Results for “derivatives”

Symbolic mathematics in Python with SymPy — solve equations algebraically, perform calculus (derivatives, integrals, limits), manipulate algebraic expressions, work with symbolic matrices, and generate executable code from formulas. Use when exact symbolic results are needed rather than numerical approximations, or for physics, number-theory, and geometry computations involving variables and parameters. Part of the AlterLab Academic Skills suite.

Algebra Based Derivation Skill

Botany Based Derivation Skill

Generates Mermaid diagrams from code graphs, including call graphs, class hierarchies, module dependency maps, and data flow visualizations.

Converting repository changes into detailed learning documents. Use when turning diffs into teaching materials, recording design decisions, or creating onboarding materials for new members.

Extract employee, employer, earnings, deductions, tax, and net pay from Spanish or Latin American payroll slips.

Extract Lineage from Fabric Artifacts

DeFi Primitives

Use this skill when working with symbolic mathematics in Python. This skill should be used for symbolic computation tasks including solving equations algebraically, performing calculus operations (derivatives, integrals, limits), manipulating algebraic expressions, working with matrices symbolically, physics calculations, number theory problems, geometry computations, and generating executable code from mathematical expressions. Apply this skill when the user needs exact symbolic results rather than numerical approximations, or when working with mathematical formulas that contain variables and parameters.

Extract merchant, date, line items, tax, and total from receipts.

上市公司财报/季报/年报/业绩的深度因果分析，覆盖A股、港股、美股和中概股。用于解读财报表现、亮点/风险、收入利润等指标变动、超预期或低于预期原因，以及针对毛利率、现金流、费用率等具体变量的归因问题。不用于纯股价、估值、评级、目标价、非财报新闻或未锚定具体公司报告期的宏观行业讨论。

Extract shipper, consignee, order references, carton lines, weights, and package totals from packing lists.

Find adjacent vendors and subs (not top market primes) who fill a capability gap against a displacement target using USASpending flows and SAM entity signals. Use when user defines a teaming gap and wants vault-ready partner shortlist with citations.

Interactive knowledge graph analysis. Routes natural language questions to graph scripts, interprets results in domain vocabulary, and suggests concrete actions. Triggers on "/graph", "/graph health", "/graph triangles", "find synthesis opportunities", "graph analysis".

Extract parties, obligations, restrictions, permitted disclosures, and expiry dates from non-disclosure agreements.

Extract structured knowledge from source material. Comprehensive extraction is the default — every insight that serves the domain gets extracted. For domain-relevant sources, skip rate must be below 10%. Zero extraction from a domain-relevant source is a BUG. Triggers on "/reduce", "/reduce [file]", "extract insights", "mine this", "process this".

Extract paginated product listings from e-commerce category pages, search results, or keyword searches with filters like price, brand, rating, and stock status. Supports Amazon, eBay, Walmart, Shopify, WooCommerce, and Google Shopping.

Extract structured fields from cmr waybill documents.

Extract structured fields from p60 documents.

Calculus Design Expert Skill

Extract structured fields from cfdi nomina documents.

Reduction is a trade, not an improvement.

Transforms A/B test and product experiment data into actionable readouts with hypothesis, metrics, interpretation, and decision.

Derive selection thresholds from market data instead of hardcoding. Trigger when: (1) reviewing hardcoded parameters, (2) volume/price thresholds seem arbitrary, (3) selection returns too many/few candidates.

OpenTelemetry observability patterns: traces, metrics, logs, context propagation, OTLP export, Collector pipelines, and troubleshooting

Use this skill when working with symbolic mathematics in Python. This skill should be used for symbolic computation tasks including solving equations algebraically, performing calculus operations (derivatives, integrals, limits), manipulating algebraic expressions, working with matrices symbolically, physics calculations, number theory problems, geometry computations, and generating executable code from mathematical expressions. Apply this skill when the user needs exact symbolic results rather than numerical approximations, or when working with mathematical formulas that contain variables and parameters.

Use this skill when working with symbolic mathematics in Python. This skill should be used for symbolic computation tasks including solving equations algebraically, performing calculus operations (derivatives, integrals, limits), manipulating algebraic expressions, working with matrices symbolically, physics calculations, number theory problems, geometry computations, and generating executable code from mathematical expressions. Apply this skill when the user needs exact symbolic results rather than numerical approximations, or when working with mathematical formulas that contain variables and parameters.

Use this skill when working with symbolic mathematics in Python. This skill should be used for symbolic computation tasks including solving equations algebraically, performing calculus operations (derivatives, integrals, limits), manipulating algebraic expressions, working with matrices symbolically, physics calculations, number theory problems, geometry computations, and generating executable code from mathematical expressions. Apply this skill when the user needs exact symbolic results rather than numerical approximations, or when working with mathematical formulas that contain variables and parameters.