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Found 1,904 Skills
Iteratively inspect traces, interview the user, and create LangSmith online evaluators one at a time. Use specifically for creating online evaluators for use within LangSmith -- use "eval-engineering" for Harbor-style online evaluations.
Comprehensive quality auditing and evaluation of tools, frameworks, and systems against industry best practices with detailed scoring across 12 critical dimensions
Retrieve analysts' price target summary for any stock using Octagon MCP. Use when evaluating analyst sentiment, upside/downside potential, consensus expectations, and tracking target trends over time.
Intelligent recommendation system analysis tool that provides implementations of multiple recommendation algorithms, evaluation frameworks, and visual analysis. It requires user behavior data, product information, or rating data for use, supports recommendation algorithms such as collaborative filtering and matrix factorization, and generates personalized recommendation results and evaluation reports.
Detailed report for individual stocks. Generate a financial analysis report by specifying a ticker symbol. Displays valuation, undervaluation judgment, and shareholder return ratio (dividends + share repurchases).
Score assistant responses for relevance on a strict 1-5 scale, then return strict JSON only with score, rationale, and improvement suggestions. Use when the user asks to evaluate relevance, grade relevance, or critique topical alignment.
Conduct multi-dimensional comparative analysis based on user-input technical options or project requirements, and output structured technology selection reports. Applicable scenarios: front-end framework selection, back-end technology comparison, database selection, deployment solution evaluation
Score how well a creator fits a brand's niche on a 1-10 scale with detailed written rationale. This skill should be used when evaluating creator-brand fit, scoring niche alignment, checking if an influencer matches a brand, assessing creator relevance, rating a creator's fit for a campaign, vetting a creator for niche match, deciding whether a creator is right for a brand, comparing creators by brand fit, or reviewing an influencer's profile against campaign requirements. For full creator vetting beyond niche fit (brand safety, rates, compliance), see creator-vetting-scorecard. For writing outreach to creators who pass vetting, see outreach-writer.
Comprehensive analytics audit of website codebase to identify trackable elements and assess analytics readiness. Use when users want to "audit my analytics", "scan for trackable elements", "find what I can track", "analyze my website for tracking opportunities", or before implementing GTM tracking. Scans HTML/JSX/TSX/Vue for all clickable elements (buttons, links, forms, etc.), identifies existing tracking code, evaluates DOM structure for analytics, and provides recommendations. Acts as senior frontend engineer with GA4 expertise.
Evaluate creative work against explicit taste preferences. Use when drafting to align with project aesthetics, when reviewing to surface preference conflicts, or when generating voting options to reflect diverse tastes.
Build recommendation systems with collaborative filtering, matrix factorization, hybrid approaches. Use for product recommendations, personalization, or encountering cold start, sparsity, quality evaluation issues.
Evaluate AI contribution in projects using the AI Assessment Scale (AIAS) 5-level framework. Measure AI involvement from no AI to full AI exploration across development stages.