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Prices FX options and exotic structures with Garman-Kohlhagen, local volatility, and stochastic volatility models. Use when pricing FX derivatives, evaluating FX options, or modeling cross-currency products.
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Access a collection of open-source molecular design and structural biology tools on the Tamarind Bio platform, via its REST API or MCP server — no local GPUs required. Tamarind bundles popular open-source models for structure prediction (AlphaFold, Boltz, Chai, ESMFold), protein, binder, and de novo design (RFdiffusion, ProteinMPNN, BoltzGen), antibody and nanobody design and developability, protein-ligand docking (DiffDock, Autodock Vina), binding-affinity prediction, MSA generation, and molecular dynamics. Use when the user mentions Tamarind or tamarind.bio, wants to run any of these open-source tools in the cloud, references app.tamarind.bio/api or the x-api-key header, or needs to submit batches of sequences for structural or biophysical characterization.
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Django web framework conventions: app layout, settings split (base/local/production), URLconf with app namespacing, CBV and DRF ViewSets, DRF serializers and permissions, form validation, signals, Django admin registration, and middleware. Activated automatically by django-plugin/stack.md. Works alongside python-foundation:python-conventions and django-plugin:django-orm-patterns. Use this skill to: - Structure a Django project with multiple apps and correct URLconf hierarchy. - Write CBVs and DRF ViewSets with appropriate permissions and serializers. - Configure settings correctly for different environments. - Use signals for decoupled event handling between apps. - Register models in Django admin with useful list_display and search_fields. Do NOT use this skill for: - Django ORM model field finalization and migration patterns — see django-plugin:django-orm-patterns. - Python language idioms (type hints, dataclasses, enums) — see python-foundation:python-conventions. - Testing patterns — see python-foundation:pytest-testing.
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Add an external probabilistic classifier to a decision path without letting it take the path over. Covers finding the externally-graded rows you are already logging, measuring the confidence separation between the overrides it got right and the ones it got wrong, choosing an operating point your data licenses, failing open at the call site, and proving the whole arrangement offline with no API key. Applies to any service returning a score you can order — TypeSafe AI's System One models (Jev) are the worked example. Most of the method transfers to a local model or a second heuristic, with the parts that do not called out where they arise. Use when a rule-based path is wrong often enough to hurt, when someone proposes replacing a heuristic with a model, when a confidence threshold needs a defensible value, or when an oracle already in production has never been graded.
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This skill should be used to spawn specialized OpenAI Codex CLI subagents for code review, debugging, architecture analysis, security audits, refactoring, documentation, comparative evidence adjudication, and autonomous /goal runs. It adds each persona through process-local developer instructions while preserving the project's AGENTS.md chain, including during parallel launches. Supports GPT-6-Astra across low, medium, high, xhigh, max, and ultra reasoning with default or priority service tiers, plus GPT-5.6 and GPT-5.5 models. Triggers on 'delegate to Codex', 'Codex Astra', 'Astra subagent', 'Codex subagent', 'code review agent', 'security audit', 'refactor with Codex', 'goal run', 'autonomous goal', 'have Codex weigh this'.
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Generate 3D models from text or images via 5 providers: Meshy (text-to-3D, texturing, batch), fal.ai Hunyuan3D Pro ($0.225, PBR), WaveSpeedAI Rapid ($0.0225, bulk), Trellis 2 (poly control), and Local Depth (free offline ONNX depth maps + mesh). Includes GLB viewer. Triggers on 3D model, image to 3D, GLB, depth map, text to 3D, texturing, 3D asset, Meshy, Hunyuan.
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Create, inspect, analyze, and edit spreadsheets (`.xlsx`, `.xlsm`, `.csv`, `.tsv`) with local code execution. Use for formulas, formatting, charts, validation, financial models, and spreadsheet deliverables.
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Scaffold a new model provider for Forge — class implementation, registry wiring, providerEnum entry, local-catalog classification, and unit test with mocked transport. Use for anything under src/models/.
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Design and audit PFC 5.0 wall servo, loading-rate control, equilibrium checks, micro-to-macro calibration, two-target local solves, DOE campaigns, and independent confirmation for asphalt models.
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WatermelonDB reactive local database for React Native - schema, models, decorators, reactive queries, relations, writers/readers, batch operations, migrations, sync
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Add Ollama MCP server so the container agent can call local models and optionally manage the Ollama model library.
