890 skills · sorted by relevance
Drafts a one-page anonymous company profile for sell-side M&A outreach before a confidentiality agreement is signed. It organizes business highlights, financial metrics, and transaction details, then checks for information that could reveal the company’s identity.
Analyze Donald Trump’s negotiations, public messaging, and decisions using frameworks drawn from public records. Compare possible next moves with probabilities, confidence levels, and unknown factors, or switch to roleplay to simulate his responses in a given situation.
Examine recorded calls and voicemails for signs of AI-generated speech. Extract acoustic features, classify samples with machine learning, and prepare reports with confidence scores and sound visualizations to support voice impersonation investigations.
Collect indicators of compromise, technical clues such as suspicious domains and file hashes, from incident evidence. Add context and confidence scores, then prepare them for detection, blocking, and structured sharing with partners.
Build threat actor profiles from public reports, social media, code repositories, and other intelligence sources. Correlates indicators, maps related infrastructure and attack techniques, and produces structured dossiers with confidence assessments about who may be responsible.
Investigate suspicious IP addresses, domains, URLs, file hashes, and email artifacts using multiple threat intelligence sources. Assess confidence that each indicator is malicious, check links to known campaigns, and document evidence for blocking, monitoring, or allowing it.
Investigate repository behavior, architecture, or possible causes without changing files. Trace relevant code and supporting material, then rank explanations by evidence and confidence, with concrete file references and clear distinctions between observations, conclusions, and unresolved questions.
Turn search results from chat, email, documents, and other sources into a coherent answer. Merge duplicate information, retain source references, highlight conflicting accounts, and reflect source freshness and authority when expressing confidence in the findings.
Checks factual claims in articles and reports against current sources or independently queried original data. Applies corrections, assigns one of six confidence levels to each claim, and produces a sourced report with an overall pass or fail assessment.
Turns user corrections and recurring mistakes into actionable rules with confidence scores. It records when each rule applies and why it matters, so relevant lessons can be retrieved before similar work begins.
Build three-tier bookings forecasts from sales opportunities and historical conversion data. Project recurring revenue by customer cohort, assess the reliability of each sales stage, and present forecast numbers alongside their assumptions.
Draft freelance contracts, project proposals, and confidentiality agreements with clauses tailored to US, EU, UK, or DACH contexts. Organize scope, payments, ownership, and deliverables in Markdown, with instructions for conversion to Word.
Estimate development effort using affected code, design documents, dependencies, and past sprint results. Get optimistic, expected, and pessimistic day estimates, along with a confidence level, key risks, and a suggested breakdown into smaller tasks.
Find open issues affected by a proposed code change. Identify additional problems it may fix or requested behavior it may conflict with, then report supporting code differences, issue symptoms, and confidence levels.
Turn selected research conversations or notes into themes supported by evidence and counterexamples. Distinguish observed behavior from preferences and hypotheses, assess confidence, and suggest a small next experiment with an observable measure of success.
Review PDF and Office documents for language errors, contradictions, confidential information, factual inaccuracies, and calculation mistakes. Produce an annotated copy with issue severity and suggested corrections, using external sources and calculations where needed.
Research topics across multiple sources, cross-check findings, and verify source URLs before producing a report with confidence labels. Choose from quick lookups to iterative investigations that preserve findings, with community sources prioritized for questions about public reactions.
Design systems that use language models to judge AI responses. Covers scoring criteria, comparisons between two answers, bias reduction, confidence calibration, and checks against human judgments to make automated quality assessments more consistent and traceable.
Convert PDF, PowerPoint, Excel, and Word documents into structured Markdown for search and information extraction. Outputs include document metadata, a parsing confidence score, and the parser used, with fallback parsers available when earlier attempts fail.
Classify messages, rate content, or estimate probabilities using defined question types. Receive machine-readable answers, with confidence scores for classification and ratings, and apply the same questions to multiple inputs in a batch.
Continue suitable tasks when web search repeatedly fails by assessing whether existing knowledge is sufficient. Mark unverified claims, distinguish confidence levels, and provide a follow-up checklist so readers can see what still needs checking.
Scan source code for security weaknesses with Semgrep after approving the target and rulesets. Choose full results or focus on important findings, then receive merged results and a record of failed or skipped scans.
Plan authorized security tests involving phone calls, text messages, physical access, and USB devices. Helps develop scenarios from public information, document interactions, and assess how staff verification procedures and physical controls respond.
Design charts and dashboards that show data distributions, uncertainty, missing values, and sample sizes clearly. Choose visual forms that preserve meaningful variation and explain where averages, aggregation, or interval choices could mislead readers.