Finances
Finances personals, pressupostos i eines financeres
cost-optimizer
curiositech
Tracks cumulative LLM costs across DAG execution and makes real-time decisions to stay within budget. Downgrades models, skips optional nodes, or stops early when cost exceeds thresholds. Use when managing execution budgets, analyzing cost breakdowns, or optimizing model routing for cost. Activate on "cost budget", "too expensive", "reduce cost", "cost optimization", "model downgrade", "budget exceeded". NOT for LLM model selection logic (use llm-router), pricing comparisons across providers, or billing/invoicing.
always-on-agent-safety
curiositech
Safety, privacy, cost management, and frank advice for building always-on AI agents with episodic memory. Covers data hygiene, privacy risk surfaces, runaway cost prevention, scope creep, psychological effects of persistent AI companions, and responsible deployment patterns. This is the skill that tells you what can go wrong and how to prevent it. Activate on: "agent safety", "always-on agent privacy", "agent cost control", "persistent agent risks", "AI companion safety", "agent data hygiene", "runaway agent costs", "parasocial AI risk", "/always-on-agent-safety". NOT for: architecture design (use always-on-agent-architecture), input design (use always-on-agent-inputs), application brainstorming (use always-on-agent-applications), healthcare compliance specifically (use hipaa-compliance).
setup-specialists
xtrm-dev
First-run setup workflow for a Specialists install. Use when the user says "setup specialists", "configure specialists", "change the specialist models", "models shipped do not exist on my machine", "set notes_mode globally", "opt out of GitNexus for one specialist", "sp init --global", "sp edit --global", or asks how to apply specialist overrides across all repos at once. Verifies local Pi models, explains the 3-layer field merge (package canonical → ~/.config/specialists/user.json → .specialists/user), bootstraps the global user.json via sp init --global, applies model + behavior overrides via sp edit --global, and validates with sp doctor --specialists.
agent-context-partitioner
curiositech
Algorithmic skill for designing evidence-backed partitions of LLM context or task DAGs across K agents. Covers two modes: (A) online/reactive spawning under context pressure, and (B) static pre-planned DAG execution with graph min-cut optimization. Encodes algorithms for sequence-stable clustering, dynamic K selection, token-budget-aware partitioning, and handoff protocol design. Use when designing multi-agent systems, deciding when and how many agents to spawn, or optimizing a task DAG for token efficiency. NOT for one bounded task that does not benefit from parallelism, runtime scheduling or authorization policy, or comparing vectors whose embedding-space identities are unknown or incompatible.
net-payments
ai-2070
"Use this skill when the user is integrating the Net Payments SDK (net-payments Rust crate, net_payments lib, or the Python/Node CapabilityGateway + PaymentProvider payment surface) — x402-native payments for the Net mesh. Covers pricing a capability at discovery (net.pricing.terms@1), issuing signed quotes (net.payment.quote@1), the provider lifecycle engine (PaymentEngine: quote → verify → settle → tiered verification → billing), the caller flow (CallerPaymentFlow / ProviderChannel: pricing → spend policy → payload → pay), paid agent-to-agent tasks (prepare → purchase → submit: serve_a2a_configured, redeem_for_task on a reservation-bound quote, A2aCallerFlow + a durable A2aPurchaseStore), facilitators (mock + the real HTTP verify/settle client, config packs, auth), tiered verification (observed confirmed(n) final) with the independent on-chain ChainChecker, reorg handling, the settlement signer seam (SchemeSigner / ExternalSigner / ExternalSvmSigner / ExternalXrplSigner — EIP-3009 exact-EVM, SPL exact-SVM, exact-XRPL; keys never cross the boundary), the spend policy engine (budgets, delegation inheritance, requires_payment_approval), immutable billing events + the billing stream, network enablement (CAIP-2/CAIP-19, the signed asset registry, Base/Solana/xrpl config-not-code ladder), the outbound HTTP 402 two-way door, the failure schematic (net.payment.failure@1) that rides denials beside the human error, the multi-language SDK surfaces (Python AND Node/TS at full demand+supply parity with Rust — CapabilityGateway, paid PaymentProvider + buildPricingTerms, HTTP-402 client, eip155/svm/xrpl signers, approval verbs, free publishTools; paid A2A is Rust + Python only), and cross-language golden vectors + conformance. Triggers on imports of net-payments / net_payments; on x402, PaymentEngine, PaymentQuote, PricingTerms, net.payment. / net.billing. / net.settlement.*, X402Carry, VerificationTier, confirmed(n), reorg, SchemeSigner, ExternalSigner, ExternalSvmSigner, SvmTransferIntent, SPL/Solana settlement, SpendPolicyEngine, BillingEvent, MeshPaymentChannel, serve_payments, serve_a2a_configured, redeem_for_task, A2aCallerFlow, prepare_task/purchase_task/submit_task, gated_invoke, requires_payment_approval, CAIP-2/CAIP-19, HttpFacilitator, EIP-3009, HTTP 402; and on phrases like 'price a capability', 'charge for a tool', 'charge for an agent task', 'sell bounded work to another agent', 'paid A2A', 'pay to invoke', 'settle on Base/Solana', 'verify a payment on-chain', 'spend limit / budget', 'approve a payment', 'pay an x402 API'. Net signs the commercial facts around invocation; it does NOT custody funds, process payments, issue invoices, or move money. Skip for unrelated event-bus / mesh work (the net-event-bus skill) or for editing payments' own internals unless the task is payments integration."
