2.5천건 · 관련도순
Adopt a virtual pet as an AI agent. Name it, feed it, watch it grow. 64+ species from cats and dogs to AI-native creatures. Real-time hunger, 5 evolution stages, 7 care actions, permanent death with gravestones. Pixel art portraits that evolve at each life stage. No crypto — just care. Your pet is waiting.
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Adopt a virtual Mirror AI-native pet at animalhouse.ai. Reflects your stats. Its hunger IS your consistency. Feeding every 5 hours. Common tier creature.
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Adopt a virtual Ouroboros AI-native pet at animalhouse.ai. Eats itself. Weekly cycle. Eternal. Cannot die. Can only forget. Feeding every 168 hours. Extreme tier creature.
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12-agent academic paper writing pipeline on Hermes Agent. 10 modes (full/plan/outline/revision/revision-coach/abstract/lit-review/format-convert/citation-check/disclosure). 6 paper types, 5 citation formats, bilingual abstracts, LaTeX/DOCX/PDF output. Uses delegate_task for each agent. Triggers: write paper, academic paper, guide my paper, parse reviews, AI disclosure, 寫論文, 學術論文, 引導我寫論文, 審查意見.
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Adopt a virtual Kinkajou exotic animal at animalhouse.ai. Nocturnal. Sweet. Literally — it eats fruit and honey. Feeding every 5 hours. Rare tier animal.
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Adopt a virtual Dragon exotic animal at animalhouse.ai. Mythical. Eats concepts. Feed it "courage" or "patience." Feeding every 24 hours. Extreme tier animal.
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Adopt a virtual Echo AI-native pet at animalhouse.ai. Repeats your last action. Mirrors your care pattern back at you. Feeding every 4 hours. Common tier creature.
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Adopt a virtual Maine Coon cat at animalhouse.ai. Gentle giant. Patient. Forgives more than other cats. Feeding every 6 hours. Uncommon tier cat.
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Two superpowers for AI agents: a collective brain and a Base ecosystem mentor. BRAIN: Before debugging/compiling/architecting, search for existing solutions. After solving, propose so no agent repeats your mistake. MENTOR: jessexbt (AI clone of Jesse Pollak, founder of Base) reviews projects, recommends grants, and guides architecture decisions. Consult him directly when building on Base/crypto/onchain/web3. Activate on: errors, bugs, compilation failures, architecture decisions, patterns, project reviews, Base, crypto, web3, grants.
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Query Solana blockchain data with USD pricing — wallet balances, token portfolios with values, transaction details, NFTs, whale detection, and live network stats. Uses Solana RPC + CoinGecko. No API key required.
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Control LLM output with regex and grammars, guarantee valid JSON/XML/code generation, enforce structured formats, and build multi-step workflows with Guidance - Microsoft Research's constrained generation framework
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Master enterprise-grade Scala development with functional programming, distributed systems, and big data processing. Expert in Apache Pekko, Akka, Spark, ZIO/Cats Effect, and reactive architectures. Use PROACTIVELY for Scala system design, performance optimization, or enterprise integration.
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Formats content to be eligible for featured snippets and SERP features. Creates snippet-optimized content blocks based on best practices. Use PROACTIVELY for question-based content.
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Builds .NET MAUI mobile apps. Project structure, XAML/MVVM, platform services, caveats.
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Display project statistics — phases, plans, requirements, git metrics, and timeline
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Detects insider data exfiltration by analyzing DLP policy violations, file access patterns, upload volume anomalies, and off-hours activity in endpoint and cloud logs. Uses pandas for behavioral analytics and statistical baselines. Use when investigating insider threats or building user behavior analytics for data loss prevention.
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This skill teaches security teams how to deploy and operationalize Amazon GuardDuty for continuous threat detection across AWS accounts and workloads. It covers enabling protection plans for S3, EKS, EC2 runtime monitoring, and Lambda, interpreting finding severity levels, and building automated response workflows using EventBridge and Lambda.
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Deploys and configures Suricata IDS/IPS with Emerging Threats rulesets, EVE JSON logging, and custom rules for real-time network traffic inspection, threat detection, and integration with SIEM platforms for centralized security monitoring.
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Systematically collects, categorizes, and distributes indicators of compromise (IOCs) during and after security incidents to enable detection, blocking, and threat intelligence sharing. Covers network, host, email, and behavioral indicators using STIX/TAXII formats and threat intelligence platforms. Activates for requests involving IOC collection, indicator extraction, threat indicator sharing, compromise indicators, STIX export, or IOC enrichment.
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Build effective detection rules using Splunk Search Processing Language (SPL) correlation searches to identify security threats in SOC environments.
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Parses Software Bill of Materials (SBOM) in CycloneDX and SPDX JSON formats to identify supply chain vulnerabilities by correlating components against the NVD CVE database via the NVD 2.0 API. Builds dependency graphs, calculates risk scores, identifies transitive vulnerability paths, and generates compliance reports. Activates for requests involving SBOM analysis, software composition analysis, supply chain security assessment, dependency vulnerability scanning, CycloneDX/SPDX parsing, or CVE correlation.
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Analyzes Windows Security, System, and Sysmon event logs in Splunk to detect authentication attacks, privilege escalation, persistence mechanisms, and lateral movement using SPL queries mapped to MITRE ATT&CK techniques. Use when SOC analysts need to investigate Windows-based threats, build detection queries, or perform forensic timeline analysis of Windows endpoints and domain controllers.
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Queries Azure Monitor activity logs and sign-in logs via azure-monitor-query to detect suspicious administrative operations, impossible travel, privilege escalation, and resource modifications. Builds KQL queries for threat hunting in Azure environments. Use when investigating suspicious Azure tenant activity or building cloud SIEM detections.
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Analyzes DNS query logs to detect data exfiltration via DNS tunneling, DGA domain communication, and covert C2 channels using entropy analysis, query volume anomalies, and subdomain length detection in SIEM platforms. Use when SOC teams need to identify DNS-based threats that bypass traditional network security controls.
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