'engineer' 검색 결과

Data structures and algorithms for AI agent episodic memory. Covers vector stores (HNSW, IVF, PQ), temporal indexing, knowledge graphs with triple stores, hierarchical summarization, forgetting curves, working/long-term/ procedural memory, and memory consolidation. Deep analysis of MemGPT/Letta, Zep/Graphiti, Mem0, and the Stanford generative agents memory architecture. Teaches the CS fundamentals behind how agents remember, retrieve, and forget. Activate on: "agent memory", "episodic memory", "vector search algorithm", "HNSW", "memory retrieval", "forgetting curve", "knowledge graph memory", "MemGPT", "Letta", "Zep", "Mem0", "memory consolidation", "temporal retrieval", "agent long-term memory", "memory layer". NOT for: conversation protocol design (use agent-conversation-protocols), agent infrastructure selection (use agentic-infrastructure-2026), building RAG pipelines (use ai-engineer).

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Build face recognition systems with InsightFace, ArcFace, enrollment pipelines, HDBSCAN clustering, and privacy-compliant architecture. Activate on: face recognition, face enrollment, face clustering, identity verification, facial search. NOT for: general object detection (computer-vision-pipeline), emotion analysis (ai-engineer).

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Star schema, snowflake schema, SCD types, and Kimball methodology for analytical data modeling. Activate on: dimensional model, star schema, snowflake schema, SCD, fact table, dimension table, Kimball, grain, surrogate key. NOT for: dbt implementation (use dbt-analytics-engineer), warehouse tuning (use data-warehouse-optimizer).

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Snowflake, BigQuery, clustering, partitioning, and materialized views for warehouse performance. Activate on: Snowflake, BigQuery, Redshift, query optimization, clustering, partitioning, materialized view, warehouse cost, query profile. NOT for: dbt model structure (use dbt-analytics-engineer), data modeling (use dimensional-modeler).

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Great Expectations, dbt tests, anomaly detection, and data contracts for data quality. Activate on: data quality, data validation, Great Expectations, data contract, anomaly detection, SLA, freshness check, schema validation. NOT for: dbt model structure (use dbt-analytics-engineer), schema evolution (use schema-evolution-manager).

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Safe database migration manager for zero-downtime DDL changes and rollback plans. Activate on: database migration, schema change, DDL, rollback plan, zero-downtime migration, Prisma migrate, Drizzle kit, Flyway, column rename, table alter. NOT for: query optimization (use database-optimizer), ORM modeling (use data-pipeline-engineer), backup/restore (use devops-automator).

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OpenLineage, DataHub, Marquez for data lineage tracking and impact analysis. Activate on: data lineage, OpenLineage, DataHub, Marquez, impact analysis, data catalog, column lineage, data discovery. NOT for: data quality validation (use data-quality-guardian), dbt documentation (use dbt-analytics-engineer).

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Cognitive Systems Engineering design methodology for joint cognitive systems and human-centered automation

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Review of Cognitive Systems Engineering applications and current practice in safety-critical domains

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Treat tokens as a coding swarm's cost-of-goods-sold and legibility engine while accounting for finite subscription allowance when per-call price is unknown. Covers provider windows, remaining-usage evidence, burn forecasts, preemptive checkpoint/model switching, per-agent budgets, compaction, shared digests, context degradation, and spend metering. Activate on: "token budget", "context budget", "compaction strategy", "briefing as compression", "context rot", "summarization collapse", "COGS for agents", "subscription usage remaining", "five-hour or weekly limit", "burn forecast", "model switch before limit", or "/context-economics-for-agent-swarms". NOT for: memory architecture (use always-on-agent-architecture), single-prompt wording (use prompt-engineer), mechanism-design proofs (use nisan-et-al-2007-algorithmic-game-theory), physical containment (use sandboxed-adversarial-test-harness), or production rebodiment and fencing (use agent-resurrection-and-body-continuity).

