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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

Build chat bots for multiple platforms using shared TypeScript logic with Chat SDK. The skill guides message handling, interactive cards, webhook connections, streamed AI replies, and adapters that connect platforms or store conversation state.

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• Build a bot for Slack and Teams
• Respond to mentions and direct messages
• Add approval buttons to message cards

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

Find the appropriate plugin for supported DeFi services, blockchain-based financial applications, using service names or native tokens. Guide installation with user confirmation, then pass the original request to the plugin, or show the available services.

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• Find the plugin for a specific DeFi service
• Identify a service from its native token
• Browse supported DApps

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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创建或修改连接Paperclip与AI智能体运行环境的适配器，涵盖服务端执行、配置界面、命令行输出、会话管理、用量与费用获取及环境诊断。

• 接入新的命令行智能体
• 通过HTTP端点连接智能体
• 实现会话恢复与重试

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

Explore DeFi products, blockchain-based financial services, aggregated by OKX. Check yields, historical data, and existing positions across supported chains, then handle deposits, withdrawals, or reward claims through the onchainos CLI.

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• Find DeFi products and compare yields
• Check DeFi holdings across multiple chains
• Deposit assets or withdraw existing positions

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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