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Found 1,927 Skills
Design multi-agent harnesses for long-running autonomous coding tasks. Covers generator/evaluator loops, context reset strategy, sprint contracts, and the planner-generator-evaluator architecture from Anthropic's harness research.
Set up an LLM-judge evaluation that extracts canonical use cases for a PostHog feature at scale and streams the results to a Slack channel as a live feed. Use when someone wants to understand how users are actually using a specific AI/LLM-powered feature in production — what they're investigating, what questions they're trying to answer, and what patterns surface — without manually reading hundreds of traces. Assumes the feature emits `$ai_generation` and `$ai_evaluation` events with `$session_id` linkage to the trigger user's recording (the standard setup post the session-summary linkage PRs).
Investment-banking pitch book for strategic alternatives — trading comps, precedent transactions, valuation football field, DCF sensitivity, strategic-options matrix, process recommendation. Built by adapting `assets/template.html` so IB-specific chrome, disclosure bands, and source labels are preserved. Use for Board / sell-side discussion materials. Not a VC fundraising deck (see html-ppt-pitch-deck). Workflow adapted from Anthropic financial-services Pitch Agent (Apache-2.0).
Create institutional-quality equity research initiation reports through a 5-task workflow. Tasks must be executed individually with verified prerequisites - (1) company research, (2) financial modeling, (3) valuation analysis, (4) chart generation, (5) final report assembly. Each task produces specific deliverables (markdown docs, Excel models, charts, or DOCX reports). Tasks 3-5 have dependencies on earlier tasks.
Build institutional-grade comparable company analyses with operating metrics, valuation multiples, and statistical benchmarking in Excel/spreadsheet format. **Perfect for:** - Public company valuation (M&A, investment analysis) - Benchmarking performance vs. industry peers - Pricing IPOs or funding rounds - Identifying valuation outliers (over/under-valued) - Supporting investment committee presentations - Creating sector overview reports **Not ideal for:** - Private companies without comparable public peers - Highly diversified conglomerates - Distressed/bankrupt companies - Pre-revenue startups - Companies with unique business models
Retrieve analyst financial estimates including Revenue and EPS projections with low/high ranges and analyst coverage. Use when analyzing forward expectations, consensus estimates, valuation inputs, or comparing projections to historical performance.
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.
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.
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.