closed-form-marbling-renderer
curiositech
Render mathematically-faithful Turkish marbling (Ebru) and paper-marbling with closed-form coordinate-deformation maps — a drop is a radial outward push, a comb/tine is a decaying shear, all composed as homeomorphisms over colored region boundaries. No fluid solver, runs 60fps on a 2D canvas. Use when building a marbling/Ebru toy or generative-art renderer, implementing drop/comb/wave/swirl deformations, scripting traditional patterns (Battal, Gel-Git, Şal, Bülbül Yuvası), keeping combed edges crisp via adaptive resampling, modeling ox-gall shouldering for crisp ring-in-ring drops, or exporting high-DPI marbled prints. NOT for real fluid / Navier-Stokes simulation, metaball / alpha-blended "smoke" blob effects, raster image-processing filters, or non-marbling generative art.
cost-accrual-tracker
curiositech
Track real-time API cost accrual during LLM execution. Activate on 'cost tracking', 'token usage', 'API costs', 'budget monitoring', 'usage metrics'. NOT for cost estimation, pricing tiers, or billing systems.
agentic-patterns
curiositech
Fundamental patterns for effective agentic behavior. Teaches decomposition, tool orchestration, error recovery, context management, quality self-assessment, and knowing when to stop. Model-agnostic principles that make any agent more effective regardless of domain. Activate on: "how should I structure this agent", "agentic workflow", "agent patterns", "multi-step task", "tool orchestration", "/agentic-patterns", "decompose this", "agent best practices", "chain of actions", "when should the agent stop", "agent loop design". NOT for: creating agent infrastructure (use agent-creator), building DAGs (use jury_rig-architect), specific tool implementation.
bellifemine-2007-jade-fipa
curiositech
JADE platform for building FIPA-compliant multi-agent systems with standardized agent communication
security-pattern-check
kjgarza
Identify security vulnerabilities and anti-patterns providing feedback on security issues a senior developer would catch. Use when user mentions security/vulnerability/safety concerns, code involves user input/authentication/data access, working with sensitive data (passwords/PII/financial), code includes SQL queries/file operations/external API calls, user asks about security best practices, or security-sensitive files are being modified (auth, payment, data access).
symfony-api-platform-filters
data219
Implement API Platform filters for search, date ranges, boolean, and custom filtering with proper indexing
circuit-breakers-and-retries
curiositech
Building resilient distributed systems with circuit breakers, retries with full-jitter exponential backoff, retry budgets (per-request 3-attempt + per-client 10% ratio per Google SRE), deadline propagation, and the cascading-failure math (4 layers × 3 retries = 64x amplification). Grounded in Resilience4j, Microsoft Cloud Patterns, AWS Architecture Blog (Marc Brooker), and Google SRE Book. NOT for server-side rate limiting, bulkhead isolation, backpressure protocols, or database-specific retry.
cursor-adversarial-review
aarontzeng
Run a read-only challenge review through Cursor's CLI (cursor-agent) in ask mode. Use when the user asks for a review via Cursor, or when the cross-family rule needs a reviewer family the standalone CLIs cannot field — one paid adapter serving GPT, Claude, Grok, Kimi, Composer, and auto.
dev-lead
aarontzeng
Orchestrate a feature or PR end-to-end as the lead — dispatch implementation to a delegate family based on task risk, model capability, and remaining quota; run bounded adversarial-review rounds with cross-family reviewers; verify everything independently; and hold the merge gate. Use when the user wants a whole feature/fix delegated and supervised, rather than a single implement or review pass.
