Results for “solver”

Work through convex optimization problems by checking convexity, putting objectives and constraints into a standard form, and choosing a solver. The skill provides SciPy examples and outlines checks for constraint satisfaction and mathematical conditions used to assess optimality.

• Checking whether an objective and its constraints are convex
• Putting a maximization problem into standard minimization form
• Choosing a solver for linear, quadratic, or semidefinite problems

Nonlinear optimization with CasADi and IPOPT solver. Use when building and solving NLP problems: defining symbolic variables, adding nonlinear constraints, setting solver options, handling multiple initializations, and extracting solutions. Covers power systems optimization patterns including per-unit scaling and complex number formulations.

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S-parameters, insertion loss, fields, currents, mesh control, and solver selection for RF PCB performance validation. TRIGGER: user asks to compute S-parameters, analyze insertion/return loss, extract fields or currents, compare MoM vs FEM, or control mesh for any RF PCB component. Invoke BEFORE writing sparameters() or solver code — API is non-obvious. SKIP: designing or creating components (use the specific matlab-design-pcb-* skill), material/stackup setup only (use matlab-manage-pcb-material), optimization sweeps (use matlab-optimize-pcb-design), PDN/IR-drop analysis (use matlab-analyze-pcb-pdn).

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数学建模竞赛论文写作全流程指导。覆盖国赛(CUMCM)和美赛(MCM/ICM)，从论文结构规划、各章节撰写、模型检验、参考文献规范到最终格式检查。与math-modeling-solver形成"解题→写作"配对——可接收solver输出的论文草稿片段直接展开写作。当用户提及数学建模论文写作、建模比赛、国赛/美赛/电工杯/亚太杯/深圳杯/华为杯论文、CUMCM、MCM/ICM、数模论文结构、摘要写作、模型检验、灵敏度分析、latex建模模板、word建模排版、Memo/Letter写作、模型命名、Our Work流程图，或需要写/修改/优化/检查建模论文的任何部分时，都必须使用此 skill。

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Build and configure a GraphQL API backed by Neo4j using @neo4j/graphql v7 (current) or v5 (LTS). Covers Neo4jGraphQL constructor, getSchema(), assertIndexesAndConstraints(), type definitions with @node, @relationship (IN/OUT/UNDIRECTED), @cypher for custom resolvers, @authorization/@authentication for JWT/JWKS security, auto-generated queries/mutations, OGM programmatic access, subscriptions via CDC, and Apollo Federation. Use when writing typeDefs, securing fields, or wiring Neo4j to Apollo Server. Does NOT handle raw Cypher outside resolvers — use neo4j-cypher-skill. Does NOT cover Spring Data Neo4j entity mapping — use neo4j-spring-data-skill.

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Expert guide for mathematical formal verification, SMT solver constraints (Z3, Dafny, TLA+), invariant theorem proving for FinTech billing state machines, RBAC/ABAC authorization, and zero-violation architecture / Panduan ahli verifikasi formal matematis, SMT solver (Z3, Dafny, TLA+), pembuktian invarian state machine billing FinTech, otorisasi RBAC/ABAC, dan arsitektur zero-violation.

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Investigate one Anabasis v2 campaign from its log and turn what it shows into findings with one owner each. Answers whether a comparison's reading (step, no-step, not-scored) may be believed, whether a fail was the solver's or the exam's, whether the harness could know the exam, whether the tasks bracket the solver, whether the campaign is climbing, and where the hours and dollars went. Reads evidence; starts no solve, session or round, and changes no verdict.

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Pattern for adding derived edge types in the Grafema Rust orchestrator (main.rs). Use when: (1) need to create new graph edges derived from existing edges (e.g., MODULE-level DEPENDS_ON from IMPORTS_FROM), (2) Datalog joins on large edge sets time out, (3) adding enrichment steps that combine data from multiple resolver outputs, (4) need to understand how resolver outputs flow through the orchestrator pipeline.

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Use when legacy prompts or older framework flows reference `build-error-resolver` and you need the modern runtime to resolve that capability cleanly.

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Covers object-level authorization bypass in GraphQL APIs where introspection reveals hidden fields or mutations that accept arbitrary user/resource IDs without ownership checks. Trigger on keywords like "GraphQL", "query", "mutation", "introspection", "resolver", "node ID", "relay", "object type", "schema", "batching", or "alias". Applies to dual-stack REST+GraphQL apps, Relay-style global IDs, and unauthenticated resolvers.