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Expert API designer for REST, GraphQL, gRPC architectures. Activate on: API design, REST API, GraphQL schema, gRPC service, OpenAPI, Swagger, API versioning, endpoint design, rate limiting, OAuth flow. NOT for: database schema (use data-pipeline-engineer), frontend consumption (use web-design-expert), deployment (use devops-automator).

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Research AI coding assistant products, audiences, user stories, social proof, hacks, and unmet needs for apps like Cursor, Claude Code, Codex, Warp Code, Devin, Windsurf, GitHub Copilot, Cline, Aider, and homegrown agent stacks. Use when designing or positioning agentic developer tools, Port Daddy Agent Harbor, swarm consoles, background coding agents, or competitive/product research for AI software engineering. NOT for implementing the coding agent runtime, generic market research, or UX mockups without developer workflow evidence.

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Cryptographic security for agentic systems — zero-trust agent networking, signed message envelopes (JWS/JWE), capability-based security (ocaps), Merkle tree audit trails, WASM sandboxing, and formal verification. Covers CLI dev tool security, mTLS between agents, permission boundaries (least privilege for AI agents), and supply chain security for skills/plugins. Activate on: "agent security", "zero trust agents", "secure agent communication", "capability-based security", "ocap", "signed messages between agents", "agent audit trail", "sandbox agent execution", "agent permissions", "mTLS agents", "cryptographic verification", "agent supply chain", "OWASP agentic", "prove agent did X", "tamper-proof agent logs". NOT for: application-level SAST scanning (use security-auditor), network firewall rules (use infrastructure), SOC2/HIPAA compliance (organizational), or prompt injection defense (use prompt-engineer).

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Apache Airflow DAGs, operators, SLA monitoring, and workflow orchestration. Activate on: Airflow, DAG, operator, sensor, scheduler, task dependency, SLA, backfill, XCom. NOT for: dbt transformations (use dbt-analytics-engineer), streaming pipelines (use streaming-pipeline-architect).

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Build production-ready LLM applications, advanced RAG systems, and intelligent agents. Implements vector search, multimodal AI, agent orchestration, and enterprise AI integrations. Use PROACTIVELY for LLM features, chatbots, AI agents, or AI-powered applications.

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Find and identify the CCSPlayerPawn_SnapEyeAngles function in CS2 server binary using IDA Pro MCP. Use this skill when reverse engineering CS2 server.dll or libserver.so to locate the non-virtual SnapEyeAngles method. It is the one caller of the shared apply helper (CCSPlayerPawn_ApplyEyeAngleNetworkChange) that is NOT CCSPlayerPawn_SnapViewAngles. Emits a unique IDA-style byte signature and a func YAML. Mirrors the find-CCSPlayerPawn_SnapEyeAngles.py preprocessor (xref_funcs apply-helper, exclude_funcs SnapViewAngles). Trigger: CCSPlayerPawn_SnapEyeAngles, SnapEyeAngles

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Find and identify the CDecoyProjectile_Create factory in CS2 server binary using IDA Pro MCP. Use this skill when reverse engineering CS2 server.dll or libserver.so to locate the decoy projectile spawn factory. It is a non-virtual, direct-call static factory found via the entity classname string "decoy_projectile" it references (excluding the RTTI class string "CDecoyProjectile"). Emits a unique IDA-style byte signature and a func YAML. Mirrors the find-CDecoyProjectile_Create.py preprocessor (xref_strings FULLMATCH:decoy_projectile). Trigger: CDecoyProjectile_Create, CDecoyProjectile::Create, decoy projectile Create

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Find and identify the CCSPlayerPawn_SnapViewAngles function in CS2 server binary using IDA Pro MCP. Use this skill when reverse engineering CS2 server.dll or libserver.so to locate the non-virtual SnapViewAngles method, anchored on the "setang" console-command usage string and its non-teleport call branch. Emits a unique IDA-style byte signature and a func YAML. Trigger: CCSPlayerPawn_SnapViewAngles, SnapViewAngles