always-on-agent-inputs
curiositech
How to design contextual inputs for an always-on AI agent with episodic memory. Covers what data to feed the agent, how to structure observations and triggers, ambient context capture (screen, audio, calendar), context window budgeting, and retrieval strategies that keep the agent grounded in what's actually happening. Activate on: "what should the agent observe", "context inputs for agent", "ambient context capture", "agent triggers", "agent input design", "screenpipe integration", "context window budget", "what data to feed my agent", "/always-on-agent-inputs". NOT for: memory architecture and storage (use always-on-agent-architecture), application ideas (use always-on-agent-applications), safety concerns (use always-on-agent-safety).
agent-interchange-formats
curiositech
Data structures and serialization formats for agent-to-agent communication. Covers message envelopes, structured output schemas, capability declarations, task handoff payloads, error/retry signaling, and context windows as data structures. Deep comparison of A2A protocol, MCP, OpenAI function calling, and LangChain message types. Teaches when to use rigid schemas vs free-form with validation, typed vs untyped, streaming vs batch. Activate on: "agent message format", "agent communication schema", "agent-to-agent protocol", "A2A protocol", "MCP message format", "structured output for agents", "agent interop", "interchange format", "agent serialization", "task handoff format", "capability declaration". NOT for: what agents say to each other (use agent-conversation-protocols), orchestration topology (use multi-agent-coordination), building agent infrastructure (use agentic-infrastructure-2026).
context-economics-for-agent-swarms
curiositech
Treat tokens as a coding swarm's cost-of-goods-sold AND its legibility engine. Covers per-agent context budgeting, compaction strategies (in-context summarization, structured note-taking, sub-agent isolation), the shared digest as compaction-for-humans- and-agents, the context-degradation cascade (lost-in-the-middle, context rot, recursive- summarization collapse), and mechanism design for metering token spend across a fleet. Activate on: "token budget", "context budget per agent", "compaction strategy", "digest / briefing as compression", "context window degradation / context rot", "summarization collapse", "COGS for agents", "metering agent token spend", "pheromone decay as forgetting", "/context-economics-for-agent-swarms". NOT for: memory storage architecture (use always-on-agent-architecture), single-prompt wording (use prompt-engineer), pure mechanism-design proofs (use nisan-et-al-2007-algorithmic-game-theory).
performance-budget-setter
patricio0312rev
Defines measurable performance budgets for bundle size, API latency, database queries, and render times. Provides enforcement strategies and monitoring plans. Use for "performance budgets", "performance monitoring", "web vitals", or "optimization targets".
agentic-calendar-coordination
curiositech
Design scheduling agents. Use for timezone-safe negotiation, focus protection, and privacy-safe free-busy handling. NOT for calendar UI, project planning, or general agent architecture.
morning-weather
rolandcanyon-cmd
Fetch today's weather from Tempest and Ambient Weather stations and send it via iMessage
us-gov-shutdown-tracker
Mann1988
Track and analyze US government shutdown liquidity impacts by monitoring TGA (Treasury General Account), bank reserves, EFFR, and SOFR data from FRED API. Use when user wants to (1) analyze current or past government shutdown effects on financial markets, (2) track liquidity conditions during fiscal policy disruptions, (3) assess "stealth tightening" effects, (4) compare shutdown episodes across different monetary policy regimes (QE vs QT), or (5) generate liquidity stress reports with historical context. Recommended usage frequency is weekly on Wednesdays after TGA/reserve data releases.
alphago-deep-rl
curiositech
Apply AlphaGo-style patterns: learned priors plus search, mixed evaluators, self-play, and asynchronous fast/slow loops. Use for intractable search and compute allocation. NOT for basic supervised learning, tractable optimization, or domains without search bottlenecks.
product-roadmap-focus
curiositech
"Chooses the most important product or roadmap work under ADHD, founder, budget, and multi-agent constraints. Use when asking what to work on next, prioritizing a roadmap, cutting scope, choosing an MVP slice, or deciding whether to split work across agents. NOT for executing an already-chosen task, generic project status reporting, personal financial advice, or long unbounded brainstorming."
opencode-adversarial-review
aarontzeng
Run an adversarial (red-team) review through the OpenCode CLI's free model pool (muse-spark, Nemotron, stealth models) under a machine-enforced read-only permission config. Use when a HIGH-risk change needs a second cross-family reviewer without spending paid quota, or as the cheap extra pair of eyes beside a primary review.