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Einmaliger Tasksolver+Writer+Maintainer-Durchlauf fuer den Projektordner, in dem die Session gerade sowieso gearbeitet hat (inkl. Unterordner) — kein systemweiter Sweep. Loest offene triviale/autonome Register-Punkte, aktualisiert Dokumentation auf den gemessenen Ist-Stand (im Projekt UND in der Root der Pipeline, in der das Projekt liegt) und raeumt Strays/Temp- Dateien nach dem Papierkorb-Prinzip weg. Nutze diesen Skill bei /tidy-up, "raeum das Projekt auf", "mach hier sauber bevor wir weitermachen", am Ende einer Arbeitssitzung an einem Projekt, oder als faellige autonome Aufgabe innerhalb von /work-autonomous + /goal.

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Z3 SMT solver ile CTF constraint çözme — byte equations, hash collision, validator bypass

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CTF challenge otomatik cozum pipeline'i. 6 asama: zip'i ac, siniflandir, coz, flag topla, writeup olustur. /auto-solve komutuyla cagrilir.

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Training patterns for autoregressive neural PDE solvers (FNO, DeepONet, CNO). Covers rollout training, noise injection for stability, multi-component loss functions (H1, frequency-sensitive, boundary-aware), per-channel normalization for coupled multi-variable systems, and the PDEBench nRMSE metric. Use when training any neural operator that predicts time-dependent PDE solutions.

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Designs GraphQL schemas with types, queries, mutations, subscriptions, resolvers, and DataLoader patterns for efficient data fetching. Use when users request "GraphQL API", "schema design", "GraphQL setup", "resolvers", or "Apollo Server".

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Plan and review home network changes before altering settings. The skill checks VLANs, which separate device groups, local DNS filtering, and VPN access, then organizes staged changes, validation checks, and recovery steps.

• Separating trusted, IoT, and guest devices
• Planning a move to local DNS filtering
• Reviewing remote VPN access

Work on advanced RuView sensing with signals from multiple WiFi nodes. Explore position estimation, three-dimensional occupancy reconstruction, changes in movement patterns over time, and defenses against suspicious signals, with guidance on implementation modules and validation.

• Combining WiFi observations from multiple nodes
• Reconstructing occupied space with RF tomography
• Studying long-term changes in movement patterns

Analyze application and system performance to find bottlenecks, the points that slow processing. Use resource usage and performance data to plan improvements to resource allocation, load balancing, caching, and algorithms, then compare results after changes.

• Investigating slow application processing
• Reviewing CPU and memory allocation
• Improving workload distribution across nodes

Turn complex goals into actionable plans by mapping dependencies, prioritizing tasks, and allocating time, budget, and people. Supports coordination across multiple agents and revises plans when progress or constraints change.

• Planning a feature launch under a deadline
• Allocating people and budget across competing goals
• Revising plans when requirements change

Analyze networks of people, web pages, or systems using PageRank, a method that scores importance from connections. Identify influential nodes and communities, generate personalized recommendations, and examine communication bottlenecks to guide network improvements.

• Finding influential users and communities on social networks
• Analyzing links and page importance on a website
• Generating recommendations based on user preferences

Design and implement ways for multiple agents or distributed computers to agree on decisions. Covers weighted voting, task allocation, coordination, and protocols that handle faulty or malicious participants, with tools for mathematical analysis.

• Design agreement protocols for multiple agents
• Build voting systems with weighted influence
• Review protocols for faulty or malicious nodes

Calculate portfolio weights from a covariance matrix, which describes how asset returns move together, and expected returns using Conjugate Gradient. Save the weights with the solver used, numerical error, and timing so the calculation can be checked later.

• Calculating portfolio weights from supplied return data
• Comparing Conjugate Gradient with the legacy calculation
• Keeping records of weights and calculation details

Connect syncable entity components within Twenty server internals and expose them through GraphQL, an API query interface. It guides NestJS module registration, business services, response data conversion, and consistent handling of validation and execution errors.

• Register builders, validators, and action handlers in NestJS modules
• Connect entity creation to validation and migration execution
• Expose entities through GraphQL with response data conversion

Validates skill files and registration consistency, then checks project tests and system health. Compares failures with recent changes to distinguish regressions, outdated tests, intermittent failures, and infrastructure issues, producing a report that tracks results over time.

• Validating definitions and registration for new skills
• Running daily tests and system health checks
• Classifying failures after code changes