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Find and patch the water jump velocity inside CCSPlayer_MovementServices_CheckJumpButton in CS2 binary using IDA Pro MCP. This patch changes the water jump velocity from 100.0f to 145.0f by modifying the immediate operand of a mov instruction. Use this skill when reverse engineering CS2 server.dll or libserver.so to locate and patch the water jump height value. Trigger: water jump patch, CheckJumpButton water velocity, jump height patch, water jump 145

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Find and identify the CCSGameRules_PostCleanUp function in CS2 server binary using IDA Pro MCP. Use this skill when reverse engineering CS2 server.dll or libserver.so to locate the post-round entity-cleanup routine. It is non-virtual and has no unique string of its own, so it is found via the CCSGameRules_ResetRound predecessor: PostCleanUp is the entity-cleanup call ResetRound makes. Emits a unique IDA-style byte signature and a func YAML. Mirrors the find-CCSGameRules_PostCleanUp.py preprocessor (LLM_DECOMPILE CCSGameRules_ResetRound). Trigger: CCSGameRules_PostCleanUp, PostCleanUp, CGameRules::PostCleanUp

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Find and identify the CCSNavArea_IsValidNavMesh function in CS2 server binary using IDA Pro MCP. Use this skill when reverse engineering CS2 server.dll or libserver.so to locate the nav-mesh validity predicate. It is a tiny non-virtual-looking helper that returns `g_pNavMesh != nullptr` (15 bytes), referenced only from a vtable slot, with no debug string of its own. Emits a unique IDA-style byte signature and a func YAML. Mirrors the find-CCSNavArea_IsValidNavMesh.py preprocessor (xref_gvs g_pNavMesh intersected with the tail signature `48 83 38 ? 0F 95 C0 C3`). Trigger: CCSNavArea_IsValidNavMesh, IsValidNavMesh, g_pNavMesh predicate

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Find and identify the CCSPlayer_WeaponServices_EquipWeapon function and the CCSPlayer_WeaponServices_CanUse virtual function in CS2 binary using IDA Pro MCP. Use this skill when reverse engineering CS2 server.dll or libserver.so to locate the weapon-equip helper and the "is this weapon usable right now" vfunc by RTTI-walking the CCSPlayer_WeaponServices vtable and confirming each candidate's decompiled body against the known CCSPlayer_WeaponServices_PickupItem anchor's callee shapes. Trigger: CCSPlayer_WeaponServices_EquipWeapon, CCSPlayer_WeaponServices_CanUse

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Find and identify the CCSPlayer_ItemServices_GiveNamedItem virtual function, the CCSPlayer_WeaponServices_Weapon_GetSlot helper, and the CBasePlayerPawn_RemovePlayerItem helper in CS2 binary using IDA Pro MCP. Use this skill when reverse engineering CS2 server.dll or libserver.so to locate GiveNamedItem by RTTI-walking the CCSPlayer_ItemServices vtable, then to locate the other two by decompiling the already-known CCSPlayer_ItemServices_GiveDefaultItems anchor and matching its callees' argument shapes and inventory-slot bookkeeping semantics. Trigger: CCSPlayer_ItemServices_GiveNamedItem, CCSPlayer_WeaponServices_Weapon_GetSlot, CBasePlayerPawn_RemovePlayerItem

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Find and identify the CCSGameRules_ResetRound function in CS2 server binary using IDA Pro MCP. Use this skill when reverse engineering CS2 server.dll or libserver.so to locate the round-reset routine. It is the only function that references the "GMR_ResetRound\n" debug log string, and is the predecessor anchor for find-CCSGameRules_PostCleanUp (which it calls). Emits a unique IDA-style byte signature and a func YAML. Mirrors the find-CCSGameRules_ResetRound.py preprocessor (xref_strings "GMR_ResetRound\n"). Trigger: CCSGameRules_ResetRound, ResetRound, GMR_ResetRound

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