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Found 9,300 Skills
Guides actuarial consulting engagements—client scoping and SOW design, stakeholder communication (CFO, risk, boards, regulators at overview level), due diligence and M&A actuarial support, reserving/pricing/capital review programs, model validation and opinion support, regulatory interaction prep, and deliverable governance (memos, exhibits, management presentations). Use when the user mentions actuarial consulting, actuarial engagement, reserve opinion, due diligence actuarial, model validation engagement, actuarial memo, SOW actuarial, regulatory actuarial, M&A reserves, or actuarial review—not deep technical modeling execution (actuary), P&C line education only (property-casualty-insurance), legal advice (commercial-counsel), or generic management consulting without actuarial lens (business-consultant).
Convert any data file to another format: CSV, Parquet, JSON, Excel, GeoJSON, and more. Use when the user says "convert to parquet", "save as xlsx", "export as JSON", "make this a CSV", "turn into parquet", or any variation of format-to-format conversion for data files. Also triggers when the user wants to write Parquet, Excel, or other binary formats that Claude cannot produce natively.
For in-depth research on the core investment logic of individual stocks, focusing on individual stock research / fundamental analysis / institutional research. This Skill is mainly applied in scenarios such as question answering, report writing, and financial article creation. The output content of this report is relatively extensive, making it unsuitable for simple conversation scenarios. For acquiring various information and data, the wind.financial.data tool can be used with appropriate keywords or keyword combinations. After users input a stock name, they expect to quickly obtain a high-quality individual stock analysis similar to the style of sell-side analysts.
Hand a Prisma Next question or report off to the team — file a GitHub issue (bug or feature request), or route Q&A / design discussion / direct-team-contact to the Prisma Discord at pris.ly/discord. Use for bug, bug report, file an issue, report a bug, feature request, missing feature, this should be a feature, file this, this is a bug, this is broken, surprising behaviour, this doesn't work, file feedback, send feedback, capability gap, file via prisma-next-feedback, ask the team, talk to the team, talk to the Prisma team, talk to Prisma, Discord, Prisma Discord, Q&A, design feedback, is this the intended way, how should I do X, extension author question, extension author needs help.
Use when a BizOps lead, COO, or process-improvement owner needs to document an end-to-end business process (procurement, employee onboarding, incident handoff, customer-onboarding, claims adjudication) in BPMN-style notation, measure cycle times by stage, surface where work spends most of its time waiting vs. being worked, and quantify the gap between processing time and total elapsed time. Pairs Lean / Six Sigma / Theory-of-Constraints canon with deterministic stdlib-only Python tools to produce a process map, a ranked bottleneck list (with severity + root-cause hypothesis), and a cycle-time analysis (P50, P90, value-add ratio, Little's-Law throughput). Distinct from sales-pipeline, system-reliability (SLO), and strategic-OKR work — this is tactical process documentation for internal operations.
Start here. Introduces what NemoClaw is, what agent skills are available, and which skill to use for a given task. Use when discovering NemoClaw capabilities, choosing the right skill, or orienting in the project. Trigger keywords - skills, capabilities, what can I do, help, guide, index, overview, start here.
Explains how to run NemoClaw on a remote GPU instance, including the deprecated Brev compatibility path and the preferred installer plus onboard flow. Use when deploying NemoClaw to a remote VM, onboarding a Brev instance, or migrating away from the legacy `nemoclaw deploy` wrapper. Trigger keywords - deploy nemoclaw remote gpu, nemoclaw brev cloud deployment, nemoclaw plugins, openclaw plugins, install openclaw plugin, nemoclaw onboard from dockerfile, nemoclaw brev web ui, nemoclaw getting started, brev quickstart, nvidia nemotron agent, nemoclaw sandbox hardening, container security, docker capabilities, process limits.
Give your AI agents capabilities through tools (function calling). Helps you identify what your AI needs to do, create tool definitions, and attach them to AI Config variations.
Build or adapt a local browser/CDP harness to drive and inspect a web, IDE, or Electron UI. Use for local UI verification, screenshots, accessibility snapshots, perf profiles, visual diffs, or reproducing UI bugs.
Valuation and pricing framework focusing on valuation analysis / pricing logic / investment decisions. This Skill is mainly applied in scenarios such as answering user questions, writing reports, and creating financial articles. This report generates extensive content and is not suitable for simple conversation scenarios. Various information and data can be obtained via the wind.financial.data tool using appropriate keywords or keyword combinations. Users want to know how to value a company, the level of its current valuation, why the market is willing to assign this valuation, and whether there is room for revaluation.
Write CLI scripts using the cyclopts framework. Use this skill when creating any command-line script or developer utility — place it in bin/ using cyclopts, not argparse, click, typer, or bare sys.argv.
Use whenever the user mentions LLM prompt/prefix cache misses, cached_tokens=0, cache_read_input_tokens/cache_creation_input_tokens, prompt_cache_key, cache_control/cachePoint placement, stable prefixes, tool/schema stability, TTFT/prefill latency, OpenAI/Claude/Bedrock/OpenRouter routing, vLLM/SGLang KV reuse, or LLM cost/speed regressions on repeated long prompts. Use when reviewing LLM request shape changes: prompt text, message order, request builders, tools, schemas, response_format, provider API surface, model/router settings, agent loop structure, context compaction, or inference deployment. Use for speeding up agents only when prompt-cache stability, TTFT, or cache cost is central. Do not use for generic prompt writing, generic RAG design, token counting, or non-LLM performance.