'intel' 검색 결과

Keep the CopilotKit Intelligence documentation landing page aligned with feature and guide changes. It coordinates feature cards, links, navigation, and related tests so readers can find current guides after additions, moves, renames, or removals.

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• Adding landing-page links for a new Intelligence feature
• Updating links after moving or renaming a guide
• Removing navigation entries for deleted pages

Keeps customer-facing CopilotKit Intelligence documentation consistent by applying an approved vocabulary to prose, navigation, buttons, and image descriptions. Checks disallowed alternatives and exceptions while preserving code identifiers and the labels users actually see in product controls.

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• Standardizing terminology in customer documentation
• Reviewing navigation and button labels
• Checking terminology in image descriptions

Connect a local CopilotKit agent to Slack through a managed Intelligence Channel. The skill guides dedicated Slack app creation, credential setup, runtime configuration, and checks that a human mention receives an actual reply.

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• Setting up a dedicated Slack bot for a local agent
• Investigating a Channel stuck waiting for its runtime
• Diagnosing mentions that receive no reply

Generates structured cyber threat intelligence reports at strategic, operational, and tactical levels tailored to specific audiences including executives, security operations teams, and technical analysts. Use when producing finished intelligence products from raw collection data, creating sector threat briefings, or delivering post-incident intelligence assessments. Activates for requests involving CTI report writing, threat briefings, intelligence products, finished intelligence, or executive security reporting.

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Build Splunk pipelines that import threat intelligence and match security events against indicators such as malicious IP addresses, domains, and file hashes. Add source, confidence, and severity details so analysts have context when investigating matches.

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• Importing external threat feeds into Splunk
• Matching network and endpoint logs against threat indicators
• Adding threat and asset context to alerts

VNX-specific domain expertise for the intelligence system, central state databases, and dispatch lifecycle. Use when working on quality_intelligence.db / runtime_coordination.db, code_snippets FTS5, snippet_metadata linkage, success_patterns / antipatterns, T0 state projection (t0_state.json), intelligence_injections lifecycle, dispatch → receipt → events → archive flow, central state architecture, project_id propagation across VNX, or any code that reads/writes VNX governance state. Triggers include: editing intelligence injection code, querying central DB for cross-project insights, debugging "intelligence not appearing in T0 state", modifying schema in `schemas/quality_intelligence.sql` or `schemas/runtime_coordination_v*.sql`, working with `scripts/quality_db_init.py` or `scripts/lib/coordination_db.py`.

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VNX-specific domain expertise for the intelligence system, central state databases, and dispatch lifecycle. Use when working on quality_intelligence.db / runtime_coordination.db / dispatch_tracker.db, code_snippets FTS5, snippet_metadata linkage, success_patterns / antipatterns, T0 state projection (t0_state.json), intelligence_injections lifecycle, dispatch → receipt → events → archive flow, central state architecture, project_id propagation across VNX, or any code that reads/writes VNX governance state. Triggers include: editing intelligence injection code, querying central DB for cross-project insights, debugging "intelligence not appearing in T0 state", modifying schema in `schemas/quality_intelligence.sql` or `schemas/runtime_coordination_v*.sql`, working with `scripts/quality_db_init.py` or `scripts/lib/coordination_db.py`.

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Use when you need CrowdStrike Falcon Intelligence on an indicator (IOC reputation for an IP, domain, hash, or URL — malicious confidence, linked actors, malware families, reports) OR on an adversary (threat-actor profile, origin/target search, MITRE ATT&CK TTPs, finished intel reports). Answers questions like "look up 1.1.1.1", "what TTPs does Charming Kitten use?", "which threat actors operate from Russia?", and "latest report on Mustang Panda". Commonly invoked by the four /*-investigation skills, /ioc-enrichment-workflow, /threat-actor-profiling, and the regional espionage cells. Other agents/skills can chain this for vendor-authoritative actor and finished-intel context. Requires a Falcon Intelligence subscription.

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Maintain Pulp's macOS Intel (x86_64) portability lint and CI tiering — the PULP_INTEL_CANARY configure gate, intel_canary_lint.py + its allowlist, and the Tier 0-3 workflows (build.yml canary step, intel-portability.yml, nightly-intel.yml, release-cli.yml universal gate). Use when touching cross-arch build wiring, arch-gated SIMD, or Intel CI.

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Use hosted DNA models to predict gene structures, expression levels, and regions that regulate gene activity. Start from a gene symbol, genomic coordinates, or a DNA sequence, without installing model weights or running a local GPU.

