Claude Skills by thedixitjain

Assess portfolio risk using npx neural-trader — VaR, CVaR, Sharpe, position sizing, circuit breaker status

Generate trading signals using npx neural-trader anomaly detection engine with Z-score scoring and neural prediction

A trading journal that captures the decision, not just the fill: thesis, plan, and emotion at the moment of entry, written to the user's own Notion database; reviews grade decisions, not P&L.

Use when the user wants to search Upwork, qualify roles, draft proposals, submit applications, or continue an active Upwork application session. This skill uses a Chrome CDP workflow, payload JSON files, sequential browser actions, connect-budget tracking, and final success confirmation through Upwork proposal URLs.

Design pricing models that developers understand, accept, and can predict. Trigger phrases: usage-based pricing, API pricing, metered billing, developer pricing, pricing page, cost calculator, pay as you go, pricing transparency, competitive pricing, developer billing

'Optimize Vast.ai GPU cloud costs through smart instance selection and lifecycle management. Use when analyzing GPU spending, reducing training costs, or implementing budget controls for Vast.ai workloads. Trigger with phrases like \"vastai cost\", \"vastai billing\", \"reduce vastai costs\", \"vastai pricing\", \"vastai budget\". '

Use when reviewing, scoring, or auditing third-party SaaS / vendor relationships — running a vendor scorecard with industry tuning, tracking SLA compliance with credit-claim flags, classifying third-party risk across 4 risk vectors, preparing a tier-1 vendor review, or auditing the SaaS portfolio. Forks context so large vendor catalogs (50-500 line items) and SLA logs don't pollute the parent thread. Triggers on \"vendor SLA\", \"vendor scorecard\", \"third-party risk\", \"TPRM\", \"vendor re...

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Use when auditing an IEEE VIS full-paper submission for PCS readiness, covering the abstract-then-paper two-deadline structure under the VGTC society, the IEEE VGTC/TVCG 9+2 page budget, author-optional double-blind anonymization, the supplemental-material one-week window, and desk-reject triage before the AoE cutoff for a paper that will publish in IEEE TVCG.

Use when deciding what belongs in an IEEE VIS paper body versus its supplemental materials, covering the VGTC/TVCG 9+2 page budget, the supplemental video that VIS reviewers routinely watch, the one-week supplemental deadline extension, double-blind supplemental anonymization, and how to split a visualization paper between the reviewed pages and the archive.

VP of Engineering advisory for startups: delivery throughput (DORA 4 metrics + bottleneck identification), engineering hiring funnel (sourcing → screen → onsite → offer conversion + time-to-fill + pipeline gap), engineering team structure (squad/tribe/chapter design + tech-lead manager-trigger thresholds), and production discipline (on-call, deployment cadence, postmortem culture). Use when sprint velocity is dropping, eng hiring is broken, team structure is unclear, or deciding when to add a...

Agente que simula Warren Buffett — o maior investidor do seculo XX e XXI, CEO da Berkshire Hathaway, discipulo de Benjamin Graham e socio intelectual de Charlie Munger.

Automate Wave Accounting tasks via Rube MCP (Composio): invoices, customers, payments, and small business accounting. Always search tools first for current schemas.

Wave Accounting toolkit is not currently available as a native integration. No Wave-specific tools were found in the Composio platform. This skill is a placeholder pending future integration.

Use when preparing a Web Conference (WWW) camera-ready after acceptance, covering the uniform 12-page/8-content proceedings budget, de-anonymization and restored acknowledgements, ACM e-rights and TAPS production, ACM Open cost exposure, author registration, and the artifact-badging submission that rides along with the final files.

'Optimize Webflow costs through plan selection, CDN read optimization, bulk endpoint usage, and API usage monitoring with budget alerts. Use when analyzing Webflow billing, reducing API costs, or implementing usage monitoring for Webflow integrations. Trigger with phrases like \"webflow cost\", \"webflow billing\", \"reduce webflow costs\", \"webflow pricing\", \"webflow budget\". '

Cleans a weekly CRM export and produces a regional sales summary. Activates when the user asks to clean a CRM export, deduplicate sales rows, calculate regional totals, or generate a weekly sales report from a CSV.

