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Found 1,944 Skills
Launch a meta-judge then a judge sub-agent to evaluate results produced in the current conversation
Evaluate the reproducibility of technical articles. Dispatch a subagent to simulate a first-time reader reproducing the work locally and list missing information. Use as the final check on a draft before publication.
Use when you need to implement or improve Java metrics observability with Micrometer — including meter design, naming/tag conventions, cardinality control, timers/counters/gauges/distribution summaries, percentiles/histograms, Actuator/Prometheus integration, and metrics validation through tests. This should trigger for requests such as Improve metrics; Apply Micrometer; Add metrics observability; Refactor Micrometer instrumentation. Part of cursor-rules-java project
Guides advanced long-term actuarial mathematics (SOA ALTAM)—survival models, life insurance and annuity APVs, premiums and reserves (equivalence principle, Thiele), multiple decrement and Markov states, yield-curve discounting, mortality improvement, longevity risk, profit testing, and mortality graduation. Tool-agnostic, concept-first. Use when the user mentions advanced long-term actuarial mathematics, ALTAM, survival model, life insurance reserve, annuity valuation, equivalence principle, Thiele equation, multiple decrement, force of mortality, longevity risk, mortality improvement, actuarial present value, or net premium reserve—not ASTAM/P&C (advanced-short-term-actuarial-mathematics), workpapers only (actuarial-analyst), appointed actuary (appointed-chief-actuary), assumption governance (assumption-setting), ALM detail (asset-liability-management), or exam-only deliverables.
Build quick IRR/MOIC sensitivity tables for PE deal evaluation. Models returns across entry multiple, leverage, exit multiple, growth, and hold period scenarios. Use when sizing up a deal, stress-testing assumptions, or preparing IC returns exhibits. Triggers on "returns analysis", "IRR sensitivity", "MOIC table", "what's the return at", "model the returns", or "back of the envelope".
Evaluate a skill against the Legal Skill Design Framework — thirteen design parameters (including trust-surface, freshness, schema validation, and conflict detection), three legal failure modes, and a three-band verdict (Ready / Some Concern / Material Concerns). Use when deciding whether to trust a community skill before installing it, before deploying a first-party skill to your team, or whenever the user asks "should I trust this?" or "is this skill well-designed?". Runs automatically as part of /legal-builder-hub:skill-installer.
Compare the differences in business quality, growth, profitability, valuation and catalysts of peer candidate companies horizontally, and provide conclusions on relative strengths and weaknesses. It is applicable to scenarios such as choosing between two candidate stocks, selecting the best among peers in an industry, and establishing a priority tracking order.
Perform comprehensive financial analysis including DCF modeling, ratio analysis, and financial statement evaluation for companies and investment opportunities
Use when the user says "get started with Cekura", "set up Cekura", "onboard to Cekura", "I'm new to Cekura", "help me set up my agent", "how do I use Cekura", "walk me through Cekura", "configure my project", "first time using Cekura", or needs guidance on initial platform setup. Covers two onboarding paths: **testing** (default — build evaluators and run simulated calls) and **observability** (ingest production call logs and evaluate them).
Use when the user asks to "create a metric", "write a metric", "design a metric", "build a metric for", "evaluate agent performance", "measure call quality", "track a KPI", "add a workflow metric", "improve my metric", "fix a metric", "debug metric results", "set up quality scoring", or "what metrics do I need". Also relevant when discussing LLM judge prompts, custom code metrics, evaluation triggers, VALID_SKIP patterns, section extraction, or metric best practices for Cekura voice AI agents. Covers both creating new metrics and reviewing, iterating on, or troubleshooting existing ones.
Analyze multi-round evaluation score data, count various indicators, and calculate rating levels. Suitable for analyzing score trends and calculating S/A/B ratings
Reviews pitch decks and investor presentations. Reads slide content, evaluates narrative flow, problem/solution clarity, market sizing, competitive positioning, financial projections, team credibility, and ask clarity. Generates a scored pitch-review.md with slide-by-slide feedback, overall score, top improvements, investor objection predictions, and comparisons to successful decks. Use when reviewing fundraising materials, investor decks, or pitch presentations.