. Goes beyond translation to swap brand examples, adapt CTAs, substitute legal references, localize statistic sources where possible, and adjust formality (Sie/du, tu/vous, formal/informal). Built-in profiles for DACH, Francophone, Hispanic, and Japanese markets, plus a custom-locale template. Makes content feel locally authored, not translated. Use when user says "localize blog", "blog localize", "cultural adaptation", "adapt for Germany", "adapt for France", "lokalisieren", "localiser", "adaptar".

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Build or modify adapters that connect Paperclip to AI agent runtimes. Covers server execution, configuration forms, terminal output, session persistence, and environment checks for CLI agents, HTTP endpoints, and custom processes.

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• Connect a new CLI agent to Paperclip
• Add support for an HTTP agent endpoint
• Implement session resumption and recovery

Fine-tune large language models with LoRA and QLoRA while limiting GPU memory use. Guides training settings and adapter management, using small sets of task-specific weights that can be saved, switched, or merged into a base model.

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• Fine-tuning an LLM with limited GPU memory
• Choosing LoRA settings and training layers
• Switching task-specific adapters on one base model

Validate FASTQ sequencing files, run local quality checks, and interpret reports to decide whether trimming is needed. Optionally remove adapters or low-quality read ends while preserving original reads and their quality reports.

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• Check sequencing quality before downstream analysis
• Summarize quality reports across multiple samples
• Assess whether adapter or quality trimming is needed

Global content at the speed of AI. This skill covers the full spectrum of AI-powered localization: translation, cultural adaptation, voice localization, visual adaptation, and the orchestration required to take content from one language/market to 50. Traditional localization is slow, expensive, and creates bottlenecks. AI-powered localization enables simultaneous global launches, personalized content by market, and continuous localization as content evolves. But localization isn't just translation. It's cultural adaptation. It's knowing that colors mean different things in different cultures, that humor doesn't translate, that some messages must be completely reimagined for new markets. Use when "localize, localization, translate, translation, multi-language, international, global, multilingual, market adaptation, cultural adaptation, other languages, different countries, localization, translation, international, global, multilingual, cultural-adaptation, ai-dubbing" mentioned.

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How to use the Adaptyv Bio Foundry API and Python SDK for protein experiment design, submission, and results retrieval. Use this skill whenever the user mentions Adaptyv, Foundry API, protein binding assays, protein screening experiments, BLI/SPR assays, thermostability assays, or wants to submit protein sequences for experimental characterization. Also trigger when code imports `adaptyv`, `adaptyv_sdk`, or `FoundryClient`, or references `foundry-api-public.adaptyvbio.com`.

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How to use the Adaptyv Bio Foundry API and Python SDK for protein experiment design, submission, and results retrieval. Use this skill whenever the user mentions Adaptyv, Foundry API, protein binding assays, protein screening experiments, BLI/SPR assays, thermostability assays, or wants to submit protein sequences for experimental characterization. Also trigger when code imports `adaptyv`, `adaptyv_sdk`, or `FoundryClient`, or references `foundry-api-public.adaptyvbio.com`.

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Pure API reference for reddapi.dev - authentication, all endpoints (vector search, semantic search, trends, subreddit lookup), request parameters, response schemas, and error codes, with no research-workflow framing. Use when the user wants raw endpoint documentation, is debugging a reddapi.dev integration, needs exact request/response field names, or asks for 'reddapi API reference', 'reddapi.dev endpoints', or 'reddapi error codes'. For guided research workflows and query playbooks, see reddit-research. For B2B lead scoring, see reddit-leads.

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Build, install, validate, and debug custom Exasol virtual schema adapters. Covers source-specific JDBC dialect implementation with `virtual-schema-common-jdbc` including `SqlDialect`, metadata reader behavior, type mapping, and pushdown capabilities, custom document-file adapter code boundaries, custom adapter properties, JAR packaging, BucketFS deployment, adapter script setup, `EXPLAIN VIRTUAL` validation, and adapter-side remote debugging workflows.

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Harden LDAP directory services against common attacks including credential harvesting, LDAP injection, anonymous binding, and channel binding bypass. Covers LDAPS enforcement, channel binding, LDAP si

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How to use the Adaptyv Bio Foundry API and Python SDK for protein experiment design, submission, and results retrieval. Use this skill whenever the user mentions Adaptyv, Foundry API, protein binding assays, protein screening experiments, BLI/SPR assays, thermostability assays, or wants to submit protein sequences for experimental characterization. Also trigger when code imports `adaptyv`, `adaptyv_sdk`, or `FoundryClient`, or references `foundry-api-public.adaptyvbio.com`.

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Harden LDAP directory services against common attacks including credential harvesting, LDAP injection, anonymous binding, and channel binding bypass. Covers LDAPS enforcement, channel binding, LDAP si

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.