Matemàtiques

Càlculs matemàtics, fórmules i estadística

Skills: 409–432 de 446
mmbmf1

geojson-postgis

mmbmf1

Serialize PostGIS geometry rows into a GeoJSON FeatureCollection for map display (4326, Feature + properties).

Desenvolupament d’API 0 fa 8 mesos
midhunxavier

Convert Document

midhunxavier

Convert between LaTeX and DOCX formats. Preserves structure, citations, math equations, figures, and tables during conversion.

Àmbit acadèmic 0 fa 8 mesos
magfrump

business-plan-critique-unit-economics

magfrump

Critically review a business-plan-shaped draft (founder pitch, investor deck narrative, go-to-market strategy doc, fundraising memo, product strategy brief, financial model, or similar) using a focused set of unit-economics lenses: CAC, LTV, contribution margin, payback period, and gross-margin trajectory. This skill exists because many early-stage plans look defensible on the moat and market story but quietly fail on the math — the per-customer economics either never work or only work at a scale the business can't reach. Use this skill whenever a draft proposes a business or product strategy and the author wants pressure on whether the unit economics actually compound. Also trigger when the draft quotes CAC, LTV, LTV/CAC ratio, churn, retention, gross margin, contribution margin, payback period, NRR/GRR, or any per-customer profitability figure the author wants pressure-tested. Trigger phrases: "do the unit economics work", "review my CAC/LTV", "critique the financial model", "is this fundable on the numbers", "stress-test the margins", "payback period feedback", "contribution margin critique", "unit economics review", "is the LTV real", "are these margins defensible", "check the per-customer math", "review the CAC assumptions", "what's wrong with my unit economics". Produces a structured Markdown critique with a known section layout (CAC, LTV, Contribution Margin, Payback Period, Gross-Margin Trajectory, Factual Foundation, Overall Assessment). Scope is intentionally narrow: moat/distribution and market-sizing critiques are explicitly deferred to sibling skills (business-plan-critique-moat and the future business-plan-critique-market-sizing) so this skill stays focused on the per-customer math. NOTE: This skill is typically invoked by the draft-review orchestrator, which provides a pre-built fact-check report. If a fact-check report is provided, use it as your factual foundation and do not redo basic fact verification.

Revisió de codi 0 fa 3 mesos
Jackiexiao

xlsx

Jackiexiao

"QUERY LENGTH LIMIT EXCEEDED. MAX ALLOWED QUERY : 500 CHARS"

Processament de dades 0 fa 8 mesos
rozario-dev

bazi-pro

rozario-dev

Professional Bazi analysis skill. Invoke when user asks for "bazi", "fortune telling", "calculate bazi", "eight characters", or "interpret bazi".

Desenvolupament d’API 0 fa 7 mesos
mmbmf1

postgis-extract-xy

mmbmf1

Extract longitude and latitude from PostGIS geometries using ST_X and ST_Y safely.

Processament de dades 0 fa 8 mesos
TriNgo0108

_business-finance-mastery

TriNgo0108

Master financial integrations, competitive analysis, cost optimizations, and business metrics. Use this as a central index to access specialized sub-skills.

Finances 0 fa 8 mesos
cassoli2016

previsao-projecao

cassoli2016

Gera previsões e projeções a partir do histórico (caixa, demanda de cargas, manutenção, churn) sempre com cenários e premissas explícitas. Use para perguntas sobre o futuro ("quanto vou receber", "vai faltar caixa", "quando esse veículo vai quebrar").

Matemàtiques 0 fa 3 mesos
cassoli2016

telemetria-insights

cassoli2016

Transforma telemetria bruta (CAN/J1939) em insights acionáveis — consumo vs alvo, uso de ECO/embalo/freio-motor, detecção de veículo fora da curva e correlação com DTCs. Use para diagnóstico de eficiência e saúde mecânica.

Matemàtiques 0 fa 3 mesos
iamkaf

amber

iamkaf

Amber docs index. Use when building or porting Minecraft mods that use the Amber multiloader library (unified APIs for Fabric/Forge/NeoForge), or when you need quick links to Amber systems (registry, events, networking, commands, config).

Desenvolupament d’API 0 fa 8 mesos
TheWatcher01

xlsx

TheWatcher01

"Use this skill any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .csv, or .tsv file (e.g., adding columns, computing formulas, formatting, charting, cleaning messy data); create a new spreadsheet from scratch or from other data sources; or convert between tabular file formats. Trigger especially when the user references a spreadsheet file by name or path — even casually (like \"the xlsx in my downloads\") — and wants something done to it or produced from it. Also trigger for cleaning or restructuring messy tabular data files (malformed rows, misplaced headers, junk data) into proper spreadsheets. The deliverable must be a spreadsheet file. Do NOT trigger when the primary deliverable is a Word document, HTML report, standalone Python script, database pipeline, or Google Sheets API integration, even if tabular data is involved."

Processament de dades 0 fa 8 mesos
Tzeusy

memory-taxonomy

Tzeusy

Education domain memory taxonomy for concept entity resolution, predicates, permanence, tags, and example fact patterns.

