Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates.
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Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Build collaborative forensic incident timelines using Timesketch to ingest, normalize, and analyze multi-source event data for attack chain reconstruction and investigation documentation.
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Leverages Splunk Enterprise Security and SPL (Search Processing Language) to investigate security incidents through log correlation, timeline reconstruction, and anomaly detection. Covers Windows event logs, firewall logs, proxy logs, and authentication data analysis. Activates for requests involving Splunk investigation, SPL queries, SIEM log analysis, security event correlation, or log-based incident investigation.
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Parses and analyzes the Windows Amcache.hve registry hive to extract evidence of program execution, application installation, and driver loading for digital forensics investigations. Uses Eric Zimmerman's AmcacheParser and Timeline Explorer for artifact extraction, SHA-1 hash correlation with threat intel, and timeline reconstruction. Activates for requests involving Amcache forensics, program execution evidence, Windows artifact analysis, or application compatibility cache investigation.
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Uses the Linux Audit framework (auditd) with ausearch and aureport utilities to detect intrusion attempts, unauthorized access, privilege escalation, and suspicious system activity. Covers audit rule configuration, log querying, timeline reconstruction, and integration with SIEM platforms. Activates for requests involving auditd analysis, Linux audit log investigation, ausearch queries, aureport summaries, or host-based intrusion detection on Linux.
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Reverse engineer Go-compiled malware using Ghidra with specialized scripts for function recovery, string extraction, and type reconstruction in stripped Go binaries.
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Solana development patterns used in the Pump SDK — Anchor IDL-based program interaction, SPL Token and Token-2022 management, transaction construction with instruction composition, RPC batching, and cross-program coordination.
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Knowledge base from MIL-STD-881F (13 May 2022), DoD Standard Practice for Work Breakdown Structures for Defense Materiel Items. Use for Program/Contract/Subcontract WBS construction, 100% rule and dictionary discipline, commodity appendices A–J, Common Elements (K), sustainment CES reporting (L), Government ST&E (M), and RFP/post-award implementation. Technical planning & WBS and PM/measurement focus—not a cost manual substitute for CAPE policy.
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Knowledge base from the NASA Cost Estimating Handbook (CEH) v4.0. Use for NASA's 12-step, three-part cost estimating process (Project Definition, Cost Methodology, Cost Estimate); the WBS, CADRe, and ONCE data backbone; estimating methodologies (analogy, parametric/CER, engineering build-up, EVM, Delphi); ground rules and assumptions, data normalization and inflation (BY/CY/RY); the point-estimate-to-S-curve cost-risk chain and Unallocated Future Expense (UFE) reserves; Joint Cost and Schedule Confidence Level (JCL) analysis via probabilistic cost-loaded schedules; decision-support analyses (sensitivity, trade studies, make/lease-vs-buy, affordability, CAIV); and economic analysis (discounting, NPV, OMB Circular A-94). The cost-estimating complement to NASA's SE and risk packs. Does NOT reproduce the handbook's tool-specific procedures, worked examples, or appendix-depth methods (it names the appendices), nor cover full DoD/GAO cost guides, schedule construction, or formal risk management beyond the cost interface.
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Build comprehensive attack trees to visualize threat paths. Use when mapping attack scenarios, identifying defense gaps, or communicating security risks to stakeholders.
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Expert in LangGraph - the production-grade framework for building stateful, multi-actor AI applications. Covers graph construction, state management, cycles and branches, persistence with checkpointers, human-in-the-loop patterns, and the ReAct agent pattern.
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Coordinate evidence based reconstruction from scans, photos, plans, and measurements into a reviewable Blender architectural model, with photographic appearance, renders and portable browser delivery when requested.
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Use when cataloging or annotating visible construction in photographs or scan RGB, especially before registration or while the base model may be replaced.
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Collect and verify Google Street View exterior references for a building reconstruction, preserving panorama identity, imagery dates, attribution and viewpoint separately from calibrated scan evidence.
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Build comprehensive attack trees to visualize threat paths. Use when mapping attack scenarios, identifying defense gaps, or communicating security risks to stakeholders.
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Build comprehensive attack trees to visualize threat paths. Use when mapping attack scenarios, identifying defense gaps, or communicating security risks to stakeholders.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Design System Builder IA — Expert en construction de design systems (Storybook, tokens, component API, theming, Figma sync)
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Expert en construction de design systems avancés (tokens, composants, Storybook, Figma sync, versioning, theming)
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Expert en construction de communauté avancé (Discord, forums, ambassadors, engagement, monetization)
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Community Builder IA — Expert en construction de communautés (Discord, Telegram, engagement, moderation, growth loops).
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Expert en construction d'outils pour agents IA (function calling, tool schemas, MCP, validation, error handling)
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Break a design system into its constituent decisions and evaluate each one. Use when auditing design systems, evaluating consistency, or understanding how a product maintains quality at scale.
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Guide for dataset construction — SupervisedDatasetBuilder, RLDatasetBuilder, ChatDatasetBuilder, and custom dataset creation from JSONL, HuggingFace, or conversation data. Use when the user asks about datasets, data loading, data preparation, or custom data formats.
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