Results for “verifiable-randomness”

Randomly selects winners from lists, spreadsheets, or Google Sheets for giveaways, raffles, and contests with fair, transparent selection.

Validate cryptographic implementations against known attacks and edge cases using Wycheproof test vectors.

Picks random winners from lists, spreadsheets, or Google Sheets for giveaways, raffles, and contests. Ensures fair, unbiased selection with transparency.

Analyze RAM dumps with Volatility 3 to detect malware, process injection, network connections, and credential theft during incident response.

Builds a 3D volatility surface for any optionable ticker, mapping implied volatility across strike price and time to expiration to identify cheap, expensive, or anomalous options.

Find sources for every numerical claim in the draft, add inline hyperlinks, and add internal links to brand-reference articles. Triggered after /draft.

汇总某个经管实证变量在文献中的测算口径、数据来源、模型角色和项目可用性

Decompose an unknown quantity into 3-5 estimable factors and produce a defensible order-of-magnitude answer without needing precise data. Load when the user needs to size something without data — market size, resource requirements, effort estimates, user numbers, costs — or when a decision is blocked by "we don't know the numbers". Also triggers on "ballpark this", "rough estimate", "how big is this market", "how long would this take", "how many users", or when deep-thinking diagnoses a sizing/estimation frame. The goal is not precision — it is a defensible answer that enables a decision to be made. Based on Enrico Fermi's estimation method.

Collect volatile forensic evidence from a compromised system following order of volatility, preserving memory, network connections, processes, and system state before they are lost.

Validate backup integrity through cryptographic hash verification, automated restore testing, corruption detection, and recoverability checks to ensure backups are reliable for disaster recovery and ransomware response scenarios.

Extract cached credentials, password hashes, Kerberos tickets, and authentication tokens from memory dumps using Volatility and Mimikatz for forensic investigation.

Track weekly funding rounds across configurable verticals with primary-source verification, per-round analysis, and risk assessment.

Debugging constant Markov regime features in RL observations - when HMM probabilities show uniform values instead of dynamic regime estimates

E1-Quantitative Analysis Guide with Code Generation & Sensitivity Analysis VS-Enhanced with Full 5-Phase process: Avoids obvious analyses, explores innovative methodologies Expanded to include qualitative analysis (thematic, grounded theory, content, narrative) Absorbed E4 (Analysis Code Generator) and E5 (Sensitivity Analysis - Primary Study) capabilities Use when: selecting statistical/qualitative methods, interpreting results, checking assumptions, generating code, sensitivity analysis Triggers: statistical analysis, ANOVA, regression, t-test, power analysis, assumption checking, effect size, thematic analysis, grounded theory, content analysis, narrative analysis, NVivo, ATLAS.ti, coding, qualitative data, R code, Python code, SPSS syntax, sensitivity analysis, robustness check

Calculates IV Rank and IV Percentile for any ticker to determine whether implied volatility is high or low relative to its 252-day history, and provides trading signals based on IV zones.

Validate Pleasur.ai Stage 01 blog-keyword candidates with the Business potential, Intent, and Difficulty method using current Ahrefs evidence. Use before AIO vetting and prioritization to reject poor business fits, mismatched search intent, and SERPs the brand cannot realistically win.

VALIS registration for CODEX: rigid + non-rigid with tuned smoothing. Earlier 'rigid-only' conclusion was caused by a parameter passing bug — all non-rigid tests ran with unsmoothed OpticalFlowWarper.

Design and implement Monte Carlo methods for uncertainty quantification, risk analysis, and probabilistic simulations across scientific and financial domains. Use when "monte carlo, random sampling, uncertainty quantification, risk analysis, stochastic simulation, MCMC, variance reduction, probabilistic, " mentioned.

A git SHA pins the transformation.

Shuffle repetitive JSON objects safely by validating schema consistency before randomising entries.

NLVR2: A Visual Reasoning Benchmark for Natural Language

Review a code change for changed behavior that could regress without reliable verification catching it. Use when checking whether a change is adequately verified.

Combined verification — recite (description quality via cold-read prediction) + validate (schema compliance) + review (health checks). Use as a quality gate after creating notes or as periodic maintenance. Triggers on "/verify", "/verify [note]", "verify note quality", "check note health".

Strategic patterns for solving intractable problems through cascading approximation, self-improvement, and heterogeneous evaluation from DeepMind's AlphaGo system

Generates at most one token recommendation and one prediction-market pick per run, each with a falsifiable thesis, entry, sizing, and kill criterion. Returns NO_PICK when no candidate meets the bar.

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.