'Optimize Windsurf licensing costs through seat management, tier selection, and credit monitoring. Use when analyzing Windsurf billing, reducing per-seat costs, or implementing usage monitoring and budget controls. Trigger with phrases like \"windsurf cost\", \"windsurf billing\", \"reduce windsurf costs\", \"windsurf pricing\", \"windsurf budget\". '

'Understand and manage Windsurf credit system, usage limits, and model selection. Use when running out of credits, optimizing AI usage costs, or understanding the credit-per-model pricing structure. Trigger with phrases like \"windsurf credits\", \"windsurf rate limit\", \"windsurf usage\", \"windsurf out of credits\", \"windsurf model costs\". '

Primary entry point for the spec-superflow state-machine workflow. Invoke when the user is inside an active spec-superflow change directory (look for .spec-superflow.yaml, changes/<name>/, proposal.md, specs/, design.md, tasks.md, or execution-contract.md) and asks to start, continue, resume, implement, plan, or figure out the next workflow step. Also invoke when the user explicitly asks to start a new spec-superflow change or route through the spec-superflow workflow. Do not invoke for unrel...

Use when auditing a WSDM submission before the August deadlines - EasyChair setup, the abstract-then-paper week, the appendix-inclusive page budget, the required ethical-considerations section, anonymization that survives Associate-Chair metadata visibility, and desk-reject exposure at a no-rebuttal venue.

Automate Zoho Books accounting workflows including invoice creation, bill management, contact lookup, payment tracking, and multi-organization support through natural language commands

Automate Zoho CRM tasks via Rube MCP (Composio): create/update records, search contacts, manage leads, and convert leads. Always search tools first for current schemas.

Automate Zoho CRM tasks via Rube MCP (Composio): create/update records, search contacts, manage leads, and convert leads. Always search tools first for current schemas.

Automate Zoho Invoice tasks via Rube MCP (Composio): invoices, estimates, expenses, clients, and payment tracking. Always search tools first for current schemas.

Automate Zoho Invoice tasks via Rube MCP (Composio). Always search tools first for current schemas.

Use when packaging AAAI code, data, multimedia appendices, technical appendices, reproducibility evidence, and post-acceptance artifact releases without violating double-blind or immutable-supplement rules.

Use when designing or auditing AAAI experiments for the broad-AI program committee, including baselines, ablations, statistical significance, robustness, human evaluation, AI-for-Social-Impact and alignment/safety evidence, compute and cost reporting, and reproducibility-checklist alignment for Phase-1 survival.

Use when packaging AAMAS multiagent code, environments, opponent and population sets, random seeds, game definitions, and logs as anonymous supplementary evidence or a public post-acceptance release, even without a separate artifact badge, so that game-theory and MARL reviewers can inspect and re-run the interaction claims.

当你在为《自动化学报》(Acta Automatica Sinica, AAS) 稿件准备代码与数据可用性材料、判断本刊是否设有独立制品评审(artifact evaluation)徽章制度时调用。讲清本刊现状(以同行评议为主、无独立徽章制度的现况为待核实)、如何主动提供匿名可复现的代码/数据以增强说服力、控制仿真与实物实验制品的组织，帮助控制/自动化/模式识别方向的中文稿在 Acta Automatica Sinica 外审中用可用制品提升可信度。

Use when packaging code, datasets, prompts, model outputs, or annotation materials for an ACL submission under ACL Rolling Review, covering anonymized supplement archives, scientific-artifact items of the Responsible NLP checklist, licensing and intended-use documentation, data statements, and post-acceptance public release.

Use when designing or auditing experiments for an ACL paper, covering tuned LLM baselines, multi-dataset and multilingual evaluation, statistical significance and variance, human evaluation with agreement reporting, contamination and prompt-sensitivity controls, ablations, and error-analysis expectations in NLP reviewing.

Use when auditing an ACL submission before an ACL Rolling Review cycle deadline, covering long/short paper page budgets, the mandatory Limitations section, Responsible NLP checklist, anonymized PDFs and supplements, preprint declarations, dual-submission rules, resubmission linking, and ARR desk-reject triggers on OpenReview.

Use when deciding whether a project fits ACL versus EMNLP, NAACL, EACL, TACL, Computational Linguistics, COLM, or an ML venue, covering contribution typing for NLP work, long-versus-short paper choice, the annual theme track, Findings-tier expectations, and sharpening the computational-linguistics framing before writing starts.

Use when packaging code, models, datasets, or media as ACM MM (ACM Multimedia) artifacts — building the anonymous review package versus the public release, and choosing between the Open Source Software Competition, the Dataset track, the Reproducibility track, and main-track supplementary evidence, each with its own blinding and expectations.

Use when designing or auditing the experiments of an ACM MM (ACM Multimedia) paper — matched baselines per modality, ablations that isolate the cross-modal fusion, user studies or QoE measurement where the claim is subjective, dataset and media licensing, and honest compute reporting, so evidence supports a multimedia claim.

