Results for “opportunities”

Finding and expanding keyword opportunities for free — mining Search Console queries for high-impression/low-position pages, expanding via Google Autocomplete, and snapshotting SERPs with web search; optional paid DataForSEO volume/difficulty data.

Analyze Azure resources and IaC files to identify cost optimization opportunities, calculate savings, and create GitHub issues for tracking.

Audits iOS app source code and metadata to identify App Store rejection risks and optimization opportunities, producing a structured compliance report.

Audits product flows to find delight opportunities, then specifies micro-interactions, animations, and usability risk assessments that balance playful design with functional clarity.

Query Google Search Console for SEO data including search queries, top pages, CTR opportunities, URL inspection, and sitemaps to analyze search performance and indexing status.

Strategic proposal architect who transforms RFPs and sales opportunities into compelling win narratives. Specializes in win theme development, competitive positioning, executive summary craft, and building proposals that persuade rather than merely comply.

Build an Opportunity Solution Tree (OST) to structure product discovery — map a desired outcome to opportunities, solutions, and experiments.

Review technical and strategy documents for codebase drift, strategic alignment, cross-document conflicts, simplification opportunities, engineering quality, and document organization. Use when auditing whether docs should be kept, updated, merged, split, moved, archived, or deleted.

Mines a codebase for evidence-backed improvement opportunities, forcing two escalation gates to surface breakthrough ideas, and outputs a ranked portfolio with a plan seed without implementing.

Find existing articles on the brand's own blog covering the target keyword or related topics. Extract reusable modules, internal-linking opportunities, and product use cases to anchor the new article in the brand's existing voice.

Use this skill when a user asks for SEO keyword research, keyword discovery, search volume analysis, keyword difficulty, search intent mapping, topic clusters, content opportunities, competitor keyword gaps, or a keyword strategy for a domain, URL, product, market, or seed topic. When a website is provided, crawl and interpret the site first, then use AIsa API access to DataForSEO keyword, SERP, trend, Labs, and OnPage endpoints plus AIsa LLM reasoning to find non-brand keyword opportunities. Use when: the user needs web search, research, source discovery, or content extraction.

Evaluates Power BI data model architecture, relationships, storage modes, and performance to identify optimization opportunities and ensure adherence to best practices.

Record and analyze post-trade outcomes for trading signals, tracking false positives, missed opportunities, and regime mismatches to generate feedback for signal aggregation and skill improvement.

Recommends the optimal Claude model tier (Opus, Sonnet, or Haiku) for a given task by analyzing reasoning depth, blast radius, domain expertise, output length, and correctness cost, and suggests parallelization opportunities.

Build an Opportunity Solution Tree from outcomes to opportunities, solutions, and tests. Use when a stakeholder request needs problem framing before you decide what to build.

Screen US stocks for high-quality dividend opportunities combining value characteristics, attractive yields, and consistent growth using a two-stage screening approach with FINVIZ Elite and FMP APIs.

Creative discovery partner for ideation and concept shaping. Use when brainstorming, exploring product ideas, expanding vague concepts, comparing directions, finding opportunities, creative ideation. Triggers: 'brainstorm', 'product ideas', 'concept exploration', 'idea expansion', 'creative thinking', 'product discovery', 'what if', 'I have an idea'.

Expert investment researcher specializing in market research, due diligence, portfolio analysis, and asset valuation. Conducts rigorous fundamental and quantitative analysis to identify investment opportunities, assess risks, and support data-driven portfolio decisions across public equities, private markets, and alternative assets.

Identifies and analyzes statistical arbitrage opportunities through pair trading, using correlation analysis, cointegration testing, and z-score calculations to generate entry/exit signals for market-neutral strategies.

Shared vocabulary for designing deep modules. Use when the user wants to design or improve a module's interface, find deepening opportunities, decide where a seam goes, make code more testable or AI-navigable, or when another skill needs the deep-module vocabulary.

Prediction market arbitrage & alpha scout. Searches Polymarket and Kalshi for the same event, runs cross-platform arb math (including fees), and ranks opportunities by profitability. Use when asked to "find arb", "scout markets", "find edge", or scan a specific topic across prediction markets.

Daily inbound freelance-job discovery across the markets and platforms the brand chose — scrapes job posts via Claude in Chrome (Freelancer.com API where available), scores each for service fit, deduplicates, and drops matches into a Notion opportunities DB. Runs daily on cron schedule.

Sweeps a codebase or UI for places that would genuinely benefit from motion, applying a strict gate to reject over-animation, and proposes precise animation recipes without implementing them.