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Resolve CodeRabbit review feedback on a GitHub pull request. Collects every open CodeRabbit finding (inline threads, plus the nitpick and outside-diff findings packed into review bodies), judges and fixes each one against the real code with subagents, unifies fixes that share a pattern, commits locally, asks before pushing, then shows every reply draft linked to its finding and posts only on approval. Runs only on top-tier models. Use on "resolve the CodeRabbit feedback", "address coderabbit comments", "answer the rabbit", "fix what CodeRabbit flagged on
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Infers person-to-person transmission from pathogen genomes using outbreaker2, TransPhylo, phybreak, BadTrIP, SCOTTI, BEASTLIER, and SNP-distance / cluster-picker approaches (HIV-TRACE for HIV; transcluster). Defines outbreak clusters using pathogen-specific SNP thresholds (NOT a universal cutoff -- TB <=12 SNPs; MRSA <=15; C. difficile <=2; Klebsiella <=21), models within-host diversity and transmission bottlenecks, integrates contact-tracing data, distinguishes generation from serial interval, and attributes source via Bayesian source attribution (islandR). Use when investigating outbreaks for who-infected-whom, defining SNP-cluster outbreak definitions, accounting for unsampled intermediates, choosing between outbreaker2 (rich epi data) and TransPhylo (genomic-only after a dated phylogeny), running source attribution between host populations, calling HIV-TRACE thresholds appropriate to the local subtype, or distinguishing recent transmission from reactivation in TB or chronic HIV.
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Performs gene-level association from GWAS summary statistics via genetically predicted tissue expression using FUSION, PrediXcan, S-PrediXcan, S-MultiXcan, UTMOST, MOSTWAS, kTWAS, EpiXcan, TIGAR-V2, and probabilistic fine-mapping with FOCUS and MA-FOCUS. Use when running TWAS from GWAS sumstats, prioritising candidate causal genes from a GWAS lead locus, picking single-tissue vs cross-tissue models, identifying LD-induced TWAS false positives, choosing ancestry-matched prediction weights, fine-mapping co-regulated TWAS hits, or triangulating TWAS with cis-eQTL Mendelian randomization and colocalization to nominate a causal gene.
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Run the extended Corpo Net range suite across many models on one remote host with parallel isolated range instances, local Langfuse recording, bounded spend, and verified teardown. Use when asked to run, rerun, or scale a Corpo Net campaign; use run-ephemeral-hosts for the host contract and manage-remote-resources for billable resource ownership.
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Garanta estrutura válida de JSON/XML/código durante a geração, use modelos Pydantic para outputs type-safe, suporte modelos locais (Transformers, vLLM) e maximize velocidade de inferência com Outlines - biblioteca de geração estruturada da dottxt.ai
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Agent Media OS, the single skill for every media need in a HyperFrames project. Resolve BGM, SFX, image, icon, brand logo, voice, color grade, or LUT into a frozen local file or paste-ready block + ledger record (one verb, `resolve`); generate via TTS / music / image models when the catalog misses; produce voiceover, transcription, captions, and background removal through one shared audio engine; operate on media (cut / reframe / transform); and reuse assets across projects. Also use for vague feedback that real footage looks dark, flat, boring, should feel retro/camcorder/print/ASCII, needs privacy, or needs a media reveal.
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Add Ollama MCP server so the container agent can call local models and optionally manage the Ollama model library.
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Add Ollama MCP server so the container agent can call local models and optionally manage the Ollama model library.
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Attack Success Rate (360 runs 60 payloads 2 models ~3 reps) Paradigm gemma4-e2b (local, Ollama
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The AI Free tier gives you unlimited code completion and access to local AI models, as well as credit-based use of cloud-based AI assistance and our c
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Role-based multi-model strategy. The model catalog lives in a local configuration file instead of the skill text -- roles (thinker/decision-maker, long-running worker, draft generator, reviewer/acceptance, escalation), reasoning effort as an independent axis, mandatory review for draft models, provider switching for independent reviews, budgets, delegation flow, and cost/quality of small workers.
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Design and review native presenter classes in WordPress plugins without requiring better-data - converting DTOs or domain objects into REST arrays, admin table rows, JS config payloads, email variables, and public view models with allowlisted fields, context methods, redaction by default, locale/date/number formatting, no DTO mutation, and correct WordPress escaping boundaries. Use when adding FooPresenter, response mappers, admin-row arrays, wp_send_json payloads, rest_ensure_response data, wp_add_inline_script config, or when code returns raw DTOs, WP_Post, WC_Order, get_object_vars, json_encode, or unescaped HTML from controllers.
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Use when working with Contentful — contentful headless CMS management covering space and environment inventory, content type analysis, entry and asset monitoring, locale configuration, webhook tracking, API key auditing, and usage quota monitoring. Use when reviewing content models, investigating publishing issues, monitoring API usage, or auditing space access.
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