Weekly charts can produce conflicting signals and vague forecasts. This skill structures chart evidence into trends, levels, patterns, and probability-weighted scenarios.

Social research can be difficult when results lack context, source links, or clear evidence boundaries. Jev Social gathers browser-grounded records from supported platforms and returns a source-linked report.

News research needs dated sources and reliable follow-up across public channels. This skill guides SentryDock searches, source-linked briefings, reviewed monitors, and verified alert delivery.

Teams often lack a consistent way to identify timely buying signals for a specific ICP segment. This skill creates a ranked hunt list with sources, cadence, freshness rules, and implied pain.

Broad customer segments and generic messaging make operational pain difficult to identify. This skill guides structured research linking recent signals, pain, timing, roles, and recipient vocabulary.

Pricing reviews often produce opinions without a consistent score or action order. This skill evaluates 30 checks and turns gaps into three prioritized levers and a 90-day remediation plan.

Guessed citation lists do not show which names an answer actually attached. This skill structures observed names, a date, and a method around one buyer question.

Choosing a model without current availability, pricing, or capability data can cause failed requests and poor tradeoffs. This skill queries the live RouteMux catalogue for the models your key can call.

Brands struggle to measure how AI systems mention them and their competitors. BotSee manages research inputs, runs analyses, and turns results into actionable reports.

AI search engines may overlook a brand when its website language differs from common queries and cited sources. This skill uses BotSee evidence to identify gaps and propose focused copy changes.

Manual Google research makes search results difficult to reuse in automated workflows. This skill retrieves structured results, AI Overviews, and follow-up answers through Pangolinfo APIs.

Market uncertainty makes risk signals and hedge choices difficult to compare. This skill routes requests into structured fear, volatility, hedging, and research-quality workflows.

Portfolio research can become fragmented across profiles, theses, themes, watchlists, and alerts. This skill routes each request into a structured workflow powered by LLMQuant Data.

Market research can become fragmented across macro indicators, sentiment measures, and event markets. This skill routes each question to a focused workflow with dates, data windows, caveats, and portfolio context.

Macro research often mixes indicators, market pricing, and portfolio exposures without consistent dates or assumptions. This skill structures the analysis through focused LLMQuant workflows.

Investors often have data but lack a consistent framework for comparing business quality, valuation, growth, and risk. This skill routes the question to a suitable investor lens and grounds the analysis in dated LLMQuant Data.

Equity derivative analysis requires reliable contract terms, market data, and clear risk framing. This skill routes each request through a focused, evidence-based workflow.

Local business research requires searching listings and gathering details and reviews. This skill documents paid fetcher.sh requests for these tasks through HTTP and MCP.

Cross-border teams need clear analysis of credit terms, financing choices, clearing routes, and authenticity risks. This skill provides structured reviews and compliant recommendations.

Gold projects combine technical data, volatile economics, and complex financial rules. This skill structures evidence, tests assumptions, and identifies compliant financing paths.