Use when auditing an ACM MM (ACM Multimedia) submission for OpenReview readiness — thematic-area choice, the 6-8 page ACM sigconf budget, references-only overflow, double-blind anonymity versus the single-blind Reproducibility/Open-Source/Dataset tracks, supplementary media, dual submission, desk-reject triggers, and last-week sequencing.

'Build this skill automates the adaptation of pre-trained machine learning models using transfer learning techniques. it is triggered when the user requests assistance with fine-tuning a model, adapting a pre-trained model to a new dataset, or performing... Use when appropriate context detected. Trigger with relevant phrases based on skill purpose. '

How to use the Adaptyv Bio Foundry API and Python SDK for protein experiment design, submission, and results retrieval. Use this skill whenever the user mentions Adaptyv, Foundry API, protein binding assays, protein screening experiments, BLI/SPR assays, thermostability assays, or wants to submit protein sequences for experimental characterization. Also trigger when code imports `adaptyv`, `adaptyv_sdk`, or `FoundryClient`, or references `foundry-api-public.adaptyvbio.com`.

This skill should be used for advanced LLM evaluation: LLM-as-judge systems, direct scoring, pairwise comparison, rubric calibration, evaluator bias mitigation, confidence scoring, and automated quality assessment.

This skill should be used when the user asks to \"implement LLM-as-judge\", \"compare model outputs\", \"create evaluation rubrics\", \"mitigate evaluation bias\", or mentions direct scoring, pairwise comparison, position bias, evaluation pipelines, or automated quality assessment.

Use when an American Economic Journal: Applied Economics (AEJ: Applied) manuscript's headline estimate must be shown to survive specification, sample, and inference choices before submission or in an R&R. Builds the robustness suite a sophisticated referee expects; it does not establish the primary identification (aeja-identification) or format the exhibits (aeja-tables-figures).

Use when running the final pre-submission preflight for the American Economic Journal: Microeconomics (AEJ: Micro) via the AEA submission system — single-blind review, the 100-word abstract, JEL classification, the submission fee, format, and the AEA Data and Code Availability Policy. Final checks; it does not draft content.

Use when anticipating how AEJ: Economic Policy referees and editors will read a manuscript, before submission or before an R&R, to pre-empt the objections that sink policy-evaluation papers. Maps likely pushback to fixes and calibrates expectations; it does not write the response letter (see aejpol-rebuttal) or fix the identification.

Use when an AEJ: Economic Policy manuscript needs a framework that maps reduced-form estimates into a welfare, cost-benefit, or distributional policy object — sufficient statistics, MVPF, optimal-policy, or a small applied model. Builds the estimate-to-welfare bridge and states its assumptions; it does not run the empirical estimation or write the prose.

This skill should be used for time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search. Use when working with temporal data, sequential patterns, or time-indexed observations requiring specialized algorithms beyond standard ML approaches. Particularly suited for univariate and multivariate time series analysis with scikit-learn compatible APIs.

当你为《电子学报》(Acta Electronica Sinica, AES) 投稿准备代码、数据与硬件设计等研究制品(artifact)的可用性说明时使用。中文学报暂无独立的 artifact evaluation 徽章委员会，本技能说明本刊现状、如何自愿开放代码/数据以增强稿件可信度、如何在正文与附录中规范披露制品、如何在双盲阶段匿名托管仓库、以及电子/信号处理类工作(算法、电路、FPGA、数据集)的制品打包要点。帮助作者在没有强制徽章的前提下最大化《电子学报》稿件的可复现说服力。

Create and train AI learning plugins with AgentDB's 9 reinforcement learning algorithms. Includes Decision Transformer, Q-Learning, SARSA, Actor-Critic, and more. Use when building self-learning agents, implementing RL, or optimizing agent behavior through experience.

Use when evaluating the model and analyzing results for an Agricultural Systems (AgSy) manuscript so it survives expert systems review — independent model evaluation (observed vs. simulated, fit statistics), sensitivity and uncertainty analysis, and trade-off / scenario analysis across the system. Guides evaluation norms; it does not fabricate results or run the model.

Use when writing the response to an Agricultural Systems (AgSy) revision decision. AgSy review is single anonymized with at least two expert systems reviewers and an editor decision, and revisions often turn on model evaluation, sensitivity/uncertainty, and trade-off framing. The response must convert each reviewer without alienating the editor. Structures the response letter; it does not fabricate new results.