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• Finding promoter regions in a DNA sequence
• Predicting splice donor and acceptor sites
• Estimating gene expression for a specified cell type

Run language models locally with llama.cpp on CPUs, Apple Silicon, or AMD and Intel GPUs. The skill guides model setup, memory-saving GGUF format choices, interactive chat, and serving models through an OpenAI-compatible API.

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• Running a language model on a CPU-only computer
• Setting up local chat on an Apple Silicon Mac
• Choosing model quantization to fit available memory

Guides you through running large language models on CPUs, Apple Silicon, and AMD or Intel GPUs. Covers choosing GGUF model files, reducing memory through quantization, and starting an OpenAI-compatible chat server.

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• Running a local LLM on an Apple Silicon Mac
• Trying LLM inference on a CPU-only machine
• Choosing a model format that fits available memory

Query Fintel (fintel.io) institutional market data through its REST API or official MCP server. Use this skill whenever the user mentions Fintel or asks about short interest, short interest ratio or days to cover, short squeeze data, borrow rate or cost to borrow, shares available to borrow, daily short volume, fails-to-deliver (FTD), 13F institutional owners ("who owns X"), insider buying or selling from SEC Form 3/4/5, analyst price targets, ratings and forecasts, dividend or earnings history and calendars, EOD or last prices, security lookup by ticker, CUSIP, ISIN, or FIGI, Fintel leaderboards, or their Fintel watchlists and alerts. Read-only: GET endpoints only.

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Azure.AI.DocumentIntelligence (.NET) workflow skill. Use this skill when the user needs Azure AI Document Intelligence SDK for .NET. Extract text, tables, and structured data from documents using prebuilt and custom models and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

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🧠 Andru.ia Niche Intelligence (Dominio Experto) workflow skill. Use this skill when the user needs Estratega de Inteligencia de Dominio de Andru.ia. Analiza el nicho específico de un proyecto para inyectar conocimientos, regulaciones y estándares únicos del sector. Actívalo tras definir el nicho and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

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Build Java applications that extract text, tables, and fields from documents using Azure AI Document Intelligence. Covers ready-made models for invoices and receipts, custom model creation, document classification, authentication, and error handling.

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• Extract text and tables from PDFs
• Read invoice and receipt fields
• Build models for custom document formats

Build .NET workflows that extract text, tables, and fields from invoices, receipts, and other documents using Azure AI Document Intelligence. Covers prebuilt models, custom model creation, document classification, authentication, and result handling.

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• Extract vendors, line items, and totals from invoices
• Read merchants, dates, and totals from receipts
• Extract text and table cells from documents

Build automated pipelines that collect threat indicators, such as malicious IP addresses and file hashes, from multiple feeds. Standardize formats, remove duplicates, assess confidence, and distribute indicators to security monitoring systems for matching and alerts.

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• Automating threat feed ingestion
• Standardizing and deduplicating threat indicators
• Distributing indicators to multiple monitoring systems

Set up MISP to collect, store, and correlate threat intelligence from multiple feeds. Use PyMISP to automate searches and imports of indicators of compromise, such as suspicious IP addresses and file hashes, and export data for security monitoring tools.

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• Collecting threat indicators from multiple feeds
• Automating MISP imports and searches
• Exporting indicators for security monitoring tools

Build a central platform for collecting, analyzing, and sharing cyber threat information. Connect MISP, OpenCTI, TheHive, and Cortex to import feeds, add context to suspicious indicators, manage cases, and track platform activity.

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• Build a central threat intelligence platform
• Automate threat feed ingestion
• Add context to suspicious IP addresses and domains

Turn threat intelligence and detection gaps into testable investigation hypotheses. Use endpoint monitoring and security log queries to examine evidence, validate findings, connect related activity, and document risks and recommended actions in a consistent hunt report.

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• Planning a hunt based on threat intelligence
• Investigating gaps in ATT&CK coverage
• Testing hypotheses prompted by unusual activity

Create and review SVG icons for IntelliJ New UI. Choose sizes by interface role, prepare matching light and dark versions, refine shapes and strokes, and place the assets in the plugin’s resource folders.

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• Creating icons for actions and tool windows
• Preparing matching light and dark SVG versions
• Adapting existing icons to a 16×16 canvas

Use when the user asks what the codebase intel knows, or runs /gsd-intel query, status, diff, or refresh. Queries or rebuilds the .planning/intel/ files, and stops with a disabled message when intel is off in .planning/config.json.

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Cyber threat intelligence production — the intelligence cycle, IOC extraction/normalization/enrichment, STIX/TAXII and MISP, structured analytic models (Diamond, Kill Chain, ATT&CK), source scoring, actor/campaign tracking, and finished intelligence reporting

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