Matemàtiques 0 fa 3 mesos
brixtonpham

3d-graphics

brixtonpham

"3D web graphics with Three.js (WebGL/WebGPU). Capabilities: scenes, cameras, geometries, materials, lights, animations, model loading (GLTF/FBX), PBR materials, shadows, post-processing (bloom, SSAO, SSR), custom shaders, instancing, LOD, physics, VR/XR. Actions: create, build, animate, render 3D scenes/models. Keywords: Three.js, WebGL, WebGPU, 3D graphics, scene, camera, geometry, material, light, animation, GLTF, FBX, OrbitControls, PBR, shadow mapping, post-processing, bloom, SSAO, shader, instancing, LOD, WebXR, VR, AR, product configurator, data visualization, architectural walkthrough, interactive 3D, canvas. Use when: creating 3D visualizations, building WebGL/WebGPU apps, loading 3D models, adding animations, implementing VR/XR, creating interactive graphics, building product configurators."

Generació de codi 0 fa 8 mesos
YPYT1

homebrew

YPYT1

Homebrew package manager for macOS. Search, install, manage, and troubleshoot packages and casks.

Eines de línia d’ordres 0 fa 8 mesos
smouj

data-prep

smouj

Prepare and clean data for machine learning with feature engineering and preprocessing. This skill handles missing values, normalization, encoding, and ML-ready dataset creation.

Processament de dades 0 fa 7 mesos
tonyflo79

proof-inventory

tonyflo79

Catalog, classify, and score all available proof elements for a product or offer. Use after research (Skill 01) is complete and you need to build a comprehensive inventory of testimonials, clinical studies, data points, credentials, awards, media mentions, and other proof assets. Produces a scored proof inventory with gap analysis and promise ceiling calculation. The proof inventory determines what claims you can credibly make — without it, copy makes promises the proof can't support. Trigger when users mention proof inventory, testimonials, evidence audit, social proof, clinical proof, proof scoring, or promise ceiling. Requires research handoff from Skill 01.

Analítica 0 fa 7 mesos
terrylica

arxiv-source-first-paper-ingest

terrylica

Read an arXiv paper faithfully by fetching the authors' own LaTeX source instead of OCR-ing the PDF. Extracts every display equation with its label, environment and enclosing proposition, renders each to MathML, and proves usability by compiling each formula with a real TeX engine. Use when you need a paper's formulas exactly — to replicate a method, implement a loss function or custom objective, verify a quoted number, or check a claim against what the authors actually wrote. TRIGGERS - read this paper, get the paper, arxiv paper, extract formulas from a paper, replicate a method, implement the loss from, verify the paper's numbers, machine-readable paper, latex source, mathml, e-print.

Operacions amb fitxers 0 fa 2 mesos
YuukiAS

bayesian-ppl-diagnostics

YuukiAS

Executable guidance for Bayesian workflows using Stan/CmdStanPy, brms, PyMC, and ArviZ, with legacy JAGS/OpenBUGS paths and Rcpp acceleration patterns.

Matemàtiques 2 fa 2 mesos
aiagentskills

xlsx

aiagentskills

"Comprehensive spreadsheet creation, editing, and analysis with support for formulas, formatting, data analysis, and visualization. When Claude needs to work with spreadsheets (.xlsx, .xlsm, .csv, .tsv, etc) for: (1) Creating new spreadsheets with formulas and formatting, (2) Reading or analyzing data, (3) Modify existing spreadsheets while preserving formulas, (4) Data analysis and visualization in spreadsheets, or (5) Recalculating formulas"

Processament de dades 0 fa 9 mesos
cuba6112

numpy-statistics

cuba6112

Standard and NaN-robust statistical functions for data analysis, histograms, and correlation matrices. Triggers: statistics, mean, nanmean, histogram, corrcoef, percentile, std.

Processament de dades 0 fa 10 mesos
The-Interdependency

gonol-build

The-Interdependency

"Construction, closure, and replay contract for gonols across UCNS and EDCM. Load this when building or reviewing UCNS geometry used by gonols, or building EDCM character, word, definition, or recursive-relation gonols. UCNS owns geometry; EDCM owns text construction. The required EDCM order is characters -> words -> definitions -> recursive gonol relations. Pronunciation is not required unless an explicitly declared later experiment makes it part of the construction. Do not load for unrelated geometry, ordinary prose editing, or measurement over already-closed gonols."

Matemàtiques 0 fa 2 mesos
mmbmf1

postgis-dwithin

mmbmf1

Distance-based spatial filtering with ST_DWithin, using index-friendly and unit-safe patterns.

Generació de codi 0 fa 8 mesos
epun

threejs-fundamentals

epun

Three.js scene setup, cameras, renderer, Object3D hierarchy, coordinate systems. Use when setting up 3D scenes, creating cameras, configuring renderers, managing object hierarchies, or working with transforms.

Matemàtiques 0 fa 2 mesos
JetSquirrel

csv-data-summary

JetSquirrel

Analyzes CSV files, generates comprehensive summary statistics, identifies data patterns, and creates visualizations using Python and pandas. Automatically adapts analysis based on data type (sales, customer, financial, survey, operational).

Revisió de codi 0 fa 9 mesos