Automates detection engineering workflows in Google SecOps by extracting threat intelligence, generating detection opportunities, simulating attacker behavior with synthetic events, evaluating rule coverage, and creating new YARA-L 2.0 rules to close gaps.

Use to find upgrade, seat-growth and new-use-case signals that customers give support and nobody routes anywhere. Trigger for "find upsell opportunities in support", "customers hitting plan limits", "which accounts are asking about enterprise features", expansion signals from tickets, or support-sourced pipeline.

Parses complex problems into DAG (Directed Acyclic Graph) execution structures. Decomposes tasks into nodes with dependencies, identifies parallelization opportunities, and creates optimal execution plans. Activate on 'build dag', 'create workflow graph', 'decompose task', 'execution graph', 'task graph'. NOT for simple linear tasks or when an existing DAG structure is provided.

Find arbitrage opportunities across Polymarket and Kalshi prediction markets via AIsa API. Scan sports markets for cross-platform price discrepancies, compare real-time odds, verify orderbook liquidity. Use when user asks about: prediction market arbitrage, cross-platform price differences, sports betting arbitrage, odds comparison, risk-free profit, market inefficiencies.

Maps the end-to-end customer experience from awareness to advocacy — touchpoints, emotions, friction points, and improvement opportunities per stage. Use when identifying drop-off points, improving onboarding, or understanding the full user lifecycle. Triggers on: customer journey, user journey, journey map, touchpoints, onboarding experience, funnel analysis, churn points, aha moment, drop-off, user lifecycle.

Expert PR and media relations guidance for earned media, press coverage, and reputation building. Use when writing press releases, crafting media pitches, developing journalist relationships, planning embargo strategies, managing crisis communication, placing thought leadership, building analyst relations, submitting award applications, or measuring PR coverage. Use for media outreach, press kits, speaking opportunities, and earned media strategy.

When the user wants to find co-marketing partners, plan joint campaigns, or brainstorm partnership opportunities. Use when the user says 'co-marketing,' 'partner marketing,' 'joint campaign,' 'who should we partner with,' 'integration marketing,' 'cross-promotion,' 'collaborate with another company,' 'partnership ideas,' or 'co-brand.' For customer referral programs, see referrals. For launch-specific partnerships, see launch.

Logs and scores skill usage quality, tracking output effectiveness, user satisfaction signals, and improvement opportunities. Expert in skill analytics, quality metrics, feedback loops, and continuous improvement. Activate on "skill logging", "skill quality", "skill analytics", "skill scoring", "skill performance", "skill metrics", "track skill usage", "skill improvement". NOT for creating skills (use agent-creator), skill documentation (use skill-coach), or runtime debugging (use debugger skills).

Use to design the process that gets a revenue signal out of support and to the account owner without turning agents into sellers or degrading support quality. Trigger for "route upsell leads from support to sales", "support-sourced pipeline process", "should agents flag opportunities", designing a CS-to-sales handoff, or a handoff programme where agents have stopped flagging.

Layer 1b of the keyword research pipeline. Finds keyword opportunities by comparing the brand's blog against competitors AND by expanding seeds + modifiers via Semrush (phrase_fullsearch / phrase_related). Auto-discovers competitors via domain_organic_organic when none are provided, derives the keyword gap via domain_domains, tags every row with `gap_mode`, and outputs a candidate-keyword CSV ready for downstream BID/AIO vetting.

Search a codebase or UI for places that don't animate but should, and reject everything that shouldn't. Read-only; it proposes motion with exact values, it does not implement it. Use when the user asks "what could be animated here?" or wants to "make this feel more alive". For fixing existing animations, use `improve-animations` or `review-animations` instead. Source: github.com/emilkowalski/skills.

Use to assemble a fair, evidence-backed coaching pack for a support agent's one-to-one from QA evaluations and conversation history. Trigger for "prepare a coaching session for X", "what areas does X need to improve", "areas of markdown for this agent", "what coaching opportunities stand out", "build a coaching agenda from these tickets", or preparing a weekly or monthly agent review.

Lightweight scanner tracking Smart Money market concentration across all Hyperliquid assets. Flags assets accelerating up the ranks before they become crowded top-3 plays. IMMEDIATE_MOVER signal fires on 10+ rank jumps with quality filters (erratic history, velocity gate, trader count floor, max leverage check). One API call per scan, runs every 60 seconds. Use when detecting SM rotations, finding emerging opportunities early, or monitoring rank acceleration patterns.